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Linking colloid deposit morphology and clogging

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Title:
Linking colloid deposit morphology and clogging insights by measurement of deposit fractal dimension
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Roth, Eric James ( author )
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Denver, CO
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University of Colorado Denver
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Permeability ( lcsh )
Filters and filtration ( lcsh )
Colloids ( lcsh )
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bibliography ( marcgt )
theses ( marcgt )
non-fiction ( marcgt )

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Clogging is an important limitation to essentially any technology or environmental process involving flow in porous media. Examples include (1) groundwater remediation, (2) managed or natural aquifer recharge, (3) hydrocarbon reservoir damage, (4) head loss in water treatment filters, (5) fouling in porous media reactors, and (6) nutrient flow for plants or bacteria. Clogging, that is, a detrimental reduction in permeability, is a common them in each of these examples. Clogging results from a number of machoism, including deposition of colloidal particles (such as clay minerals), which is the focus of this research. Colloid deposits reduce porosity, which is recognized to play an important role in clogging, as expressed in the Kozeny-Carman equation. However, recent research has demonstrated that colloid deposit morphology is also a crucial variable in the clogging process. Accordingly, this thesis reports a series of laboratory experiments with the goal of quantifying deposit morphology as a fractal dimension, using an innovative technique based on static light scattering (SLS) in refractive index matched (RIM) porous media. For experiments conducted at constant flow, with constant influent suspension concentration, and initially clean porous media, results indicate that increased clogging is associated with colloid deposits having smaller fractal dimensions, that is, more dendritic and space-filling deposits. This result is consistent with previous research that quantified colloid deposit morphology using an empirical parameter. Clogging by colloid deposits also provided insight into the more complex clogging mechanisms of bio clogging, mineralization, and bio mineralization. Although this line of work was originally motivated by problems of clogging in groundwater remediation, the methods used and the insight gained by correlating clogging with fractal dimension are expected to have relevance to other areas where flow in porous media overlaps with colloid science; Hydrogeology, petrology, water treatment, and chemical engineering.
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Thesis (M.S.)--University of Colorado Denver. Civil engineering
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Department of Civil Engineering
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by Eric James Roth.

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Full Text
LINKING COLLOID DEPOSIT MORPHOLOGY AND CLOGGING:
INSIGHTS BY MEASUREMENT OF DEPOSIT FRACTAL DIMENSION
by
ERIC JAMES ROTH
B.F.A. University of Colorado Boulder, 2002
B.S. University of Colorado Denver, 2011
A thesis submitted to the
Faculty of the Graduate School of the
University of Colorado in partial fulfdment
of the requirements for the degree of
Master of Science
Civil Engineering Program
2013


This thesis for the Master of Science degree by
Eric James Roth
has been approved for the
Civil Engineering Program
by
David C. Mays, Chair
James C.Y. Guo
Tim C. Lei
November 12, 2013
n


Roth, Eric James (M.S., Civil Engineering)
Linking Colloid Deposit Morphology and Clogging: Insights through Categorization by Fractal
Dimension
Thesis directed by Assistant Professor David C. Mays
ABSTRACT
Clogging is an important limitation to essentially any technology or environmental process
involving flow in porous media. Examples include (1) groundwater remediation, (2) managed or
natural aquifer recharge, (3) hydrocarbon reservoir damage, (4) head loss in water treatment fdters,
(5) fouling in porous media reactors, and (6) nutrient flow for plants or bacteria. Clogging, that is, a
detrimental reduction in permeability, is a common theme in each of these examples. Clogging
results from a number of mechanisms, including deposition of colloidal particles (such as clay
minerals), which is the focus of this research.
Colloid deposits reduce porosity, which is recognized to play an important role in clogging, as
expressed in the Kozeny-Carman equation. However, recent research has demonstrated that colloid
deposit morphology is also a crucial variable in the clogging process. Accordingly, this thesis reports
a series of laboratory experiments with the goal of quantifying deposit morphology as a fractal
dimension, using an innovative technique based on static light scattering (SLS) in refractive index
matched (RIM) porous media. For experiments conducted at constant flow, with constant influent
suspension concentration, and initially clean porous media, results indicate that increased clogging is
associated with colloid deposits having smaller fractal dimensions, that is, more dendritic and space-
filling deposits. This result is consistent with previous research that quantified colloid deposit
morphology using an empirical parameter.
Clogging by colloid deposits also provides insight into the more complex clogging
mechanisms of bio clogging, mineralization, and bio mineralization. Although this line of work was
originally motivated by problems of clogging in groundwater remediation, the methods used and the
insight gained by correlating clogging with fractal dimension are expected to have relevance to other
iii


areas where flow in porous media overlaps with colloid science: Hydrogeology, petrology, water
treatment, and chemical engineering.
The form and content of this abstract are approved. I recommend its publication.
Approved: David C. Mays
IV


DEDICATION
This thesis is dedicated to scientists who arent afraid to take on insurmountable odds in the
effort to create a more balanced world. Also to those who realize that natural systems are complex,
and that a complete understanding of natural processes may ultimately be unattainable... but its
worth a shot.
Importantly, I would like to dedicate this thesis to my family. Thanks to my parents Jim and
Vera, my brother Paul, and my girlfriend Sarah for support and inspiration. In particular, I dedicate
this thesis to my daughter Ivy, with the hopes that insights gained through my research might improve
the natural environment that will someday be her inheritance.
v


ACKNOWLEDGEMENTS
This research has passed through many hands before reaching mine. First, I must thank Dr.
David C. Mays, the Principal Investigator for this project. David kept the fire burning through almost
a decade of research which was sometimes extremely frustrating and always difficult. I couldnt have
done my phase of the research without the efforts of my predecessors and collaborators: Asnoldo
Benitez, Kevin Kennedy, Kevin Harris, Adam Kanold, Orion Cannon, Ryan Taylor, and Michael
Mont-Eton. I would also like to thank Dr. Tim Lei for his optics expertise, Dr. Benjamin Gilbert for
his unparalleled knowledge of fractals and their measurement, and Ken Williams for his much
appreciated help at the Old Rifle field site. The U.S. Department of Energy Subsurface Biochemical
Research program provided funding for this research which was essential.
vi


TABLE OF CONTENTS
Chapter
1. Introduction...........................................................................1
1.1 Motivation.....................................................................1
1.1.1 Groundwater Remediation...............................................1
1.1.2 Other Applications....................................................2
1.1.3 Problems with Current Models..........................................2
1.2 Background.....................................................................4
1.2.1 Flow Through Porous Media.............................................4
1.2.2 Colloids and Clogging.................................................6
1.2.3 Fractal Dimension.....................................................7
1.3 Overview.......................................................................8
1.3.1 Type of Research......................................................8
1.3.2 Problem Statement.....................................................8
1.4 Research Scope.................................................................9
1.5 Experimental Framework.........................................................9
2. Literature Review.....................................................................11
3. Experimental Methods..................................................................13
3.1 Summary of the Experimental Approach..........................................13
vii


3.2 Apparatus Components..........................................................14
3.2.1 Fluid Flow System....................................................14
3.2.2 Static Light Scattering Bench........................................14
3.2.3 Head Data System.....................................................15
3.3 Porous Media and Index Matched Fluid..........................................15
3.4 Colloids and Aggregation......................................................16
3.5 Other Measurements............................................................16
3.5.1 Specific Deposit.....................................................16
3.5.2 Porosity.............................................................16
3.5.3 Critical Coagulation Concentration...................................17
3.5.4 Collection and Analysis of Rifle Field Samples.......................17
3.6 Running the Experiments.......................................................17
3.7 Data Analysis.................................................................18
3.7.1 Fractal Dimension....................................................18
3.7.2 Data Reduction.......................................................19
4. Summary of Results.....................................................................20
4.1 Critical Concentration and Porosity...........................................20
4.2 Individual Samples............................................................20
4.3 Sample Sets...................................................................29
5. Conclusion and Discussion..............................................................43
5.1 Individual Samples............................................................43
5.2 Sample Sets...................................................................43
5.3 Overall Conclusions...........................................................43
5.4 Discussion....................................................................44
References................................................................................45
viii


Appendix
A. Experimental Data and Results................................................46
B. Additional Method Information................................................75
IX


LIST OF FIGURES
Figure
1.1 Clogging by colloidal aggregates with different deposit morphology................6
1.2 Fractal dimension of aggregate structures.........................................7
3.1 Experimental summary.............................................................13
3.2 Experimental summary.............................................................14
3.3 Flow cell during operation.......................................................14
3.4 Flow cell schematic..............................................................14
3.5 Static light scattering setup....................................................15
3.6 IQ plot for determination of fractal dimension...................................18
4.1 IQ plot for middle region........................................................21
4.2 Linear region of IQ plot with slope equal to fractal dimension...................21
4.3 Head loss data during deposition and clear flow..................................22
4.4 Specific deposit data............................................................22
4.5 Fractal dimension during deposition and clear flow...............................23
4.6 Fractal dimension versus normalized hydraulic conductivity.......................24
4.7 Fractal dimension versus pore flow velocity......................................24
4.8 Fractal dimension versus ionic strength..........................................25
4.9 Fractal dimension versus pore volumes eluted.....................................25
4.10 Fractal dimension versus specific deposit......................................26
x


4.11 Reynolds number versus fractal dimension.......................................26
4.12 Normalized hydraulic conductivity versus specific deposit......................27
4.13 Fractal dimension versus flow rate, Rifle samples...............................28
4.14 Fractal dimension versus ionic strength, Rifle samples..........................28
4.15 Fractal dimension versus pore fluid colloid concentration.......................28
4.16 Fractal dimension versus specific deposit.......................................29
4.17 Fractal dimension versus normalized hydraulic conductivity......................30
4.18 Normalized hydraulic conductivity versus specific deposit......................30
4.19 Normalized hydraulic conductivity versus pore volumes eluted...................30
4.20 Fractal dimension versus pore volumes eluted...................................31
4.21 Specific deposit versus pore volumes eluted....................................31
4.22a-c Fractal dimension versus pore volumes eluted by pore flow velocity...........32
4.23a-c Specific deposit versus pore volumes eluted by pore flow velocity............33
4.24a-c Fractal dimension versus specific deposit by pore flow velocity..............34
4.25a-c Normalized hydraulic conductivity versus fractal dimension by pore flow velocity..35
4.26a-c Normalized hydraulic conductivity versus specific deposit by pore flow velocity... .36
4.27a-c Normalized hydraulic conductivity versus radius of gyration by pore flow velocity..37
4.28 Fractal dimension versus specific deposit, all regions, by pore flow velocity..38
4.29 Normalized hydraulic conductivity versus radius of gyration, 74 m/day pore flow
velocity, 0.049 M ionic strength................................................39
xi


4.30 Normalized hydraulic conductivity versus radius of gyration, 138 m/day pore flow
velocity, 0.049 M ionic strength......................................................39
4.31 Normalized hydraulic conductivity versus radius of gyration, 292 m/day pore flow
velocity, 0.048 M ionic strength......................................................40
4.32 Normalized hydraulic conductivity versus radius of gyration, 569 m/day pore flow
velocity, 0.048 M ionic strength......................................................40
4.33 Normalized hydraulic conductivity versus radius of gyration, 588 m/day pore flow
velocity, 0.024 M ionic strength......................................................41
4.34 Normalized hydraulic conductivity versus radius of gyration, 691 m/day pore flow
velocity, 0.012 M ionic strength......................................................41
4.35 Normalized hydraulic conductivity versus radius of gyration, 1197 m/day pore flow
velocity, 0.006 M ionic strength......................................................42
4.36 Normalized hydraulic conductivity versus radius of gyration, 1439 m/day pore flow
velocity, 0.006 M ionic strength......................................................42
xii


LIST OF TABLES
Table
1.1 Typical Values of Hydraulic Conductivity..........................................3
4.1 Porosity at various ionic concentration...........................................20
xm


1. Introduction
1.1 Motivation
1.1.1 Groundwater Remediation
One responsibility of environmental and water resources engineers is to mitigate
contaminated groundwater, and within this broad category, there is perhaps no better case study than
uranium contamination at former mill sites. The Old Rifle site in Rifle, Colorado is a prime example.
At Rifle, uranium mine tailings were originally deposited in close proximity to the Colorado River.
Over time uranium seeped into the soil, contaminating the saturated zone and eventually the river. In
the 1990s mine tailings, the source of contamination, were removed. Unfortunately, uranium had
already contaminated a significant amount of soil. Luckily, as with many soil contaminants, the
uranium can be mitigated by injecting specific chemicals into the contaminated zone. At Rifle, one
successful technique has been to supply acetate to Geobacter bacteria already present in the soil.
Acetate bolsters the bacterial colonies by supplying a source of organic carbon. The bacteria reduce
mobile U(VI) to immobile U(IV). The end result is that the uranium stays in the contaminated area
and out of the river. This process works quite well as long as the chemical amendments can
uniformly be applied to contaminated areas. Sadly, uniform application has proven very difficult.
In situ bioremediation efforts like the previous example are constantly plagued by clogging
problems. Often, well screens get caked with biofilms created by the very bacteria stimulated by
remediation efforts. These bio-films cause well screen clogging, making injection or extraction
difficult or impossible. Clogs from mineral precipitates and suspended solids can also inhibit
pumping efficiency.
Another problem is that clogging is present throughout saturated soils, causing large volumes
of soil to have much diminished permeability. In the clogged soil zones, preferential pathways are
forged through the soil matrix. These preferential pathways are like tiny aqueducts, carrying large
flow volume through the pathways instead of evenly through all the soil. To visualize this idea, think
of a dish sponge with a drinking straw stuck through it. While the soil immediately adjacent to the
1


preferential pathway has plenty of exposure to the chemicals, the rest of the soil does not. Therefore,
a tremendous volume of chemical can be injected with little effect on the contamination.
1.1.2 Other Applications
An in situ bioremediation site is not the only situation where clogging is a problem. Clogs
have a detrimental effect on pumping efficiency for groundwater and petroleum extraction. For
purification processes, filters must be back washed or replaced depending on the amount of clogging.
Some reactors and fuel cells utilize flow through porous media; clogs once again knock down the
efficiency.
Stopping clogging is not the only reason to study the phenomenon. Clogs have a major effect
on permeability, an effect which is poorly understood and rarely considered. In many scientific
studies, a better understanding of permeability could be of great use. As an example, recently in situ
genomic mapping of subsurface microbial communities has become an area of great interest. Thanks
to increased computing power, the classification and niche differentiation of bacteria in the subsurface
has become possible at a greater scale. These bacteria are responsible for a multitude of natural
processes which, as is apparent from modem bio-remediation techniques, can be utilized for the
benefit of man. Like any living organism, subsurface bacteria are affected by the environment in
which they are found. Their environment is the soil. When water infiltrates the soil, it supplies or
removes materials that can support or suppress the growth of certain bacterial colonies. Therefore, the
ease of water flow is a key parameter in understanding which bacteria prefer which conditions. A
greater understanding of permeability, specifically at a micro scale is a puzzle piece which should
prove invaluable as the scientific community continues to focus on microbes.
1.1.3 Problems with Current Models
The conveyance of fluids is a very old technology. Consequently, there is a great wealth of
knowledge on the subject. Unfortunately, there is also a deficit of understanding when it comes to
clogging and resulting effects on permeability. A handful of equations are commonly used to model
flow through porous media including the Kozeny-Carman equation which relates hydraulic
2


conductivity (K) to mean grain size and porosity of the media. Kozeny-Carman is the most widely
used equation for estimating hydraulic conductivity and permeability, but the values calculated are
generally inaccurate by multiple orders of magnitude when compared with measured values.
Subsurface flow is very complex and more information is needed. To show just how variable K
values can be in the physical world, refer to Table 1.1. Kozeny-Carman only considers fluid and
media properties, not the characteristics of the suspended solids in the fluid.
Table 1.1 Typical Values of Hydraulic Conductivity (Fitts, 2002)
Material Hydraulic Conductivity, K (cm/sec)
Clean Sand 101 to 1
Silty Sand 10"5 to 101
Clay 10"10to 10'6
Limestone and Dolomite 10vto 1
Sandstone 10 s to 10'3
Igneous and Metamorphic Rock 10 to 10'2
Shale 10-14 to 10's
3


1.2 Background
1.2.1 Flow Through Porous Media
Whether considering groundwater, petroleum reservoirs, or filtration processes, the fluid flow
of concern is in part controlled by the porous media through which it travels. Essentially porous
media consists of the combination of impermeable space, and voids through which the fluid can pass.
Porosity is a property of the porous media, equal to the fraction of media volume containing void
space.
Where n is porosity, Vv is volume of voids, and Vt is the total volume.
Conventionally, porosity and grain size distribution of the media are used to calculate the
hydraulic conductivity of the media using the Kozeny-Carman equation (Fitts, 2002):
porosity, and d50 is the median grain size of the media.
Hydraulic conductivity can also be calculated using the permeability k (Fitts, 2002):
kpwg
K -------
n
where pwg and p are the unit weight and dynamic viscosity of water.
Finally, hydraulic conductivity is used to determine flow rate using Darcys Law:
n = Vv/Vt
K =
4


Q is flow rate, is manometer head difference over manometer distance s, and A is cross-sectional
area. Darcys law is applicable for laminar flows with a Reynolds number less than 10, ideally less
than 1 (Fitts, 2002). Reynolds number, R. can be calculated using characteristic length L (for flow
through porous media, this is mean grain diameter), velocity V. dynamic viscosity u. and fluid density
P-
LVp
R =-
fl
Hydraulic head is synonymous with energy potential, fluids flow from high to low potential
i.e. high to low head. This head difference drives all fluid flows, and is described by a form of the
Bernoulli Equation:
P V2
H =-----b Z + -b hr
Y 2 g J
p
H is total head at a definite location in the flow regime, is pressure over specific weight of fluid and
describes the portion of energy supplied by pressure, z is the energy from elevation above datum,
is velocity squared over doubled gravity and describes the energy supplied by fluid movement, and hf
is energy lost from friction.
Flow rate is the volume of fluid movement over time and can be calculated by taking cross-
sectional area, A, multiplied by flow velocity, V.
Q = VA
Pore flow velocity is similar to V. but describes the velocity for the fluid passing through
porous media.
5


Specific deposit is another important consideration when looking at clogging. For the
purposes of this thesis, specific deposit, er, is the volume of colloids Vc divided by the volume of the
measured area in the flow cell (total volume, V,).
Vr
1.2.2. Colloids and Clogging
Water flows contribute greatly to solid transport and redistribution. For surface flows, this
can easily be seen in the gravel and sand left behind in the street gutter after a heavy rain. For
groundwater, the porous media and slow flow velocities limit the size of solids that can be carried.
Colloids are particles with diameters between 1 (/' and 10"5 meters. Stable colloids, colloids which
have not formed aggregates, stay suspended in the fluid. Clay and silt particles, bacteria, mineral
precipitates, viruses, NAPL droplets, and bio-films can all be considered colloids.
In most situations, the pores through which fluid flows are large enough in relation to stable
colloids as to easily allow passage. However, when chemical conditions are suitable for aggregation,
the resulting colloidal aggregates can get caught in the pore throats. Depending on the specific
deposit (the amount of deposited material) and theoretically deposit morphology (structure of
aggregates), permeability can be reduced. This loss of permeability is considered clogging.
Figure 1.1 Clogging by colloidal aggregates with different deposit morphology (Mays, 2010)
6


1.2.3 Fractal Dimension
The idea of fractal dimension, or fractional dimension, was popularized by Benoit
Mandelbrot in 1967. While studying the coastline of Norway, Mandelbrot considered how the length
of coastline measured increased as the scale of measurement was reduced. In the case of this
coastline, the fractal dimension quantifies how the number of scaled increments changes with the
scale of the increment. In other words, fractal dimension is a measure of geometric complexity as a
function of scale.
Fractal dimension can be useful in describing the compactness of a shape. A straight line
would have a fractal dimension of one. A slightly curved line could be described as having a fractal
dimension of 1.2, perhaps filling the space a little more than the completely straight line. Note that
this compactness property is different than density. This measure of compactness comes in very
handy for describing aggregate structures. Two aggregates with identical mass and density could
have completely different fractal dimension. When considering multiple colloid aggregates that have
become lodged in a pore space, aggregates with lower fractal dimension would take up more space,
and according to the theory of this study, should cause differences in fluid flow.
D = 2.8 D = 2.4 D = 1.8 D = 1.2
Figure 1.2 Fractal dimension of aggregate structures (Min, 2006)
For this study the fractal dimension is considered by the mass length relationship. Where M
is mass, L is characteristic length (radius of gyration), and Z/is fractal dimension.
M~Lf
1


Since specific deposit has a direct effect on hydraulic conductivity, it is useful to also
consider the expanded equation for fractal dimension. Specific deposit can be recalculated as N,
which is the number of colloid particles, kD is a constant of proportionality assumed to be one for this
1.3 Overview
1.3.1 Type of Research
This is exploratory research, with the goal of improving our fundamental knowledge about
factors influencing hydraulic conductivity in porous media. This facet of clogging has not been fully
investigated, so any results will be presented for the first time. Ideally, the data from these
experiments can be used to create a model that could be used in conjunction with historic models.
1.3.2 Problem Statement
Hydraulic conductivity is a measure used to gauge the ease of fluid flow through porous
media. The K value is used in a multitude of fields including groundwater remediation, water and
petroleum extraction, reactor design, and for filtration processes. However, the models which
calculate K in systems with colloids are often inaccurate by orders of magnitude. An improved
fundamental knowledge concerning the role of clogging by colloid aggregates would improve the
accuracy of K calculations.
Hypothetically, the deposit morphology of colloid aggregate structures in conjunction with
specific deposit measurements should fill in some gaps in knowledge. A method for measuring
deposit morphology is being investigated in this thesis. By measuring colloid aggregate structures by
fractal dimension, morphology can be considered as a function of mass and characteristic length. The
fractal dimension measurement will supply crucial information about the overall compactness of
experiment, Rg is radius of gyration, a is colloid radius, and if is fractal dimension.
8


aggregate structures. Further, by considering fractal dimension in conjunction with specific deposit,
head loss, and clean bed porosity, the role of deposit morphology in clogging will be more apparent.
1.4 Research Scope
As shown by Kanold (2008), Nafion can be used as refractive index matched porous media.
Cannon (2010) shows that fractal dimension could be measured in the Nafion. Mont-Eton (2011)
demonstrated that static light scattering measurements could be made in a flow cell containing Nafion
as the refractive index matched porous media. Current research will start by improving the SLS and
flow apparatus for ease of use and dependability. Next, extensive data acquisition will be performed
by running experiments with index matched porous media with flow. Head loss data will be collected
as colloid aggregates are deposited and cause clogging in the flow cell. Additionally, techniques for
measuring specific deposit and porosity will be developed. After data collection, analysis will be
performed and conclusions about the role of deposit morphology in clogging will be made.
1.5 Experimental Framework
This research involves the non-destructive, real time measurement of colloid aggregate
deposition in a flow cell containing transparent porous media. Measurements of head loss and
specific deposit will be collected simultaneously with deposit fractal dimension. The static light
scattering (SLS) bench was designed by Tim Lei, the flow cell manifold was designed by Orion
Cannon, porous media was index matched to fluid by Adam Kanold, and aggregate fractal dimension
measurement was tested by Michael Mont-Eton.
For the research contained in this thesis, flow cell manifold improvements were made
including an improved flow cell-manifold interface and a quick mounting system for the manifold to
the SLS bench, improvements were made to the SLS bench including a light proof, dust inhibiting,
cooling system which also had to isolate the bench from vibration. Other SLS bench improvements
included a vertical actuator for the flow cell and the repair of the pneumatic vibration damping
system. Pressure transducers were added to the flow cell for head data, a method for measuring
specific deposit with the SLS apparatus was developed, a method for measuring porosity of porous
9


media was developed, and the ionic strength at which colloids would aggregate was determined
(critical coagulation concentration). After an iterative process of testing and improving the setup,
flow experiments were conducted at varying ionic concentrations and flow rates. Data were collected,
analysed, and conclusions were made.
10


2. Literature Review
Mays (2007) explains colloid dynamics in aqueous environments under a variety of
conditions. Colloids are defined as suspended constituents with a characteristic diameter of lnm to
10pm. Stable colloids tend to disperse in an aqueous environment, and consequently settle very
slowly. However, flocculation will occur with the right combination of ionic strength, counter ion
valence and pH. Colloids have very high surface area to volume ratios, therefore their behaviour is
dominated by surface chemistry. Electrostatic repulsion will cause dispersion, while van der Waals
forces can lead to flocculation under the right conditions. Which forces will dominate is controlled by
ionic strength, sodium adsorption ratio, and pH. Quirk-Schofield diagrams plot ionic strength versus
sodium adsorption ratio to show where the critical coagulation concentration (CCC) occurs. Above
the CCC line, colloids flocculate, while below the line colloids disperse
Mays (2010) applies these concepts to the topic of clogging in filters, soils, and membranes,
noting that the mechanism for clogging in soils and dead-end membranes is opposite that of granular
media filters. The article ends by signalling the need for further research, using innovative new
methods for measuring in situ deposit fractal dimension and deposit location.
Proof of principle for such a method is reported by Mays et al. (2011) for batch mode, or a
non-flow condition. Mays et al. explain the motivation, methods, results, and limitations of static
light scattering through index-matched porous media to reveal colloidal structure. Most importantly,
fractal dimensions were obtained for test samples by using linear regression of data points. SLS
provides real-time information on dynamic colloidal aggregation, deposition, restructuring, and
mobilization. SLS techniques provide less detailed geometric information than microtomography and
confocal microscopy, and thus would be most effectively utilized in conjunction with other
techniques.
Technical details on SLS are provided in the review by Bushell et al (2002), which discusses
fractal geometry and the techniques used to quantify fractal properties. The basic theory behind the
fractal description of aggregates is discussed, along with computer simulations of the phenomena.
Bushell et al (2002) discusses the strengths and limitations of many techniques, but for the purposes
11


of this summary, light scattering is the most important. Scattering measurements compare scattered
light or radiation with scattering angle
The result of this analysis is a quantitative measurement of fractal geometry, useful for
understanding complex, chaotic, and disordered systems. Objects found in real physical processes
must have a mass fractal dimension between 1 and 3. Computer simulations which follow fractal
theory have been widely used to better understand processes which form natural fractals. However,
these computer models are insufficient for describing real aggregation processes. This is because
aggregation controls fractal dimension, fractal dimension does not control the aggregation process.
Light scattering is preferable for structures of several microns in size. Light scattering is fast,
easy and inexpensive but is complicated by interactions of light and matter. Aggregates are fractal in
terms of kinetics in that they show scale invariance with time. On their own, aggregates restructure in
a self-similar process called Brownian motion. However, when aggregates are exposed to fluid shear
forces, the process is no longer self similar which is apparent from a curved fractal regime in
scattering plots. Additional insight into SLS is provided by the review of Sorensen (2001), which
discusses how fractal aggregates scatter and absorb light. Sorensen considers aggregate behaviour,
explaining that aggregation is random, leading to fractal geometry as a means of measurement. A key
result of his analysis is shown in Figure 3.6.
Performing SLS in porous media requires transparent porous media, which is reviewed by
Izkander (2010), who discusses the use of transparent media for modelling soil. In the book, three
choices for transparent media are investigated: silica powder, silica gel, and aquabeads (also know as
wateijewels). Amorphous silica powder can be used to model clays, silica gels can model sands, and
aquabeads can model sediments or super soft clays.
12


3. Experimental Methods
3.1 Summary of Experimental Approach
A stream of index matched fluid containing colloids and salt will be eluted through a glass
column packed with transparent media. A laser will be passed through the flow column. Light will
interact with colloids and their structures, not the transparent porous media. Static light scattering
data will be collected. Data is then analysed using a log-log plot of scattered light intensity, /, versus
scattering angle, translated into the scattering wave vector Q. The slope of the linear region of the
resulting plot is equal to fractal dimension. Head data, specific deposit, and porosity will be collected
and considered for further data analysis. Numerous samples will be analysed with varying ionic
strength and flow velocity. A thorough explanation of the SLS measurement process can be found in
the thesis by Michael E. Mont-Eton (2011).
Figure 3.1 Experimental summary
13


INDEX-MATCHED
POROUS MEDIA
FRACTAL DIMENSION
OFAGGREGATES
Figure 3.2 Experimental summary
3.2 Apparatus Components
3.2.1 Fluid Flow System
Flow begins with two peristaltic pmnps with adjustable flow rate. One pump supplies flow
from a reservoir containing stable colloids, the other pump supplies flow from a reservoir containing a
salt solution. The two flows join at a confluence point downstream from the pumps at which point
mixing begins. Next, the flow enters the flow cell and flows through the porous media. Fluid exits
the flow cell and then continues into a graduated cylinder as waste.
M aterial:
Pyrex Glass
Wall Thickness:
1.3- 1.5mm
Figure 3.3 and 3.4 Flow cell during operation and flow cell schematic (schematic by Ben Gilbert).
3.2.2 Static Light Scattering Bench
The static light scattering bench was designed by Tim Lei, Benjamin Gilbert, and David
Mays. An intensity controlled helium neon laser with a 633nm wavelength is passed through optical
components, then through the flow cell. Light is scattered from the colloid aggregates. The scattered
light intensity is measured by the rotating detector assembly as a function of scattering angle.
14


Polarizer
HeNe r | 1
Laser
Cylindrical
lens
1/2 wp Chopper
Detector Optical
Saturated block
column
Figure 3.5 Static light scattering setup (Mays et al. 2011)
3.2.3 Head Data System
Head loss is measured across the pressure ports on the flow cell. Tubing from the ports are
routed into Validyne (Northridge, CA) transducers. Validyne software then logs the data. Head loss
is measured for four distinct regions: inlet, middle, and outlet region of the flow cell, and one overall
head loss measurement from the top to bottom of the flow cell manifold.
3.3 Porous Media and Index Matched Fluid
For static light scattering to work, the porous media in the experiments required a high degree
of transparency. In order to achieve media invisibility, the media grains had to have the same index
of refraction as the fluid. Nafion, a synthetic polymer developed by Walther Grot of DuPont and used
as a membrane for a variety of chemical processes, was found to be a good porous media candidate.
Nafion is clear when hydrated, and is somewhat rigid making it a good surrogate for soil. As
deciphered by Adam Kanold, a solution of 42% 2-Propanol (isopropyl alcohol or IP A) and 58%
deionised water has the same index of refraction as the Nafion. The Nafion used in the experiment
Ji Q
was 16-35 mesh and the IPA/H20 mixture has a dynamic viscosity of 0.0027478 (Pang et al.
2007).
15


3.4 Colloids and Aggregation
The colloids used in the experiments were carboxylate modified polystyrene microspheres,
made by Seradyn (Thermo Fisher, Indianapolis, IN). The spheres had a uniform diameter of 106 nm
and were stabilized with carboxylate. In order to initiate aggregation, the microspheres were exposed
to magnesium chloride. For the experiments, varying salt concentrations were used.
3.5 Other Measurements
3.5.1 Specific Deposit
It was necessary to know the time dependent concentration of colloid deposits at specific
locations in the flow cell. It was necessary for these specific deposit measurements to be made in a
non-destructive manner, in real time. Unfortunately, there was no known method to accomplish this.
So a technique was developed using the SLS setup to measure scattered light intensity at a position
independent of deposit morphology. Refer to Appendix B to see a full explanation of the technique.
The specific deposit measurements taken from this technique have proven to be repeatable. Triplicate
scans of unique samples were in accord at lower concentrations. At higher concentrations, values are
not as accurate, but still within reasonable tolerances for error.
3.5.2 Porosity
The Nafion used in the experiment was 16-35 mesh when dry. However, hydration of Nafion
approximately doubles the volume. Furthermore, in order to limit porous media compression during
colloid deposition, enough Nafion was added to the flow cell to be in slight compression. Salinity
also effects the swelling potential of the Nafion and ionic strength is a variable for experimental runs.
For these reasons, the porosity had to be measured in the flow cell for each salt concentration used in
the experiment. A technique was developed which injected vegetable oil into the void space. The
volume of oil was then divided by the total flow cell volume to find the porosity.
16


3.5.3 Critical Coagulation Concentration
In order to know what salt concentrations to use for aggregation, it was necessary to find the
critical coagulation concentration, the salt concentration at which aggregation starts when increasing
salt concentration. For critical coagulation concentration determination, varying amounts of MgCl2
were added to the isopropanol and water solution with the microspheres. The salt concentration
which caused aggregate settling in a reasonable amount of time was found to be between 1 and 2 mM.
3.5.4 Collection and Analysis of Rifle Field Samples
In order to see the efficacy of laboratory results, it was useful to analyze water samples from
the field. There was an opportunity to sample from the DOE Old Rifle field site in Rifle Colorado.
With the help of Ken Williams, the site director, eight samples were collected from four different
wells. Samples were collected at a higher flow rate, then collected with a flow rate of zero.
Measurements for temperature and specific conductance were made at the field site.
Samples were transported back to the lab in de-aired vessels, inside of a cooler. At the lab,
the concentration of colloids was determined by weighing the material left on a 0.2 micron filter.
Batch samples were then prepared and scanned using the SLS apparatus. A comparison could now be
made between results from lab experiments and field samples.
3.6 Running the Experiments
Solutions were prepared and glassware was thoroughly washed in a caustic detergent, then
rinsed with deionized water in advance of experiments. The appropriate amount of dry Nafion was
added to the flow cell and then hydrated with IPA/H20 solution. The Nafion was allowed to hydrate
over night with a constant flow of fresh solution. The next day, the flow cell was hooked up to pre-
calibrated transducers, flow was initiated at the target flow rate with no colloids, and equilibrium was
checked. Equilibrium was assumed when the hydraulic conductivity was stable, this ensured that the
Nafion was not swelling or compressing. Next the SLS bench is calibrated by aligning the laser and
flow column. The flow cell undergoes a blank scan, with no colloids present, to be used in later
17


calculations. Deposition flow (flow with colloids) is then started, along with a stopwatch and data
logging. Scans are performed at different flow cell positions through the duration of deposition flow.
Flow is then stopped, and all regions of the flow cell are once again scanned. A clear flow (flow with
no colloids) is started and more scans are perfonned.
3.7 Data Analysis
3.7.1 Fractal Dimension
For fractal dimension measurements, the scattering intensity verses scattering wave vector
values are plotted on a log-log plot. The absolute value of slope on the plots linear region is equal to
the fractal dimension (Sorensen 2001). Other points to note on the plot are at the beginning and end
of the linear region. As seen in the following figure, radius of gyration (Rg) and individual colloid
radius (r) can also be found in the IQ plot.
Q (1/nm)
Figure 3.6 IQ plot for determination of fractal dimension (modified from Sorensen 2001)
18


Later in the data analysis, it was found that radius of gyration might be a key parameter for
consideration. Unfortunately, the radius of gyration for aggregates in the experiment were found at a
very low scattering angle, which could not be measured using our apparatus. Instead, radius of
gyration was calculated by using the measured fractal dimension and specific deposit. In order to
make this calculations some very big assumptions were necessary. First, it was assumed that there
would be one aggregate per pore space. Next, the number of pore spaces per cell was estimated by
counting Nafion grains. There is a large amount of error associated with these assumptions, thus
radius of gyration measurements are not exact.
3.7.2 Data Reduction
There were multiple data streams for each experiment. Using Microsoft Excel, all data were
combined into spreadsheets for consideration. Plots were then created in order to check the validity of
results and find possible correlations. Correlations were supported by R2 value and by comparison of
trend line slope error associated with the 95% confidence interval.
19


4. Summary of Results
4.1 Critical Coagulation Concentration and Porosity
Critical coagulation concentration, or the minimum salt concentration at which colloids form
aggregates within a reasonable amount of time (less than 5 minutes) was determined to be
approximately 2 mM for magnesium chloride with the polystyrene micro spheres used for the
experiment. For 6.5 grams of Nafion in the flow cell, porosity for various concentrations of MgCl2
are summarized in Table 4.1.
Table 4.1 Porosity at various ionic concentration
Ionic Concentration MgCh Ionic Strength Porosity
(mM) (mM)
1 3 0.05
2 6 0.11
4 12 0.22
8 24 0.26
16 48 0.26
4.2 Individual Samples
A total of 23 flow cell samples were successfully analysed, with a total of 169 SLS scans.
While carrying out the experiment on individual samples, it became evident that certain reoccurring
behaviours were exhibited during each run. As an example, results from scans on sample
2013_01_002_A will be presented here. For information on other samples, refer to Appendix A. For
this sample, influent flow rate was 10.34 mL/min, with an ionic concentration of 2 mM MgCl2, and an
influent colloid concentration of 100 ppm. SLS scans were conducted at three flow cell positions:
inlet, mid, and outlet regions during influent flow. Intensity, I, versus scattering wave vector, Q, data
20


was collected for each scan and then analysed using the IQ plot. Notice that different flow types are
contained in the IQ plot. The first two scans are during colloid deposition, then one scan was
performed while flow was stopped, and finally one scan after a colloid free (clear) solution flow.
I vs Q, Middle Region
1.00E-05
1.00E-09 -I--------------1--------------1--------------1
0.0001 0.001 0.01 0.1
Q (nmA-l)
Figure 4.1 IQ plot for middle region
I vs. Q, Mid Region
1.00E-05
1.00E-06
£
1.00E-07
*5fl fl 1.00E-08
fl 1.00E-09 1.00E-10
0.001
0.01
Q (nmA-l)
y = 1E-I2x"2-044,
R2 = 0.9952
y = lE-lOx'1 6L
R2 = 0.9841
*155.1 ml Eluted
315.4 ml Eluted
-1.261
R2 = 0.9608
y 2E-09x-1-i.A_377 41 m, Eiuted,
No Flow
0.1
y = lE-lOx-15&*-782.4 ml Clear
R2 = 0.9854 Soln. Eluted
Figure 4.2 Linear region of IQ plot with slope equal to fractal dimension
Head loss and specific deposit data were collected simultaneously with the SLS scans. Notice
that head loss increases during colloid deposition flow, indicating clogging. Furthermore, specific
21


deposit also increases as deposition flow continues. For this sample deposition flow was stopped at
approximately 400 mL eluted, then clear solution was eluted for the remainder of data collection.
During the clear flow, head loss and specific deposit both decrease with time. Note, nonnalized head
loss, dH/dHo, does not usually dip below 1 for most samples. The pulse at 900ml eluted indicates a
momentary clog in the inlet region.
Flow
A
^ Inlet Region
Mid Region
Outlet Region
JH
Figure 4.3 Head loss data during deposition and clear flow
Flow
(T=- A
X-'Inlet Region
Mid Region

Outlet Regiot
Flow
Specific Deposit vs Volume Eluted
Figure 4.4 Specific deposit data
22


One of the more interesting results of the individual scans was the evolution of fractal
dimension with time. For all samples, fractal dimension would decrease as deposition flow
commenced, then increase as clear flow was eluted.
Figure 4.5 Fractal dimension during deposition and clear flow
After performing analysis on all of the samples, the data could be compiled. The following
plots show all of the data, excluding only scans which did not meet minimum quality assurance
criteria. These plots show general trends without considering the effects of multiple variables. The
other variables are taken into account in the results of the next section. Trend lines are provided for
plots with trend line slopes higher than the 95% confidence interval, though correlations for unsorted
data were relatively weak.
23


Fractal Dimension
3.5
0 0.2 0.4 0.6 0.8 1 1.2
K/Ko
Figure 4.6 Fractal dimension versus normalized hydraulic conductivity
Pore Flow Velocity (m/day)

A



3000
3500
Figure 4.7 Fractal dimension versus pore flow velocity
24


Fractal Dimension Fractal Dimension
3.5
Ionic Strength (M)
Figure 4.8 Fractal dimension versus ionic strength
Figure 4.9 Fractal dimension versus pore volumes eluted
25


Fractal Dimension
3.5
0.0 -I--------1-------1--------1--------1--------1---------1--------1--------1--------1--------1
0 50 100 150 200 250 300 350 400 450 500
Specific Deposit (ppm)
Figure 4.10 Fractal dimension versus specific deposit
0>
.a
S
s
Z
o
s
&
10
0.1



<*


3.0
3.5

0.01
Fractal Dimension
Figure 4.11 Reynolds number versus fractal dimension
26


Figure 4.12 Normalized hydraulic conductivity versus specific deposit
The preceding shotgun plots of data show some overall trends, but many correlations were
weak since R2 values were typically below 0.5. However, the observed trends do indicate a link
between low fractal dimension and clogging as well as high specific deposit and clogging.
Interestingly, for this unfiltered data there seemed to be little effect on fractal dimension from ionic
concentration or pore flow velocity.
Samples collected from the Old Rifle field site were also successfully measured for ionic
strength and scanned using the SLS bench. It is note worthy that the fractal dimension of aggregates
from the Rifle site are of similar magnitude to aggregates produced in the lab. Also, well G51 was
severely clogged. Well G51 samples exhibited low fractal dimension and high specific deposit which
would indicate clogging according to lab data. Rifle samples were scanned with die SLS apparatus
twice, once before repeated inversion and once after.
27


1.4 I--------1-------r-------1-------1-------1
0 200 400 600 800 1000
Flowrate (ml/min)
Injection Well CD03
Injection Well G51
Monitor Well LR01
X Monitor Well FP101
Figure 4.13 Fractal dimension versus flow rate, Rifle samples
Ionic Strength (M)
Injection Well CD03
Injection Well G51
Monitor Well LR01
XMonitor Well FP101
Figure 4.14 Fractal dimension versus ionic strength, Rifle samples
s
_o
*5n
C
s
5
t3
-
it
Concentration (ppm)
Injection Well CD03
Injection Well G51
Monitor Well LR01
XMonitor Well FP101
Figure 4.15 Fractal dimension versus pore fluid colloid concentration
28


4.3 Sample Sets
Sample sets consist of data that have been grouped or removed in order to eliminate ancillary
variables. First, for quality assurance, individual scans in which die straight transmission factor was
less than or equal to 0.1% were removed since this was the maximum colloid deposition for which the
SLS apparatus could take dependable readings. Next, sample runs in which the Nafion did not hit
equilibrium were removed since this would produce inaccurate head data, probably due to changing
porosity. The remaining data was grouped by flow cell position, pore flow velocity, and flow type
(colloid deposition, no flow, or clear flow). The clear flow groups seemed to exhibit different
characteristics which made sense due to the different flow regime. However, deposit flow and no
flow data were in agreement and thus were combined. The plots were usually left with three or fewer
points. However the data appear very linear, with trend line R2 values around 0.9 and significant
correlation with consideration of the 95% confidence interval. Importantly, all the data groups show
the same trends with similar accuracy. The plots shown in figures 16 through 21 are for the outlet
region, pore velocity of 1197 m/day, ionic strength of 0.006 M, and exclude the clear flow regime.
s
_o
*5n
C
CJ
B
S
13
t3
Concentration (ppm)
Figure 4.16 Fractal dimension versus specific deposit
29


K/Ko
Figure 4.17 Fractal dimension versus normalized hydraulic conductivity
Figure 4.18 Normalized hydraulic conductivity versus specific deposit
0 50 100 150 200 250 300
Pore Volumes Eluted
Figure 4.19 Normalized hydraulic conductivity versus pore volumes eluted
30


Figure 4.20 Fractal dimension versus pore volumes eluted
Figure 4.21 Specific deposit versus pore volumes eluted
The preceding data is representative of most pore velocity/cell position combinations. The
plots clearly indicate a dependence on specific deposit and fractal dimension for hydraulic
conductivity. Importantly, there is also a clear connection between fractal dimension and specific
deposit.
A summary for all the groups was necessary in order to see reoccurring trends. Plots grouped
by the previous criteria were then combined by pore flow velocity. Only data sets with at least three
points were considered. Note that the 3000 m/day pore flow velocity data included in the following
plots is for a salt concentration below the critical coagulation concentration, so the colloids did not
aggregate.
31


(a) Inlet Region
74 m/day
569 m/day
588 m/day
1439 m/day
3000 m/day
0 200 400 600 800
Pore Volumes Eluted
74 m/day
569 m/day
1197 m/day
1439 m/day
3000 m/day
(c) Outlet Region
74 m/day
138 m/day
569 m/day
1197 m/day
1439 m/day
Figures 4.22a-c Fractal dimension versus pore volumes eluted by pore flow velocity.
As shown in figures 4.23a-c, correlation between fractal dimension and pore volumes eluted
is excellent for most data sets. There is a slight variation depending on which region is being
scanned, but behaviour is similar for sets with common ionic strength. Of note is the different slope
for the 3000 mL/day data set, which is the only data set for which I mL/day set shows data for non-aggregated colloids. Also, fractal dimension gets smaller with pore
volumes eluted, but seems to increase toward the outlet, possibly indicating some straining effects.
32


(a) Inlet Region
74 m/day
569 m/day
588 m/day
1439 m/day
3000 m/day
(b) Middle Region
o
s.
O
O
u
u
a>
74 m/day
569 m/day
1197 m/day
1439 m/day
3000 m/day
(c) Outlet Region
74 m/day
138 m/day
569 m/day
1197 m/day
1439 m/day
Figure 4.23a-c Specific deposit versus pore volumes eluted by pore flow velocity.
As shown in figures 4.24a-c, as expected, specific deposit increases with pore volumes eluted
and decreases toward the outlet. Correlation is once again excellent for all data sets. Note
3000m/day, which exhibited no accumulation due to lack of aggregation.
33


(a) Inlet Region
74 m/day
569 m/day
588 m/day
1439 m/day
3000 m/day
(b) Middle Region
74 m/day
569 m/day
1197 m/day
1439 m/day
3000 m/day
0 50 100 150 200 250 300
Specific Deposit (ppm)
74 m/day
138 m/day
569 m/day
1197 m/day
1439 m/day
Figure 4.24a-c Fractal dimension versus specific deposit by pore flow velocity.
For fractal dimension versus specific deposit a correlation between different pore flow
velocities starts to become apparent, especially toward the inlet. This indicates that specific deposit
and fractal dimension are connected. The connection starts to break down near the outlet, possibly
indicating that straining could have an effect.
34


(a) Inlet Region
0.5 1 1.5 2 2.5
Fractal Dimension
74 m/day
569 m/day
588 m/day
1439 m/day
3000 m/day
0.5 1 1.5 2 2.5
Fractal Dimension
74 m/day
569 m/day
1197 m/day
1439 m/day
3000 m/day
0.5 1 1.5 2 2.5
Fractal Dimension
74 m/day
138 m/day
569 m/day
1197 m/day
1439 m/day
Figure 4.25a-c Normalized hydraulic conductivity versus fractal dimension by pore flow velocity.
For normalized hydraulic conductivity versus fractal dimension, correlations are good with
the exception of 1439m/day. However behaviour is quite different among data sets. Note that
3000m/day shows no drop in hydraulic conductivity due to the lack of accumulation.
35


(a) Inlet Region

74 in/day
569 rn/day
588 m/day
1439 m/day
3000 m/day
(b) Middle Region
74 m/day
569 m/day
1197 m/day
1439 m/day
3000 m/day

50 100 150 200
Specific Deposit (ppm)
250
300
74 m/day
138 m/day
569 m/day
1197 m/day
1439 m/day
Figure 4.26a-c Normalized hydraulic conductivity versus specific deposit by pore flow velocity.
Normalized hydraulic conductivity versus specific deposit shows good correlation for each
data set. As expected, clogging increases with an increase in specific deposit. Behaviour seems to be
very dependent on scan region.
36


(a) Inlet Region
Radius of Gyration (m)
74 m/day
569 m/day
I 588 m/day
X< 1439 m/day
3000 m/day
l.E-05 l.E-04 l.E-03 l.E-02 l.E-01 1.E+00 l.E+01 l.E+02 l.E+03
Radius of Gyration (m)
74 m/day
569 m/day
1197 m/day
1439 m/day
3000 m/day
l.E-05 l.E-04 l.E-03 l.E-02 l.E-01 1.E+00 l.E+01 l.E+02 l.E+03
Radius of Gyration (m)
74 m/day
138 m/day
569 m/day
)( 1197 m/day
-*-1439 m/day
Figure 4.27a-c Nonnalized hydraulic conductivity versus radius of gyration by pore flow velocity.
Note that radius of gyration was calculated using assumptions stated in section 3.7.1, and
may be very inaccurate. However, the Rg should give a good estimate for purposes of investigating
behaviour. Radius of gyration accounts for specific deposit and fractal dimension, so it makes sense
that correlations are exhibited. 1439m/day once again shows poor correlation.
37


After considering the grouped data sets, it seemed likely that specific deposit and fractal
dimension work in tandem to influence clogging. When specific deposit increased, fractal dimension
decreased, and clogging became more pronounced. It follows that radius of gyration, which accounts
for specific deposit and fractal dimension, could be the key to understanding clogging. Data was
considered at all flow cell locations for the last roimd of investigation. Keep in mind that radius of
gyration was calculated (not measured) with assumptions.
Fractal Dimension vs Specific Deposit
100 150 200 250
Specific Deposit (ppm)
300
350
74 m/day 0.049 M
138 m/day 0.049 M
292 m/day 0.048 M
A 569 m/day 0.048 M
+ 588 m/day 0.024 M
691 m/day 0.012 M
XI197 m/day 0.006 M
X1439 m/day 0.006 M
3000 m/day 0.003 M
Figure 4.28 Fractal dimension versus specific deposit, all regions, by pore flow velocity.
For fractal dimension versus specific deposit, it would appear that a clear yet somewhat noisy
pattern emerges. Indicating that there is a non-linear relationship between the two, seemingly
independent of pore flow velocity (which due to the effects of salt on Nafion, is also independent of
porosity).
Normalized hydraulic conductivity versus radius of gyration for all regions is shown in
Figures 4.30 through 4.37. Excellent correlation was found for five out of eight pore flow velocities
considered. While trend line slopes and magnitudes were similar for some of die data sets, an overall
correlation unifying all data was still not clear.
38


Figure 4.29 Normalized hydraulic conductivity versus radius of gyration, 74 m/day pore flow
velocity, 0.049M ionic strength.
Figure 4.30 Normalized hydraulic conductivity versus radius of gyration, 138 m/day pore flow
velocity, 0.049M ionic strength.
39


Figure 4.31 Normalized hydraulic conductivity versus radius of gyration, 292 m/day pore flow
velocity, 0.048 M ionic strength.
K/Ko vs Radius of Gyration
A569 m/day 0.048 M
l.E-05 l.E-04 l.E-03 l.E-02 l.E-01 1.E+00 l.E+01
Radius of Gyration (m)
Figure 4.32 Normalized hydraulic conductivity versus radius of gyration, 569 m/day pore flow
velocity, 0.048M ionic strength.
40


K/Ko vs Radius of Gyration
+ 588 m/day 0.024 M
y = -0.0291n(x) + 0.772
R2 = 0.977
Radius of Gyration (m)
Figure 4.33 Normalized hydraulic conductivity versus radius of gyration, 588 m/day pore flow
velocity, 0.024M ionic strength.
1.1 1 0.9 5 08 § 0.7 0.6 0.5 K/Ko vs Radius of Gyration



B691 m/day 0.012 M



l.E-05 l.E-04 l.E-03 l.E-02 l.E-01 1.E+00 l.E+01 Radius of Gyration (m)
Figure 4.34 Normalized hydraulic conductivity versus radius of gyration, 691 m/day pore flow
velocity, 0.012M ionic strength.
41


K/Ko vs Radius of Gyration
l.E-05 l.E-04 l.E-03 l.E-02 l.E-01 1.E+00 l.E+01
Radius of Gyration (m)
XI197 m/day 0.006M
y = -0.0461n(x) + 0.576
R2 = 0.908
Figure 4.35 Normalized hydraulic conductivity versus radius of gyration, 1197 m/day pore flow
velocity, 0.006M ionic strength.
1.1 1 0.9 £ 0.8 § 0.7 0.6 0.5 K/Ko vs Radius of Gyration

/7\ X X
/K w X
* X1439 m/day 0.006 M



l.E-05 l.E-04 l.E-03 l.E-02 l.E-01 1.E+00 l.E+01 Radius of Gyration (m)
Figure 4.36 Normalized hydraulic conductivity versus radius of gyration, 1439 m/day pore flow
velocity, 0.006M ionic strength.
The preceding results show that flow cell region can perhaps be disregarded when considering
hydraulic conductivity versus radius of gyration. It follows that radius of gyration is possibly
unaffected by straining effects.
42


5. Conclusions and Discussion
5.1 Individual Samples
The first noteworthy conclusion is that the data supports a reaffirmation that fractal dimension
can be measured in a flow cell containing index matched porous media. Judging from the low colloid
accumulation and unchanged hydraulic conductivity, solutions with an ionic concentration below one
millimolar MgCl2 do not provide favorable conditions for aggregation, colloid deposition, nor
clogging.
With volume eluted and change in flow regime, the fractal dimension varies. During colloid
deposition, fractal dimension decreases as clogging increases, indicating that a lower fractal
dimension can be associated with increased clogging. When a colloid free flow is supplied to the
clogged column, fractal dimension once again increases as clogging decreases. Interestingly, some
samples showed hydraulic conductivity higher than clean bed conditions, after colloid deposition and
clear flows were applied.
Important trends were noted when the entirety of data collected was plotted. Significant
correlation was apparent from the plots of fractal dimension versus normalized hydraulic
conductivity, specific deposit versus normalized hydraulic conductivity, and fractal dimension versus
specific deposit. These findings indicate that fractal dimension and specific deposit might work in
tandem with respect to hydraulic conductivity. Also, Reynolds number for all samples fell below ten,
indicating that flows were laminar and are therefore applicable for consideration with Darcys Law.
Samples collected at the Old Rifle field site had fractal dimensions ranging from 1.5 to 2.5.
This is a similar to the samples created in the lab, indicating that experimental results could be
considered for field conditions. Finally, the sample from well G51 at the Rifle site had higher fractal
dimension and colloid concentrations than the other wells sampled. Judging from trends found in lab
samples, this well should exhibit more clogging. In fact, well G51 was severely clogged, further
supporting conclusions from lab experiments.
5.2 Sample Sets
By grouping samples by common variables, excellent correlation was achieved for many of
the plots. Specifically, data grouped by pore flow velocity, flow cell region, and flow regime showed
R2 above 0.9 and significant correlation by consideration of 95% confidence interval for fractal
dimension versus normalized hydraulic conductivity, specific deposit versus normalized hydraulic
conductivity, and fractal dimension versus specific deposit.
Combining the plots at various pore flow velocities showed some correlations. There is
strong evidence that radius of gyration measurements could be the missing link which would relate
fractal dimension and specific deposit with hydraulic conductivity. Unfortunately, measuring radius
of gyration was not possible with the SLS apparatus used in the experiment.
5.3 Overall Conclusions
It appears that fractal dimension and specific deposit are connected. Furthermore, these
parameters have been shown to have a significant connection to clogging. This connection is shown
in the analysis of almost all samples. Further experimentation is necessary to find the connection
43


between fractal dimension and specific deposit and the resulting effect on clogging. Specifically by
the use of an SLS setup that can measure radius of gyration.
As seen in figure 4.29, there seems to be a non-linear relationship between fractal dimension
and specific deposit. This finding supplies an interesting insight into the formation of aggregate
deposits. The next step here would be to further calibrate the in-situ concentration measurement
technique developed during this research, specifically at higher concentrations.
5.4 Discussion
This experiment has yielded compelling results. Fractal dimension does seem to have
a significant impact on clogging. When specific deposit is also considered, the effects on
permeability are undeniable. It would appear likely that measurement of the radius of gyration could
be key to understanding the clogging process. The next step of this research would be to run more lab
experiments with an updated SLS apparatus which could measure radius of gyration. New
experimental parameters would also be very useful since working with Nafion had some hidden
pitfalls which have now been discovered. It is also time to investigate more field samples in order to
collect empirical evidence.
44


REFERENCES
Bushell, G.C., Yan, Y.D., Woodfield, D., Raper, J., Amal, R. (2002). On techniques for the
measurement of the mass fractal dimension of aggregates. Advances in Colloid and
Interface Science 95, 1-19.
Fitts, C. (2002). Groundwater Science. London: Academic Press.
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Izkander, Magued. (2010). Modelling with Transparent Soils, 1st Ed., Springer, Berlin.
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Dispersion Phenomena Journal of Natural Resources & Life Sciences Education, Volume
36, 45-52.
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Membranes Journal of Environmental Engineering, 136(5), 475-480.
Mays, D. C. (2010). Linking Deposit Morphology and Clogging in Subsurface Remediation
Funding Request to Office of Biological and Environmental Research, 1-30.
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scattering resolves colloid structure in index-matched porous media Journal of Colloid and
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amorphous silicate feature of fractal aggregates and compact particles with complex shapes
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Mont-Eton, M.E. (2011). Quantifying the Morphology of Colloid Deposition in Granular Media
using Fractal Dimension MS thesis U of Colorado, Denver.
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Technology, 35(2), 648-655.
45


Appendix A
Experimental Data and Results
Morphology Parameter vs K/Ko
Morphology Parameter vs Specific Deposit
46


Morphology Parameter vs Fractal
Dimension
a
O.
o>
a
-
a
a.
ex
o
"e
JS
c.
-
o
0.0018
0.0016
0.0014
0.0012
0.001
0.0008
0.0006
0.0004
0.0002
0
-0.0002

0 0.5


1 1.5 2 2.5
Fractal Dimension
3
K/Ko vs Morphology Parameter
Morphology Parameter
74 m/day 0.049 M
138 m/day 0.049 M
A292 m/day 0.048 M
X569 m/day 0.048 M
X588 m/day 0.024 M
691 m/day 0.012 M
+ 1197 m/day 0.006M
-1439 m/day 0.006 M
-3000 m/day 0.003 M
47


Sample ID Flowrate (ml/min) Flow Velocity (m/day) Average Pore Velocity (m/day) Ionic Cone (mM) Ionic Strength (M) Salt Type Nation Size (mesh)
2012_03_001_A_6 0.71 9.0 0 60-100
2012_03_001_A_7 0.65 8.3 0 60-100
2012_03_001_A_11 0.63 8.0 0 60-100
2012_04_002_A_15 6.9 87.9 100 Ca(N03)2 16-35
2012_05_001_A_12 7 89.1 100 Ca(N03)2 16-35
2012_05_001_A_15 7 89.1 100 Ca(N03)2 16-35
2012_05_001_A_21 7 89.1 100 Ca(N03)2 16-35
2012_05_001_A_27 7 89.1 100 Ca(N03)2 16-35
2012_06_001_A_12 3.45 43.9 100 Ca(N03)2 16-35
2012_06_001_A_18 3.5 44.6 100 Ca(N03)2 16-35
2012_06_001_A_24 3.5 44.6 100 Ca(N03)2 16-35
2012_06_001_A_30 3.45 43.9 100 Ca(N03)2 16-35
2012_06_002_A_24 1.83 23.3 100 Ca(N03)2 16-35
2012_06_002_A_27 1.84 23.4 100 Ca(N03)2 16-35
2012_06_002_A_30 1.7 21.6 100 Ca(N03)2 16-35
2012_06_003_A_15 1.95 24.8 100 Ca(N03)2 16-35
2012_06_003_A_21 1.95 24.8 100 Ca(N03)2 16-35
2013_01_002_A_42 10.34 131.7 1197 2 0.006 MgCI2 16-35
2013_01_002_A_48 10.34 131.7 1197 2 0.006 MgCI2 16-35
2013_01_002_A_54 10.34 131.7 1197 2 0.006 MgCI2 16-35
2013_01_002_A_88 10.34 131.7 1197 2 0.006 MgCI2 16-35
2013_01_002_A_41 10.34 131.7 1197 2 0.006 MgCI2 16-35
2013_01_002_A_47 10.34 131.7 1197 2 0.006 MgCI2 16-35
2013_01_002_A_53 10.34 131.7 1197 2 0.006 MgCI2 16-35
2013_01_002_A_82 10.34 131.7 1197 2 0.006 MgCI2 16-35
2013_01_002_A_40 10.34 131.7 1197 2 0.006 MgCI2 16-35
2013_01_002_A_46 10.34 131.7 1197 2 0.006 MgCI2 16-35
2013_01_002_A_52 10.34 131.7 1197 2 0.006 MgCI2 16-35
2013_01_002_A_75 10.34 131.7 1197 2 0.006 MgCI2 16-35
2013_02_001_A_47 5.21 66.3 603 2 0.006 MgCI2 16-35
2013_02_001_A_56 5.21 66.3 603 2 0.006 MgCI2 16-35
2013_02_001_A_62 5.21 66.3 603 2 0.006 MgCI2 16-35
2013_02_002_A_20 5.4 68.8 659 1.81 0.00543 MgCI2 16-35
2013_02_002_A_26 5.4 68.8 659 1.81 0.00543 MgCI2 16-35
2013_02_002_A_47 5.4 68.8 659 1.81 0.00543 MgCI2 16-35
2013_02_002_A_62 5.3 67.5 647 1.81 0.00543 MgCI2 16-35
2013_02_002_A_22 5.4 68.8 659 1.81 0.00543 MgCI2 16-35
2013_02_002_A_28 5.4 68.8 659 1.81 0.00543 MgCI2 16-35
48


2013_02_002_A_50 5.4 68.8 659 1.81 0.00543 MgCI2 16-35
Sample ID Flowrate (ml/min) Flow Velocity (m/day) Average Pore Velocity (m/day) Ionic Cone (mM) Ionic Strength (M) Salt Type Nation Size (mesh)
2013_02_002_A_64 5.3 67.5 647 1.81 0.00543 MgCI2 16-35
2013_02_002_A_24 5.4 68.8 659 1.81 0.00543 MgCI2 16-35
2013_02_002_A_30 5.4 68.8 659 1.81 0.00543 MgCI2 16-35
2013_02_002_A_53 5.4 68.8 659 1.81 0.00543 MgCI2 16-35
2013_02_002_A_66 5.3 67.5 647 1.81 0.00543 MgCI2 16-35
2013_03_001_A_26 5.72 72.8 671 1.95 0.00585 MgCI2 16-35
2013_03_001_A_3 2 5.72 72.8 671 1.95 0.00585 MgCI2 16-35
2013_03_001_A_47 5.72 72.8 671 1.95 0.00585 MgCI2 16-35
2013_03_001_A_6 2 5.67 72.2 665 1.95 0.00585 MgCI2 16-35
2013_03_001_A_28 5.72 72.8 671 1.95 0.00585 MgCI2 16-35
2013_03_001_A_34 5.72 72.8 671 1.95 0.00585 MgCI2 16-35
2013_03_001_A_50 5.72 72.8 671 1.95 0.00585 MgCI2 16-35
2013_03_001_A_64 5.67 72.2 665 1.95 0.00585 MgCI2 16-35
2013_03_001_A_36 5.72 72.8 671 1.95 0.00585 MgCI2 16-35
2013_03_001_A_53 5.72 72.8 671 1.95 0.00585 MgCI2 16-35
2013_03_001_A_66 5.67 72.2 665 1.95 0.00585 MgCI2 16-35
2013_03_008_A_20 11.62 148.0 569 16.03 0.04809 MgCI2 16-35
2013_03_008_A_26 11.62 148.0 569 16.03 0.04809 MgCI2 16-35
2013_03_008_A_47 11.62 148.0 569 16.03 0.04809 MgCI2 16-35
2013_03_008_A_6 2 11.76 149.7 576 16.03 0.04809 MgCI2 16-35
2013_03_008_A_22 11.62 148.0 569 16.03 0.04809 MgCI2 16-35
2013_03_008_A_28 11.62 148.0 569 16.03 0.04809 MgCI2 16-35
2013_03_008_A_50 11.62 148.0 569 16.03 0.04809 MgCI2 16-35
2013_03_008_A_64 11.76 149.7 576 16.03 0.04809 MgCI2 16-35
2013_03_008_A_24 11.62 148.0 569 16.03 0.04809 MgCI2 16-35
2013_03_008_A_30 11.62 148.0 569 16.03 0.04809 MgCI2 16-35
2013_03_008_A_53 11.62 148.0 569 16.03 0.04809 MgCI2 16-35
2013_03_008_A_66 11.76 149.7 576 16.03 0.04809 MgCI2 16-35
2013_04_001_A_20 5.97 76.0 292 16.01 0.04803 MgCI2 16-35
2013_04_001_A_26 5.97 76.0 292 16.01 0.04803 MgCI2 16-35
2013_04_001_A_2 2 5.97 76.0 292 16.01 0.04803 MgCI2 16-35
2013_04_001_A_24 5.97 76.0 292 16.01 0.04803 MgCI2 16-35
2013_04_001_A_30 5.97 76.0 292 16.01 0.04803 MgCI2 16-35
2013_04_018_A_20 2.82 35.9 138 16.23 0.04869 MgCI2 16-35
2013_04_018_A_26 2.82 35.9 138 16.23 0.04869 MgCI2 16-35
2013_04_018_A_32 2.82 35.9 138 16.23 0.04869 MgCI2 16-35
2013_04_018_A_22 2.82 35.9 138 16.23 0.04869 MgCI2 16-35
49


2013_04_018_A_28 2.82 35.9 138 16.23 0.04869 MgCI2 16-35
2013_04_018_A_50 2.82 35.9 138 16.23 0.04869 MgCI2 16-35
2013_04_018_A_64 2.82 35.9 138 16.23 0.04869 MgCI2 16-35
2013_04_018_A_24 2.82 35.9 138 16.23 0.04869 MgCI2 16-35
Sample ID Flowrate (ml/min) Flow Velocity (m/day) Average Pore Velocity (m/day) Ionic Cone (mM) Ionic Strength (M) Salt Type Nation Size (mesh)
2013_04_018_A_30 2.82 35.9 138 16.23 0.04869 MgCI2 16-35
2013_04_018_A_53 2.82 35.9 138 16.23 0.04869 MgCI2 16-35
2013_04_018_A_66 2.82 35.9 138 16.23 0.04869 MgCI2 16-35
2013_06_002_A_20 12 152.8 588 8.027 0.024081 MgCI2 16-35
2013_06_002_A_26 12 152.8 588 8.027 0.024081 MgCI2 16-35
2013_06_002_A_32 12 152.8 588 8.027 0.024081 MgCI2 16-35
2013_06_002_A_22 12 152.8 588 8.027 0.024081 MgCI2 16-35
2013_06_002_A_28 12 152.8 588 8.027 0.024081 MgCI2 16-35
2013_06_002_A_50 12 152.8 588 8.027 0.024081 MgCI2 16-35
2013_06_002_A_64 12 152.8 588 8.027 0.024081 MgCI2 16-35
2013_06_002_A_24 12 152.8 588 8.027 0.024081 MgCI2 16-35
2013_06_002_A_30 12 152.8 588 8.027 0.024081 MgCI2 16-35
2013_06_002_A_53 12 152.8 588 8.027 0.024081 MgCI2 16-35
2013_06_002_A_66 12 152.8 588 8.027 0.024081 MgCI2 16-35
2013_08_001_A_20 11.86 151.0 690 3.953 0.011859 MgCI2 16-35
2013_08_001_A_26 11.86 151.0 690 3.953 0.011859 MgCI2 16-35
2013_08_001_A_47 11.86 151.0 690 3.953 0.011859 MgCI2 16-35
2013_08_001_A_6 2 11.86 151.0 690 3.953 0.011859 MgCI2 16-35
2013_08_001_A_2 2 11.86 151.0 690 3.953 0.011859 MgCI2 16-35
2013_08_001_A_28 11.86 151.0 690 3.953 0.011859 MgCI2 16-35
2013_08_001_A_50 11.86 151.0 690 3.953 0.011859 MgCI2 16-35
2013_08_001_A_64 11.86 151.0 690 3.953 0.011859 MgCI2 16-35
2013_08_001_A_24 11.86 151.0 690 3.953 0.011859 MgCI2 16-35
2013_08_001_A_30 11.86 151.0 690 3.953 0.011859 MgCI2 16-35
2013_08_001_A_53 11.86 151.0 690 3.953 0.011859 MgCI2 16-35
2013_08_001_A_66 11.86 151.0 690 3.953 0.011859 MgCI2 16-35
2013_08_002_A_20 12.53 159.5 1439 2.016 0.006048 MgCI2 16-35
2013_08_002_A_26 12.53 159.5 1439 2.016 0.006048 MgCI2 16-35
2013_08_002_A_47 12.53 159.5 1439 2.016 0.006048 MgCI2 16-35
2013_08_002_A_62 12.53 159.5 1439 2.016 0.006048 MgCI2 16-35
2013_08_002_A_22 12.53 159.5 1439 2.016 0.006048 MgCI2 16-35
2013_08_002_A_28 12.53 159.5 1439 2.016 0.006048 MgCI2 16-35
2013_08_002_A_50 12.53 159.5 1439 2.016 0.006048 MgCI2 16-35
2013_08_002_A_64 12.53 159.5 1439 2.016 0.006048 MgCI2 16-35
50


2013_08_002_A_24 12.53 159.5 1439 2.016 0.006048 MgCI2 16-35
2013_08_002_A_30 12.53 159.5 1439 2.016 0.006048 MgCI2 16-35
2013_08_002_A_53 12.53 159.5 1439 2.016 0.006048 MgCI2 16-35
2013_08_002_A_66 12.53 159.5 1439 2.016 0.006048 MgCI2 16-35
2013_08_003_A_20 11.63 148.1 1.011 0.003033 MgCI2 16-35
2013_08_003_A_26 11.63 148.1 1.011 0.003033 MgCI2 16-35
2013_08_003_A_47 11.63 148.1 1.011 0.003033 MgCI2 16-35
Sample ID Flowrate (ml/min) Flow Velocity (m/day) Average Pore Velocity (m/day) Ionic Cone (mM) Ionic Strength (M) Salt Type Nation Size (mesh)
2013_08_003_A_6 2 11.63 148.1 1.011 0.003033 MgCI2 16-35
2013_08_003_A_22 11.63 148.1 1.011 0.003033 MgCI2 16-35
2013_08_003_A_28 11.63 148.1 1.011 0.003033 MgCI2 16-35
2013_08_003_A_50 11.63 148.1 1.011 0.003033 MgCI2 16-35
2013_08_003_A_64 11.63 148.1 1.011 0.003033 MgCI2 16-35
2013_08_003_A_24 11.63 148.1 1.011 0.003033 MgCI2 16-35
2013_08_003_A_30 11.63 148.1 1.011 0.003033 MgCI2 16-35
2013_08_003_A_53 11.63 148.1 1.011 0.003033 MgCI2 16-35
2013_08_003_A_66 11.63 148.1 1.011 0.003033 MgCI2 16-35
2013_09_001_A_20 11.78 150.0 3000 0.983 0.002949 MgCI2 16-35
2013_09_001_A_26 11.78 150.0 3000 0.983 0.002949 MgCI2 16-35
2013_09_001_A_47 11.78 150.0 3000 0.983 0.002949 MgCI2 16-35
2013_09_001_A_6 2 11.78 150.0 3000 0.983 0.002949 MgCI2 16-35
2013_09_001_A_2 2 11.78 150.0 3000 0.983 0.002949 MgCI2 16-35
2013_09_001_A_28 11.78 150.0 3000 0.983 0.002949 MgCI2 16-35
2013_09_001_A_50 11.78 150.0 3000 0.983 0.002949 MgCI2 16-35
2013_09_001_A_64 11.78 150.0 3000 0.983 0.002949 MgCI2 16-35
2013_09_001_A_24 11.78 150.0 3000 0.983 0.002949 MgCI2 16-35
2013_09_001_A_30 11.78 150.0 3000 0.983 0.002949 MgCI2 16-35
2013_09_001_A_53 11.78 150.0 3000 0.983 0.002949 MgCI2 16-35
2013_09_001_A_66 11.78 150.0 3000 0.983 0.002949 MgCI2 16-35
2013_09_002_A_20 1.512 19.3 74 16.254 0.048762 MgCI2 16-35
2013_09_002_A_26 1.512 19.3 74 16.254 0.048762 MgCI2 16-35
2013_09_002_A_47 1.512 19.3 74 16.254 0.048762 MgCI2 16-35
2013_09_002_A_62 1.528 19.5 75 16.254 0.048762 MgCI2 16-35
2013_09_002_A_22 1.512 19.3 74 16.254 0.048762 MgCI2 16-35
2013_09_002_A_28 1.512 19.3 74 16.254 0.048762 MgCI2 16-35
2013_09_002_A_50 1.512 19.3 74 16.254 0.048762 MgCI2 16-35
2013_09_002_A_64 1.528 19.5 75 16.254 0.048762 MgCI2 16-35
2013_09_002_A_24 1.512 19.3 74 16.254 0.048762 MgCI2 16-35
2013_09_002_A_30 1.512 19.3 74 16.254 0.048762 MgCI2 16-35
2013_09_002_A_53 1.512 19.3 74 16.254 0.048762 MgCI2 16-35
51


1.528
19.5
75
16.254 | 0.048762 | MgCI2
16-35
2013 09 002 A 66
Sample ID Nafion Amount (g) Porosity Inlet Colloid Cone (ppm) Colloid Size (nm) Pore Fluid Colloid Cone, (ppm) Specific Deposit (ppm) Flow Cell Position
2012_03_001_A_6 5.5 125 99 255
2012_03_001_A_7 5.5 125 99 255
2012_03_001_A_11 5.5 125 99 255
2012_04_002_A_15 7 12 99 255
2012_05_001_A_12 7 125 99 255
2012_05_001_A_15 7 125 99 255
2012_05_001_A_21 7 125 99 255
2012_05_001_A_27 7 125 99 255
2012_06_001_A_12 7 125 99 255
2012_06_001_A_18 7 125 99 255
2012_06_001_A_24 7 125 99 255
2012_06_001_A_30 7 125 99 255
2012_06_002_A_24 7 125 99 255
2012_06_002_A_27 7 125 99 255
2012_06_002_A_30 7 125 99 255
2012_06_003_A_15 7 125 99 255
2012_06_003_A_21 7 125 99 255
2013_01_002_A_42 6.5 0.11 125 106 451 50 790
2013_01_002_A_48 6.5 0.11 125 106 1629 179 790
2013_01_002_A_54 6.5 0.11 125 106 1649 181 790
2013_01_002_A_88 6.5 0.11 125 106 1010 111 790
2013_01_002_A_41 6.5 0.11 125 106 117 13 580
2013_01_002_A_47 6.5 0.11 125 106 611 67 580
2013_01_002_A_53 6.5 0.11 125 106 1035 114 580
2013_01_002_A_82 6.5 0.11 125 106 543 60 580
2013_01_002_A_40 6.5 0.11 125 106 52 6 255
2013_01_002_A_46 6.5 0.11 125 106 301 33 255
2013_01_002_A_52 6.5 0.11 125 106 523 58 255
2013_01_002_A_75 6.5 0.11 125 106 403 44 255
2013_02_001_A_47 6.5 0.11 125 106 95 11 790
2013_02_001_A_56 6.5 0.11 125 106 108 12 790
2013_02_001_A_62 6.5 0.11 125 106 181 20 790
2013_02_002_A_20 6.5 0.10 136 106 60 6 790
2013_02_002_A_26 6.5 0.10 136 106 403 42 790
2013_02_002_A_47 6.5 0.10 136 106 1447 151 790
52


2013_02_002_A_62 6.5 0.10 136 106 1438 150 790
2013_02_002_A_22 6.5 0.10 136 106 152 16 580
2013_02_002_A_28 6.5 0.10 136 106 630 66 580
2013_02_002_A_50 6.5 0.10 136 106 1629 170 580
Sample ID Nafion Amount (g) Porosity Inlet Colloid Cone (ppm) Colloid Size (nm) Pore Fluid Colloid Cone, (ppm) Specific Deposit (ppm) Flow Cell Position
2013_02_002_A_64 6.5 0.1043 136.4 106.0 1669.4 174.1 580
2013_02_002_A_24 6.5 0.1043 136.4 106.0 130.2 13.6 255
2013_02_002_A_30 6.5 0.1 136.4 106.0 445.022706 46.415868 255
2013_02_002_A_53 6.5 0.1 136.4 106.0 1157.50777 120.72806 255
2013_02_002_A_66 6.5 0.1 136.4 106.0 1193.99509 124.53369 255
2013_03_001_A_26 6.5 0.1 127.9 106.0 117.895408 12.791652 790
2013_03_001_A_3 2 6.5 0.1 127.9 106.0 340.773621 36.973938 790
2013_03_001_A_47 6.5 0.1 127.9 106.0 817.642166 88.714175 790
2013_03_001_A_6 2 6.5 0.1 127.9 106.0 843.416141 91.510651 790
2013_03_001_A_28 6.5 0.1 127.9 106.0 107.414029 11.654422 580
2013_03_001_A_34 6.5 0.1 127.9 106.0 320.264434 34.748691 580
2013_03_001_A_50 6.5 0.1 127.9 106.0 618.380274 67.09426 580
2013_03_001_A_64 6.5 0.1 127.9 106.0 614.553791 66.679086 580
2013_03_001_A_36 6.5 0.1 127.9 106.0 130.205251 14.12727 255
2013_03_001_A_53 6.5 0.1 127.9 106.0 224.829012 24.393948 255
2013_03_001_A_66 6.5 0.1085 127.9 106 227.637498 24.698669 255
2013_03_008_A_20 6.5 0.26 124.3 106 115.421252 30.009525 790
2013_03_008_A_26 6.5 0.26 124.3 106 493.106914 128.2078 790
2013_03_008_A_47 6.5 0.26 124.3 106 1104.15305 287.07979 790
2013_03_008_A_6 2 6.5 0.26 124.3 106 863.504878 224.51127 790
2013_03_008_A_22 6.5 0.26 124.3 106 99.478794 25.864486 580
2013_03_008_A_28 6.5 0.26 124.3 106 360.065798 93.617108 580
2013_03_008_A_50 6.5 0.26 124.3 106 748.501064 194.61028 580
2013_03_008_A_64 6.5 0.26 124.3 106 616.274211 160.23129 580
2013_03_008_A_24 6.5 0.26 124.3 106 159.88613 41.570394 255
2013_03_008_A_30 6.5 0.26 124.3 106 455.177266 118.34609 255
2013_03_008_A_53 6.5 0.26 124.3 106 706.908938 183.79632 255
2013_03_008_A_66 6.5 0.26 124.3 106 516.183659 134.20775 255
2013_04_001_A_20 6.5 0.26 124.5 106 91.3034289 23.738892 790
2013_04_001_A_26 6.5 0.26 124.5 106 834.386801 216.94057 790
2013_04_001_A_2 2 6.5 0.26 124.5 106 233.174931 60.625482 580
2013_04_001_A_24 6.5 0.26 124.5 106 246.894153 64.19248 255
2013_04_001_A_30 6.5 0.26 124.5 106 1110.48366 288.72575 255
2013_04_018_A_20 6.5 0.26 61.4 106 56.1618 14.602068 790
53


2013_04_018_A_26 6.5 0.26 61.4 106 605.794477 157.50656 790
2013_04_018_A_32 6.5 0.26 61.4 106 1142.68532 297.09818 790
2013_04_018_A_22 6.5 0.26 61.4 106 130.144726 33.837629 580
2013_04_018_A_28 6.5 0.26 61.4 106 609.26777 158.40962 580
2013_04_018_A_50 6.5 0.26 61.4 106 1245.00206 323.70054 580
2013_04_018_A_64 6.5 0.26 61.4 106 1129.69409 293.72046 580
2013_04_018_A_24 6.5 0.26 61.4 106 72.2251405 18.778537 255
Sample ID Nafion Amount (g) Porosity Inlet Colloid Cone (ppm) Colloid Size (nm) Pore Fluid Colloid Cone, (ppm) Specific Deposit (ppm) Flow Cell Position
2013_04_018_A_30 6.5 0.26 61.4 106 291.416916 75.768398 255
2013_04_018_A_53 6.5 0.26 61.4 106 671.455783 174.5785 255
2013_04_018_A_66 6.5 0.26 61.4 106 447.436983 116.33362 255
2013_06_002_A_20 6.5 0.26 124.19 106 77.3540639 20.112057 790
2013_06_002_A_26 6.5 0.26 124.19 106 432.34905 112.41075 790
2013_06_002_A_32 6.5 0.26 124.19 106 919.552733 239.08371 790
2013_06_002_A_22 6.5 0.26 124.19 106 126.477158 32.884061 580
2013_06_002_A_28 6.5 0.26 124.19 106 424.99696 110.49921 580
2013_06_002_A_50 6.5 0.26 124.19 106 1196.16146 311.00198 580
2013_06_002_A_64 6.5 0.26 124.19 106 914.310578 237.72075 580
2013_06_002_A_24 6.5 0.26 124.19 106 198.683041 51.657591 255
2013_06_002_A_30 6.5 0.26 124.19 106 493.106914 128.2078 255
2013_06_002_A_53 6.5 0.26 124.19 106 863.504878 224.51127 255
2013_06_002_A_66 6.5 0.26 124.19 106 723.261008 188.04786 255
2013_08_001_A_20 6.5 0.2187075 126.07 106 124.326416 27.19112 790
2013_08_001_A_26 6.5 0.2187075 126.07 106 1073.03726 234.6813 790
2013_08_001_A_47 6.5 0.2187075 126.07 106 2059.04019 450.32753 790
2013_08_001_A_6 2 6.5 0.2187075 126.07 106 1889.82418 413.31872 790
2013_08_001_A_2 2 6.5 0.2187075 126.07 106 214.012151 46.806063 580
2013_08_001_A_28 6.5 0.2187075 126.07 106 853.687663 186.70789 580
2013_08_001_A_50 6.5 0.2187075 126.07 106 1573.86966 344.2171 580
2013_08_001_A_64 6.5 0.2187075 126.07 106 1162.45281 254.23715 580
2013_08_001_A_24 6.5 0.2187075 126.07 106 251.165214 54.931716 255
2013_08_001_A_30 6.5 0.2187075 126.07 106 616.274211 134.78379 255
2013_08_001_A_53 6.5 0.2187075 126.07 106 1110.48366 242.8711 255
2013_08_001_A_66 6.5 0.2187075 126.07 106 546.554156 119.53549 255
2013_08_002_A_20 6.5 0.11088 61.821 106 29.8 3.304224 790
2013_08_002_A_26 6.5 0.11088 61.821 106 105 11.6424 790
2013_08_002_A_47 6.5 0.11088 61.821 106 570 63.2016 790
2013_08_002_A_62 6.5 0.11088 61.821 106 455 50.4504 790
2013_08_002_A_22 6.5 0.11088 61.821 106 28.7 3.182256 580
54


2013_08_002_A_28 6.5 0.11088 61.821 106 111 12.30768 580
2013_08_002_A_50 6.5 0.11088 61.821 106 498 55.21824 580
2013_08_002_A_64 6.5 0.11088 61.821 106 337 37.36656 580
2013_08_002_A_24 6.5 0.11088 61.821 106 30.4 3.370752 255
2013_08_002_A_30 6.5 0.11088 61.821 106 97.8 10.844064 255
2013_08_002_A_53 6.5 0.11088 61.821 106 318 35.25984 255
2013_08_002_A_66 6.5 0.11088 61.821 106 130 14.4144 255
2013_08_003_A_20 6 61.604 106 8.3 790
2013_08_003_A_26 6 61.604 106 12.5 790
2013_08_003_A_47 6 61.604 106 30.5 790
Nafion Inlet Colloid Cone (ppm) Colloid Size (nm) Pore Fluid Specific Flow
Sample ID Amount (g) Porosity Colloid Cone, (ppm) Deposit (ppm) Cell Position
2013_08_003_A_6 2 6 61.604 106 42.4 790
2013_08_003_A_22 6 61.604 106 10.8 580
2013_08_003_A_28 6 61.604 106 11.2 580
2013_08_003_A_50 6 61.604 106 18.5 580
2013_08_003_A_64 6 61.604 106 6.1 580
2013_08_003_A_24 6 61.604 106 14.7 255
2013_08_003_A_30 6 61.604 106 11.7 255
2013_08_003_A_53 6 61.604 106 0 255
2013_08_003_A_66 6 61.604 106 0 255
2013_09_001_A_20 6.5 0.05 126.715 106 26.3 1.315 790
2013_09_001_A_26 6.5 0.05 126.715 106 28.5 1.425 790
2013_09_001_A_47 6.5 0.05 126.715 106 13.2 0.66 790
2013_09_001_A_6 2 6.5 0.05 126.715 106 21.9 1.095 790
2013_09_001_A_2 2 6.5 0.05 126.715 106 16.6 0.83 580
2013_09_001_A_28 6.5 0.05 126.715 106 15.1 0.755 580
2013_09_001_A_50 6.5 0.05 126.715 106 19.7 0.985 580
2013_09_001_A_64 6.5 0.05 126.715 106 2.7 0.135 580
2013_09_001_A_24 6.5 0.05 126.715 106 0 0 255
2013_09_001_A_30 6.5 0.05 126.715 106 5.2 0.26 255
2013_09_001_A_53 6.5 0.05 126.715 106 11.7 0.585 255
2013_09_001_A_66 6.5 0.05 126.715 106 0 0 255
2013_09_002_A_20 6.5 0.26 30.66 106 62 16.12 790
2013_09_002_A_26 6.5 0.26 30.66 106 324 84.24 790
2013_09_002_A_47 6.5 0.26 30.66 106 858 223.08 790
2013_09_002_A_62 6.5 0.26 30.66 106 680 176.8 790
2013_09_002_A_22 6.5 0.26 30.66 106 60 15.6 580
2013_09_002_A_28 6.5 0.26 30.66 106 196 50.96 580
2013_09_002_A_50 6.5 0.26 30.66 106 446 115.96 580
55


2013_09_002_A_64 6.5 0.26 30.66 106 387 100.62 580
2013_09_002_A_24 6.5 0.26 30.66 106 46.3 12.038 255
2013_09_002_A_30 6.5 0.26 30.66 106 122 31.72 255
2013_09_002_A_53 6.5 0.26 30.66 106 278 72.28 255
2013_09_002_A_66 6.5 0.26 30.66 106 244 63.44 255
Sample ID Volume Eluted (ml) Pore Volumes Eluted Clean Bed Head Loss (cm H20) Clean Bed K (cm/min) dH/dHo Hyd Cond (cm/min)
2012_03_001_A_6 33.166667
2012_03_001_A_7 59.7
2012_03_001_A_11 159.2
2012_04_002_A_15 193.2 1.02
2012_05_001_A_12 35
2012_05_001_A_15 87.5
2012_05_001_A_21 196
2012_05_001_A_27 297.5
2012_06_001_A_12 25.875
2012_06_001_A_18 94.5
2012_06_001_A_24 182
2012_06_001_A_30 268.25 1.73
2012_06_002_A_24 111.63
2012_06_002_A_27 186.76
2012_06_002_A_30 272.15
2012_06_003_A_15 23.4
2012_06_003_A_21 86.775
2013_01_002_A_42 181 131.636364 6.5 1.75970048 1.07 1.649
2013_01_002_A_48 341 248 6.5 1.75970048 1.46 1.21
2013_01_002_A_54 377 274.181818 6.5 1.75970048 1.61 1.09
2013_01_002_A_88 1320 960 6.5 1.75970048 0.908 1.94
2013_01_002_A_41 155 112.727273 10 2.28761062 1.027 2.227
2013_01_002_A_47 315 229.090909 10 2.28761062 1.359 1.683
2013_01_002_A_53 377 274.181818 10 2.28761062 1.53 1.5
2013_01_002_A_82 1160 843.636364 10 2.28761062 1.16 1.967
2013_01_002_A_40 124 90.1818182 45.4 0.75581849 0.999 0.757
2013_01_002_A_46 290 210.909091 45.4 0.75581849 1.072 0.7049
2013_01_002_A_52 377 274.181818 45.4 0.75581849 1.15 0.66
2013_01_002_A_75 984 715.636364 45.4 0.75581849 1.054 0.717
2013_02_001_A_47 356 258.909091
2013_02_001_A_56 437 317.818182
56


2013_02_001_A_62 617 448.727273
2013_02_002_A_20 22 16.8744008 3.8 1.57196088 1.04 1.516
2013_02_002_A_26 113 86.6730585 3.8 1.57196088 1.28 1.22
2013_02_002_A_47 332 254.650048 3.8 1.57196088 1.88 0.835
2013_02_002_A_62 578 443.336529 3.8 1.54285049 1.99 0.775
2013_02_002_A_22 49 37.5838926 11 1.08608206 1.101 0.98
2013_02_002_A_28 138 105.848514 11 1.08608206 1.32 0.825
2013_02_002_A_50 332 254.650048 11 1.08608206 1.95 0.557
Sample ID Volume Eluted (ml) Pore Volumes Eluted Clean Bed Head Loss (cm H20) Clean Bed K (cm/min) dH/dHo Hyd Cond (cm/min)
2013_02_002_A_64 605 464.046021 11 1.06596943 1.964 0.543
2013_02_002_A_24 73 55.9923298 15 1.19469027 1.13 1.055
2013_02_002_A_30 165 126.558006 15 1.19469027 1.245 0.959
2013_02_002_A_53 332 254.650048 15 1.19469027 1.52 0.787
2013_02_002_A_66 629 482.454458 15 1.17256637 1.5 0.782
2013_03_001_A_26 129 95.1152074
2013_03_001_A_32 235 173.271889
2013_03_001_A_47 343 252.903226
2013_03_001_A_62 593 437.235023
2013_03_001_A_28 157 115.760369
2013_03_001_A_34 260 191.705069
2013_03_001_A_50 343 252.903226
2013_03_001_A_64 621 457.880184
2013_03_001_A_36 292 215.299539
2013_03_001_A_53 343 252.903226
2013_03_001_A_66 649 478.525346
2013_03_008_A_20 58 17.8461538 1.1 11.6854385 1.015 11.515
2013_03_008_A_26 267 82.1538462 1.1 11.6854385 1.105 10.57
2013_03_008_A_47 485 149.230769 1.1 11.6854385 1.17 9.99
2013_03_008_A_62 809 248.923077 1.1 11.8262269 1.22 9.7
2013_03_008_A_22 110 33.8461538 7.4 3.47404927 1.03 2.6
2013_03_008_A_28 320 98.4615385 7.4 3.47404927 1.11 2.4
2013_03_008_A_50 485 149.230769 7.4 3.47404927 1.18 2.27
2013_03_008_A_64 861 264.923077 7.4 3.51590529 1.248 2.189
2013_03_008_A_24 163 50.1538462 9.6 4.01686947 1.05 3.81
2013_03_008_A_30 372 114.461538 9.6 4.01686947 1.135 3.54
2013_03_008_A_53 485 149.230769 9.6 4.01686947 1.26 3.42
2013_03_008_A_66 914 281.230769 9.6 4.06526549 1.21 3.35
2013_04_001_A_20 24 7.38461538 1.99 3.31858407 0.996 3.32
2013_04_001_A_26 194 59.6923077 1.99 3.31858407 1.22 2.71
57


2013_04_001_A_22 54 16.6153846 5.16 2.55968306 1.06 2.42
2013_04_001_A_24 81 24.9230769 6.45 3.07161967 1.1 2.79
2013_04_001_A_30 254 78.1538462 6.45 3.07161967 1.36 2.26
2013_04_018_A_20 17 5.23076923 1.14 2.73637634 1.1 2.5
2013_04_018_A_26 148 45.5384615 1.14 2.73637634 1.418 1.93
2013_04_018_A_32 250 76.9230769 1.14 2.73637634 1.77 1.54
2013_04_018_A_22 30 9.23076923 2.56 2.43708518 1.14 2.12
2013_04_018_A_28 161 49.5384615 2.56 2.43708518 1.5 1.62
2013_04_018_A_50 307 94.4615385 2.56 2.43708518 2.02 1.21
2013_04_018_A_64 512 157.538462 2.56 2.43708518 1.83 1.33
2013_04_018_A_24 42 12.9230769 3.3 2.83588093 1.144 2.48
Sample ID Volume Eluted (ml) Pore Volumes Eluted Clean Bed Head Loss (cm H20) Clean Bed K (cm/min) dH/dHo Hyd Cond (cm/min)
2013_04_018_A_30 175 53.8461538 3.3 2.83588093 1.367 2.07
2013_04_018_A_53 307 94.4615385 3.3 2.83588093 1.71 1.66
2013_04_018_A_66 527 162.153846 3.3 2.83588093 1.517 1.87
2013_06_002_A_20 54 16.6153846 2.8 4.74083439 1 4.73
2013_06_002_A_26 216 66.4615385 2.8 4.74083439 1.068 4.437
2013_06_002_A_32 372 114.461538 2.8 4.74083439 1.27 3.733
2013_06_002_A_22 114 35.0769231 14.1 1.88288458 1.002 1.88
2013_06_002_A_28 264 81.2307692 14.1 1.88288458 1.095 1.719
2013_06_002_A_50 492 151.384615 14.1 1.88288458 1.245 1.514
2013_06_002_A_64 780 240 14.1 1.88288458 1.233 1.527
2013_06_002_A_24 162 49.8461538
2013_06_002_A_30 318 97.8461538
2013_06_002_A_53 492 151.384615
2013_06_002_A_66 834 256.615385
2013_08_001_A_20 47.4 17.3382257 6.4 2.04991704 1.2 1.7
2013_08_001_A_26 214 78.2780655 6.4 2.04991704 1.12 1.83
2013_08_001_A_47 513 187.647886 6.4 2.04991704 1.49 1.38
2013_08_001_A_62 810 296.286136 6.4 2.04991704 1.54 1.34
2013_08_001_A_22 113 41.3337448 18.9 1.3883036 1.03 1.34
2013_08_001_A_28 267 97.6646891 18.9 1.3883036 1.19 1.16
2013_08_001_A_50 513 187.647886 18.9 1.3883036 1.43 0.97
2013_08_001_A_64 863 315.672759 18.9 1.3883036 1.3 1.07
2013_08_001_A_24 160 58.5256564 28.6 1.37616808 1.07 1.28
2013_08_001_A_30 320 117.051313 28.6 1.37616808 1.21 1.14
2013_08_001_A_53 513 187.647886 28.6 1.37616808 1.33 1.04
2013_08_001_A_66 916 335.059383 28.6 1.37616808 1.202 1.145
2013_08_002_A_20 43.9 31.6738817 5.5 2.52011263 1.012 2.49
58


2013_08_002_A_26 213 153.679654 5.5 2.52011263 1.086 2.321
2013_08_002_A_47 520 375.180375 5.5 2.52011263 1.21 2.08
2013_08_002_A_62 807 582.251082 5.5 2.52011263 0.97 2.7
2013_08_002_A_22 119 85.8585859 26.2 1.05806255 1.04 1.015
2013_08_002_A_28 269 194.083694 26.2 1.05806255 1.135 0.932
2013_08_002_A_50 520 375.180375 26.2 1.05806255 1.276 0.829
2013_08_002_A_64 859 619.76912 26.2 1.05806255 1.09 1.008
2013_08_002_A_24 157 113.275613 43.2 0.96254302 1.03 0.932
2013_08_002_A_30 326 235.209235 43.2 0.96254302 1.093 0.881
2013_08_002_A_53 520 375.180375 43.2 0.96254302 1.168 0.824
2013_08_002_A_66 918 662.337662 43.2 0.96254302 1.1 0.913
2013_08_003_A_20 46.5
2013_08_003_A_26 209
2013_08_003_A_47 521
Sample ID Volume Eluted (ml) Pore Volumes Eluted Clean Bed Head Loss (cm H20) Clean Bed K (cm/min) dH/dHo Hyd Cond (cm/min)
2013_08_003_A_62 825
2013_08_003_A_22 98.9
2013_08_003_A_28 273
2013_08_003_A_50 521
2013_08_003_A_64 877
2013_08_003_A_24 157
2013_08_003_A_30 331
2013_08_003_A_53 521
2013_08_003_A_66 930
2013_09_001_A_20 47.1 75.36 7 1.86156764 1.01 1.844
2013_09_001_A_26 212 339.2 7 1.86156764 0.99 1.88
2013_09_001_A_47 527 843.2 7 1.86156764 0.986 1.889
2013_09_001_A_62 786 1257.6 7 1.86156764 0.929 2.007
2013_09_001_A_22 100 160 30.5 0.85449006 0.998 0.856
2013_09_001_A_28 265 424 30.5 0.85449006 0.991 0.863
2013_09_001_A_50 527 843.2 30.5 0.85449006 0.985 0.868
2013_09_001_A_64 834 1334.4 30.5 0.85449006 0.955 0.896
2013_09_001_A_24 153 244.8 44.5 0.87849259 1 0.878
2013_09_001_A_30 324 518.4 44.5 0.87849259 0.998 0.88
2013_09_001_A_53 527 843.2 44.5 0.87849259 0.988 0.889
2013_09_001_A_66 940 1504 44.5 0.87849259 0.97 0.906
2013_09_002_A_20 28 8.61538462 0.9 1.85840708 1.13 1.645
2013_09_002_A_26 116 35.6923077 0.9 1.85840708 1.38 1.34
2013_09_002_A_47 248 76.3076923 0.9 1.85840708 2.13 0.873
59


2013_09_002_A_62 389 119.692308 0.9 1.87807276 1.85 1.01
2013_09_002_A_22 36.3 11.1692308 1.7 1.96772514 1.12 1.75
2013_09_002_A_28 124 38.1538462 1.7 1.96772514 1.44 1.35
2013_09_002_A_50 248 76.3076923 1.7 1.96772514 1.96 1.01
2013_09_002_A_64 395 121.538462 1.7 1.98854763 1.82 1.09
2013_09_002_A_24 43.1 13.2615385 1.8 2.78761062 1.03 2.7
2013_09_002_A_30 131 40.3076923 1.8 2.78761062 1.25 2.23
2013_09_002_A_53 248 76.3076923 1.8 2.78761062 1.43 1.96
2013_09_002_A_66 402 123.692308 1.8 2.81710914 1.39 2.02
Sample ID K/Ko Morph. Parameter (1/ppm) Fractal Dimension 95% Confidence Interval (+/-) Df- Cl Df+ Cl Fractal Fit Range (QA-1)
2012_03_001_A_6 2.957 0.086 2.87 3.04 0.002-0.01
2012_03_001_A_7 3.01 0.076 2.93 3.09 0.002-0.01
2012_03_001_A_11 3.076 0.061 3.02 3.14 0.002-0.01
2012_04_002_A_15 2.906 0.159 2.75 3.07 0.002-0.006
2012_05_001_A_12 2.466 0.065 2.4 2.53 0.005-0.02
2012_05_001_A_15 2.187 0.053 2.13 2.24 0.005-0.02
2012_05_001_A_21 1.815 0.041 1.77 1.86 0.005-0.02
2012_05_001_A_27 1.984 0.057 1.93 2.04 0.005-0.02
2012_06_001_A_12 2.96 0.131 2.83 3.09 0.005-0.02
2012_06_001_A_18 2.297 0.051 2.25 2.35 0.005-0.02
2012_06_001_A_24 1.964 0.035 1.93 2 0.005-0.02
2012_06_001_A_30 2.118 0.046 2.07 2.16 0.005-0.02
2012_06_002_A_24 2.081 0.14 1.94 2.22 0.005-0.02
2012_06_002_A_27 2.524 0.123 2.4 2.65 0.005-0.02
2012_06_002_A_30 2.928 0.114 2.81 3.04 0.005-0.02
2012_06_003_A_15 2.36 0.031 2.33 2.39 0.002-0.02
2012_06_003_A_21 1.825 0.048 1.78 1.87 0.002-0.02
2013_01_002_A_42 0.937 7.33964E-05 1.853 0.04 1.81 1.89 0.002-0.02
2013_01_002_A_48 0.685 0.000127875 1.009 0.082 0.93 1.09 0.002-0.02
2013_01_002_A_54 0.621 0.000163131 0.91 0.074 0.84 0.98 0.002-0.02
2013_01_002_A_88 1.102 -4.69449E- 05 1.375 0.057 1.32 1.43 0.002-0.02
2013_01_002_A_41 0.973 0.000117608 2.044 0.034 2.01 2.08 0.002-0.02
2013_01_002_A_47 0.736 0.000271192 1.62 0.05 1.57 1.67 0.002-0.02
2013_01_002_A_53 0.655 0.000227605 1.261 0.061 1.2 1.32 0.002-0.02
2013_01_002_A_82 0.86 0.000144301 1.588 0.047 1.54 1.64 0.002-0.02
2013_01_002_A_40 1.001 -9.55625E- 06 2.25 0.036 2.21 2.29 0.002-0.02
60


2013_01_002_A_46 0.932 0.000119069 2.015 0.061 1.95 2.08 0.002-0.02
2013_01_002_A_52 0.873 0.000134367 1.735 0.074 1.66 1.81 0.002-0.02
2013_01_002_A_75 0.949 6.58116E-05 1.829 0.054 1.78 1.88 0.002-0.02
2013_02_001_A_47 2.442 0.063 2.38 2.51 0.002-0.02
2013_02_001_A_56 2.259 0.052 2.21 2.31 0.002-0.02
2013_02_001_A_62 2.072 0.07 2 2.14 0.002-0.02
2013_02_002_A_20 0.96 0.000341936 2.722 0.048 2.67 2.77 0.005-0.02
2013_02_002_A_26 0.778 0.000331882 2.367 0.06 2.31 2.43 0.005-0.02
2013_02_002_A_47 0.531 0.000257239 1.352 0.095 1.26 1.45 0.005-0.02
2013_02_002_A_62 0.502 0.000286011 1.205 0.085 1.12 1.29 0.005-0.02
2013_02_002_A_22 0.908 0.000325121 2.235 0.041 2.19 2.28 0.005-0.02
2013_02_002_A_28 0.76 0.000233457 2.156 0.052 2.1 2.21 0.005-0.02
2013_02_002_A_50 0.512 0.000244115 1.705 0.065 1.64 1.77 0.005-0.02
Sample ID K/Ko Morph. Parameter (1/ppm) Fractal Dimension 95% Confidence Interval (+/-) Df- Cl Df+ Cl Fractal Fit Range (QA-1)
2013_02_002_A_64 0.509 0.000240592 1.472 0.062 1.41 1.53 0.005-0.02
2013_02_002_A_24 0.883 0.000493 2.891 0.048 2.84 2.94 0.005-0.02
2013_02_002_A_30 0.803 0.000260534 2.547 0.042 2.51 2.59 0.005-0.02
2013_02_002_A_53 0.658 0.000201108 1.871 0.049 1.82 1.92 0.005-0.02
2013_02_002_A_66 0.667 0.000187973 1.901 0.042 1.86 1.94 0.005-0.02
2013_03_001_A_26 2.443 0.078 2.37 2.52 0.005-0.02
2013_03_001_A_3 2 2.378 0.046 2.33 2.42 0.005-0.02
2013_03_001_A_47 2.149 0.035 2.11 2.18 0.005-0.02
2013_03_001_A_6 2 2.038 0.05 1.99 2.09 0.005-0.02
2013_03_001_A_28 2.45 0.087 2.36 2.54 0.005-0.02
2013_03_001_A_34 2.559 0.044 2.52 2.6 0.005-0.02
2013_03_001_A_50 2.341 0.048 2.29 2.39 0.005-0.02
2013_03_001_A_64 2.35 0.041 2.31 2.39 0.005-0.02
2013_03_001_A_36 2.445 0.065 2.38 2.51 0.005-0.02
2013_03_001_A_53 2.475 0.048 2.43 2.52 0.005-0.02
2013_03_001_A_66 2.429 0.051 2.38 2.48 0.005-0.02
2013_03_008_A_20 0.986 6.12917E-05 1.812 0.035 1.78 1.85 0.002-0.02
2013_03_008_A_26 0.905 0.000103784 1.385 0.044 1.34 1.43 0.002-0.02
2013_03_008_A_47 0.855 7.37906E-05 0.94 0.065 0.88 1.01 0.002-0.02
2013_03_008_A_6 2 0.82 0.000120804 1.113 0.043 1.07 1.16 0.002-0.02
2013_03_008_A_22 0.748 0.001570618 2.048 0.02 2.03 2.07 0.002-0.02
2013_03_008_A_28 0.691 0.00056375 1.692 0.019 1.67 1.71 0.002-0.02
2013_03_008_A_50 0.654 0.00031603 1.377 0.026 1.35 1.4 0.002-0.02
2013_03_008_A_64 0.622 0.000434803 1.302 0.045 1.26 1.35 0.002-0.02
2013_03_008_A_24 0.948 0.000169246 1.879 0.031 1.85 1.91 0.002-0.02
61


2013_03_008_A_30 0.881 0.000143677 1.548 0.03 1.52 1.58 0.002-0.02
2013_03_008_A_53 0.852 0.000117948 1.382 0.04 1.34 1.42 0.002-0.02
2013_03_008_A_66 0.824 0.00019689 1.539 0.04 1.5 1.58 0.002-0.02
2013_04_001_A_20 1.004 -2.18395E- 05 2.373 0.028 2.35 2.4 0.002-0.02
2013_04_001_A_26 0.82 0.00012502 1.162 0.054 1.11 1.22 0.002-0.02
2013_04_001_A_2 2 0.945 0.000123036 1.857 0.046 1.81 1.9 0.002-0.02
2013_04_001_A_24 0.909 0.000197904 1.77 0.052 1.72 1.82 0.002-0.02
2013_04_001_A_30 0.735 0.000149866 1.16 0.025 1.14 1.19 0.002-0.02
2013_04_018_A_20 0.9 0.000963156 2.208 0.049 2.16 2.26 0.002-0.02
2013_04_018_A_26 0.704 0.000316656 1.448 0.048 1.4 1.5 0.002-0.02
2013_04_018_A_32 0.565 0.000289126 1.013 0.062 0.95 1.08 0.002-0.02
2013_04_018_A_22 0.87 0.000554095 1.794 0.023 1.77 1.82 0.002-0.02
2013_04_018_A_28 0.665 0.000371394 1.454 0.035 1.42 1.49 0.002-0.02
2013_04_018_A_50 0.495 0.000338424 1.065 0.033 1.03 1.1 0.002-0.02
2013_04_018_A_64 0.545 0.000313865 1.113 0.039 1.07 1.15 0.002-0.02
2013_04_018_A_24 0.874 0.000964434 1.755 0.034 1.72 1.79 0.002-0.02
Sample ID K/Ko Morph. Parameter (1/ppm) Fractal Dimension 95% Confidence Interval (+/-) Df- Cl Df+ Cl Fractal Fit Range (QA-1)
2013_04_018_A_30 0.73 0.000584769 1.477 0.043 1.43 1.52 0.002-0.02
2013_04_018_A_53 0.58 0.000466247 1.184 0.045 1.14 1.23 0.002-0.02
2013_04_018_A_66 0.66 0.000516084 1.193 0.051 1.14 1.24 0.002-0.02
2013_06_002_A_20 1 0 2 0.023 1.98 2.02 0.002-0.02
2013_06_002_A_26 0.936 7.77677E-05 1.65 0.032 1.62 1.68 0.002-0.02
2013_06_002_A_32 0.787 0.000138361 1.25 0.048 1.2 1.3 0.002-0.02
2013_06_002_A_22 0.998 7.91845E-06 2.06 0.017 2.04 2.08 0.002-0.02
2013_06_002_A_28 0.913 0.000109556 1.72 0.02 1.7 1.74 0.002-0.02
2013_06_002_A_50 0.804 9.63493E-05 1.17 0.034 1.14 1.2 0.002-0.02
2013_06_002_A_64 0.811 0.000120775 1.38 0.025 1.36 1.41 0.002-0.02
2013_06_002_A_24 1.92 0.035 1.89 1.96 0.002-0.02
2013_06_002_A_30 1.58 0.039 1.54 1.62 0.002-0.02
2013_06_002_A_53 1.29 0.045 1.25 1.34 0.002-0.02
2013_06_002_A_66 1.34 0.053 1.29 1.39 0.002-0.02
2013_08_001_A_20 0.8 0.000949388 1.93 0.036 1.89 1.97 0.002-0.02
2013_08_001_A_26 0.89 5.59141E-05 1.3 0.046 1.25 1.35 0.002-0.02
2013_08_001_A_47 0.64 0.000121416 0.319 0.07 0.25 0.39 0.002-0.02
2013_08_001_A_6 2 0.651 0.000126675 0.511 0.055 0.46 0.57 0.002-0.02
2013_08_001_A_2 2 0.97 7.1707E-05 2.05 0.032 2.02 2.08 0.002-0.02
2013_08_001_A_28 0.84 0.000106701 1.42 0.036 1.38 1.46 0.002-0.02
2013_08_001_A_50 0.67 0.000140859 0.529 0.053 0.48 0.58 0.002-0.02
2013_08_001_A_64 0.77 0.000120096 1.01 0.047 0.96 1.06 0.002-0.02
62


2013_08_001_A_24 0.93 0.000147121 1.81 0.03 1.78 1.84 0.002-0.02
2013_08_001_A_30 0.83 0.00015844 1.48 0.03 1.45 1.51 0.002-0.02
2013_08_001_A_53 0.735 0.000149866 1.13 0.026 1.1 1.16 0.002-0.02
2013_08_001_A_66 0.83 0.000178651 1.46 0.04 1.42 1.5 0.002-0.02
2013_08_002_A_20 0.988 1.72 0.047 1.67 1.77 0.002-0.02
2013_08_002_A_26 0.92 0.000405448 2 0.074 1.93 2.07 0.002-0.02
2013_08_002_A_47 0.827 0.000174792 1.64 0.1 1.54 1.74 0.002-0.02
2013_08_002_A_62 1.03 -3.22433E- 05 1.79 0.093 1.7 1.88 0.002-0.02
2013_08_002_A_22 0.96 2.25 0.039 2.21 2.29 0.002-0.02
2013_08_002_A_28 0.881 0.000589175 2.43 0.051 2.38 2.48 0.002-0.02
2013_08_002_A_50 0.782 0.000262707 1.95 0.079 1.87 2.03 0.002-0.02
2013_08_002_A_64 0.915 0.000134768 2.11 0.077 2.03 2.19 0.002-0.02
2013_08_002_A_24 0.97 2.3 0.039 2.26 2.34 0.002-0.02
2013_08_002_A_30 0.914 0.00047023 2.27 0.048 2.22 2.32 0.002-0.02
2013_08_002_A_53 0.856 0.000254227 2.12 0.073 2.05 2.19 0.002-0.02
2013_08_002_A_66 0.91 0.000371422 2.33 0.052 2.28 2.38 0.002-0.02
2013_08_003_A_20 0 0
2013_08_003_A_26 1.89 0.151 1.74 2.04 0.002-0.02
2013_08_003_A_47 2.34 0.049 2.29 2.39 0.002-0.02
Sample ID K/Ko Morph. Parameter (1/ppm) Fractal Dimension 95% Confidence Interval (+/-) Df- Cl Df+ Cl Fractal Fit Range (QA-1)
2013_08_003_A_6 2 2.04 0.057 1.98 2.1 0.002-0.02
2013_08_003_A_22 0 0
2013_08_003_A_28 0 0
2013_08_003_A_50 2.08 0.127 1.95 2.21 0.005-0.015
2013_08_003_A_64 3.1 0.163 2.94 3.26 0.005-0.015
2013_08_003_A_24 1.32 0.242 1.08 1.56 0.005-0.012
2013_08_003_A_30 0 0
2013_08_003_A_53 2.7 0.464 2.24 3.16 0.005-0.012
2013_08_003_A_66 0 0
2013_09_001_A_20 0.99 0.889 0.1574 0.73 1.05 0.003-0.02
2013_09_001_A_26 1.01 1.136 0.1448 0.99 1.28 0.003-0.02
2013_09_001_A_47 1.014 2.265 0.2435 2.02 2.51 0.003-0.02
2013_09_001_A_6 2 1.077 1.595 0.1288 1.47 1.72 0.003-0.02
2013_09_001_A_2 2 1.002 1.138 0.2205 0.92 1.36 0.008-0.02
2013_09_001_A_28 1.01 1.352 0.2146 1.14 1.57 0.008-0.02
2013_09_001_A_50 1.015 1.574 0.174 1.4 1.75 0.008-0.02
2013_09_001_A_64 1.048 0 0
2013_09_001_A_24 0.999 0 0
2013_09_001_A_30 1.002 0 0
63


2013_09_001_A_53 1.011 0 0
2013_09_001_A_66 1.033 0 0
2013_09_002_A_20 0.885 0.001015936 2.044 0.0382 2.01 2.08 0.002-0.02
2013_09_002_A_26 0.72 0.000550961 1.554 0.0218 1.53 1.58 0.002-0.02
2013_09_002_A_47 0.47 0.000534557 1.092 0.0255 1.07 1.12 0.002-0.02
2013_09_002_A_62 0.54 0.000530629 1.142 0.0265 1.12 1.17 0.002-0.02
2013_09_002_A_22 0.89 0.000999965 1.721 0.0497 1.67 1.77 0.002-0.02
2013_09_002_A_28 0.69 0.001040095 1.584 0.0351 1.55 1.62 0.002-0.02
2013_09_002_A_50 0.512 0.000891351 1.363 0.0291 1.33 1.39 0.002-0.02
2013_09_002_A_64 0.55 0.000900258 1.423 0.0338 1.39 1.46 0.002-0.02
2013_09_002_A_24 0.96 0.000445372 2.297 0.0436 2.25 2.34 0.002-0.02
2013_09_002_A_30 0.8 0.000967492 2.1 0.0278 2.07 2.13 0.002-0.02
2013_09_002_A_53 0.69 0.000733304 1.785 0.0351 1.75 1.82 0.002-0.02
2013_09_002_A_66 0.72 0.000731604 1.864 0.0331 1.83 1.9 0.002-0.02
Sample ID Straight Transmission {%) Dyn. Viscosity Fluid, From Pang (kg/(m*s)) Clean Bed d50 calc with Kozeny Carmen (m) Reynolds Number, Clean Bed d50 Aggregate Radius of Gyration (m)
2012_03_001_A_6 0.0027478
2012_03_001_A_7 0.0027478
2012_03_001_A_11 0.0027478
2012_04_002_A_15 0.0027478
2012_05_001_A_12 0.0027478
2012_05_001_A_15 0.0027478
2012_05_001_A_21 0.0027478
2012_05_001_A_27 0.0027478
2012_06_001_A_12 0.0027478
2012_06_001_A_18 0.0027478
2012_06_001_A_24 0.0027478
2012_06_001_A_30 0.0027478
2012_06_002_A_24 0.0027478
2012_06_002_A_27 0.0027478
2012_06_002_A_30 0.0027478
2012_06_003_A_15 0.0027478
2012_06_003_A_21 0.0027478
2013_01_002_A_42 0.7 0.0027478 0.00306899 1.590061815 0.00120099
2013_01_002_A_48 0.1 0.0027478 0.00306899 1.590061815 18.9
2013_01_002_A_54 0.1 0.0027478 0.00306899 1.590061815 162.9
2013_01_002_A_88 0.2 0.0027478 0.00306899 1.590061815 0.070543303
2013_01_002_A_41 5.6 0.0027478 0.00349919 1.812949406 0.00024343
64


2013_01_002_A_47 0.4 0.0027478 0.00349919 1.812949406 0.006130301
2013_01_002_A_53 0.2 0.0027478 0.00349919 1.812949406 0.257430453
2013_01_002_A_82 0.6 0.0027478 0.00349919 1.812949406 0.007198757
2013_01_002_A_40 16 0.0027478 0.00201134 1.042085583 7.85844E-05
2013_01_002_A_46 1.2 0.0027478 0.00201134 1.042085583 0.000438965
2013_01_002_A_52 0.5 0.0027478 0.00201134 1.042085583 0.002588433
2013_01_002_A_75 0.8 0.0027478 0.00201134 1.042085583 0.001288721
2013_02_001_A_47 4.2 0.0027478 0.0
2013_02_001_A_56 3.7 0.0027478 0.0
2013_02_001_A_62 2.6 0.0027478 0.0
2013_02_002_A_20 7.6 0.0027478 0.00316179 0.855507561 2.28959E-05
2013_02_002_A_26 0.6 0.0027478 0.00316179 0.855507561 0.000126917
2013_02_002_A_47 0.1 0.0027478 0.00316179 0.855507561 0.1
2013_02_002_A_62 0.1 0.0027478 0.00313237 0.831853823 0.7
2013_02_002_A_22 5.2 0.0027478 0.00262811 0.711105939 0.000129938
2013_02_002_A_28 0.5 0.0027478 0.00262811 0.711105939 0.000334394
2013_02_002_A_50 0.1 0.0027478 0.00262811 0.711105939 0.0
Sample ID Straight Transmission {%) Dyn. Viscosity Fluid, From Pang (kg/(m*s)) Clean Bed d50 calc with Kozeny Carmen (m) Reynolds Number, Clean Bed d50 Aggregate Radius of Gyration (m)
2013_02_002_A_64 0.1 0.0027478 0.00260366 0.69144473 0.037803485
2013_02_002_A_24 3.1 0.0027478 0.00275638 0.745814201 2.09565E-05
2013_02_002_A_30 0.5 0.0027478 0.00275638 0.745814201 0.0
2013_02_002_A_53 0.1 0.0027478 0.00275638 0.745814201 0.0
2013_02_002_A_66 0.1 0.0027478 0.00273074 0.72519335 0.0
2013_03_001_A_26 5.5 0.0027478 0.0
2013_03_001_A_3 2 1 0.0027478 0.0
2013_03_001_A_47 0.2 0.0027478 0.0
2013_03_001_A_6 2 0.2 0.0027478 0.0
2013_03_001_A_28 4.7 0.0027478 0.0
2013_03_001_A_34 0.9 0.0027478 0.0
2013_03_001_A_50 0.3 0.0027478 0.0
2013_03_001_A_64 0.3 0.0027478 0.000163405
2013_03_001_A_36 5.5 0.0027478 6.33965E-05
2013_03_001_A_53 2 0.0027478 7.25449E-05
2013_03_001_A_66 2.2 0.0027478 8.3603E-05
2013_03_008_A_20 7.4 0.0027478 0.00180955 1.053594383 0.001142425
2013_03_008_A_26 0.8 0.0027478 0.00180955 1.053594383 0.070667964
2013_03_008_A_47 0.2 0.0027478 0.00180955 1.053594383 132.2003646
2013_03_008_A_6 2 0.3 0.0027478 0.00182041 1.072692483 3.670156468
65


2013_03_008_A_22 6.5 0.0027478 0.00098665 0.574472081 0.000336459
2013_03_008_A_28 1 0.0027478 0.00098665 0.574472081 0.00454141
2013_03_008_A_50 0.3 0.0027478 0.00098665 0.574472081 0.103856711
2013_03_008_A_64 0.4 0.0027478 0.00099258 0.584885315 0.206086052
2013_03_008_A_24 4.1 0.0027478 0.00106094 0.617724462 0.000951972
2013_03_008_A_30 0.8 0.0027478 0.00106094 0.617724462 0.015199454
2013_03_008_A_53 0.4 0.0027478 0.00106094 0.617724462 0.094559229
2013_03_008_A_66 0.7 0.0027478 0.00106731 0.628921716 0.017751557
2013_04_001_A_20 6.3 0.0027478 0.00096433 0.288466613 9.78218E-05
2013_04_001_A_26 0.2 0.0027478 0.00096433 0.288466613 1.664349307
2013_04_001_A_2 2 2.4 0.0027478 0.00084692 0.253344944 0.001309999
2013_04_001_A_24 2.1 0.0027478 0.00092775 0.277525481 0.002224465
2013_04_001_A_30 0.2 0.0027478 0.00092775 0.277525481 2.193772665
2013_04_018_A_20 11.1 0.0027478 0.00087566 0.123731943 0.000137698
2013_04_018_A_26 0.5 0.0027478 0.00087566 0.123731943 0.04410279
2013_04_018_A_32 0.1 0.0027478 0.00087566 0.123731943 28.75836996
2013_04_018_A_22 9 0.0027478 0.00082639 0.116769461 0.001350119
2013_04_018_A_28 0.6 0.0027478 0.00082639 0.116769461 0.041854654
2013_04_018_A_50 0.1 0.0027478 0.00082639 0.116769461 11.6751359
2013_04_018_A_64 0.2 0.0027478 0.00082639 0.116769461 4.672322302
2013_04_018_A_24 14.5 0.0027478 0.00089144 0.125961527 0.001209388
Sample ID Straight Transmission {%) Dyn. Viscosity Fluid, From Pang (kg/{m*s)) Clean Bed d50 calc with Kozeny Carmen (m) Reynolds Number, Clean Bed d50 Aggregate Radius of Gyration (m)
2013_04_018_A_30 2 0.0027478 0.00089144 0.125961527 0.020561448
2013_04_018_A_53 0.5 0.0027478 0.00089144 0.125961527 1.005206277
2013_04_018_A_66 1.1 0.0027478 0.00089144 0.125961527 0.630352498
2013_06_002_A_20 12.4 0.0027478 0.00115259 0.693032259 0.000366077
2013_06_002_A_26 1 0.0027478 0.00115259 0.693032259 0.006774995
2013_06_002_A_32 0.3 0.0027478 0.00115259 0.693032259 0.533611598
2013_06_002_A_22 5.4 0.0027478 0.00072637 0.436755022 0.000359255
2013_06_002_A_28 0.8 0.0027478 0.00072637 0.436755022 0.004156715
2013_06_002_A_50 0.1 0.0027478 0.00072637 0.436755022 2.012229437
2013_06_002_A_64 0.2 0.0027478 0.00072637 0.436755022 0.116339697
2013_06_002_A_24 2.7 0.0027478 0.000864803
2013_06_002_A_30 0.7 0.0027478 0.012396401
2013_06_002_A_53 0.3 0.0027478 0.308253184
2013_06_002_A_66 0.3 0.0027478 0.15102743
2013_08_001_A_20 5.2 0.0027478 0.0010372 0.616373682 0.000589769
2013_08_001_A_26 0.2 0.0027478 0.0010372 0.616373682 0.282925571
66


2013_08_001_A_47 0.1 0.0027478 0.0010372 0.616373682 1.06488E+21
2013_08_001_A_6 2 0.1 0.0027478 0.0010372 0.616373682 20893601259
2013_08_001_A_2 2 1.7 0.0027478 0.00085356 0.507245461 0.000445533
2013_08_001_A_28 0.2 0.0027478 0.00085356 0.507245461 0.065045781
2013_08_001_A_50 0.1 0.0027478 0.00085356 0.507245461 3724762065
2013_08_001_A_64 0.1 0.0027478 0.00085356 0.507245461 26.1647877
2013_08_001_A_24 2.2 0.0027478 0.00084982 0.505023613 0.001613166
2013_08_001_A_30 0.4 0.0027478 0.00084982 0.505023613 0.029562767
2013_08_001_A_53 0.1 0.0027478 0.00084982 0.505023613 2.998761227
2013_08_001_A_66 0.6 0.0027478 0.00084982 0.505023613 0.032640061
2013_08_002_A_20 31.8 0.0027478 0.00362548 2.276222514 0.000540176
2013_08_002_A_26 6.3 0.0027478 0.00362548 2.276222514 0.000278526
2013_08_002_A_47 0.4 0.0027478 0.00362548 2.276222514 0.005123412
2013_08_002_A_62 0.5 0.0027478 0.00362548 2.276222514 0.001726338
2013_08_002_A_22 28.5 0.0027478 0.00234916 1.474892651 6.04099E-05
2013_08_002_A_28 4.4 0.0027478 0.00234916 1.474892651 6.25779E-05
2013_08_002_A_50 0.4 0.0027478 0.00234916 1.474892651 0.000770819
2013_08_002_A_64 0.8 0.0027478 0.00234916 1.474892651 0.000309685
2013_08_002_A_24 31.2 0.0027478 0.00224061 1.406743164 5.31522E-05
2013_08_002_A_30 7.7 0.0027478 0.00224061 1.406743164 9.74401E-05
2013_08_002_A_53 1.1 0.0027478 0.00224061 1.406743164 0.000289244
2013_08_002_A_66 4.4 0.0027478 0.00224061 1.406743164 9.07243E-05
2013_08_003_A_20 44.9 0.0027478
2013_08_003_A_26 42.5 0.0027478
2013_08_003_A_47 27.8 0.0027478
Sample ID Straight Transmission {%) Dyn. Viscosity Fluid, From Pang (kg/(m*s)) Clean Bed d50 calc with Kozeny Carmen (m) Reynolds Number, Clean Bed d50 Aggregate Radius of Gyration (m)
2013_08_003_A_6 2 24 0.0027478
2013_08_003_A_22 53.9 0.0027478
2013_08_003_A_28 50.2 0.0027478
2013_08_003_A_50 42.4 0.0027478
2013_08_003_A_64 37.8 0.0027478
2013_08_003_A_24 60.2 0.0027478
2013_08_003_A_30 59.8 0.0027478
2013_08_003_A_53 62.5 0.0027478
2013_08_003_A_66 54 0.0027478
2013_09_001_A_20 31.7 0.0027478 0.0109947 6.48972679 1.069505625
2013_09_001_A_26 31.4 0.0027478 0.0109947 6.48972679 0.029620503
2013_09_001_A_47 30.7 0.0027478 0.0109947 6.48972679 2.87895E-05
2013_09_001_A_6 2 31.7 0.0027478 0.0109947 6.48972679 0.000557106
67


2013_09_001_A_2 2 36.5 0.0027478 0.00744899 4.396838481 0.017997839
2013_09_001_A_28 36.2 0.0027478 0.00744899 4.396838481 0.00223531
2013_09_001_A_50 34.8 0.0027478 0.00744899 4.396838481 0.000589363
2013_09_001_A_64 36.9 0.0027478 0.00744899 4.396838481
2013_09_001_A_24 39 0.0027478 0.00755289 4.458164156
2013_09_001_A_30 38.8 0.0027478 0.00755289 4.458164156
2013_09_001_A_53 36.4 0.0027478 0.00755289 4.458164156
2013_09_001_A_66 40.5 0.0027478 0.00755289 4.458164156
2013_09_002_A_20 9.6 0.0027478 0.00072164 0.05467226 0.000271591
2013_09_002_A_26 1.2 0.0027478 0.00072164 0.05467226 0.011634635
2013_09_002_A_47 0.3 0.0027478 0.00072164 0.05467226 5.163190695
2013_09_002_A_62 0.4 0.0027478 0.00072544 0.055542366 1.882479892
2013_09_002_A_22 14 0.0027478 0.00074256 0.056257292 0.001323948
2013_09_002_A_28 3 0.0027478 0.00074256 0.056257292 0.006710885
2013_09_002_A_50 0.8 0.0027478 0.00074256 0.056257292 0.082431212
2013_09_002_A_64 1 0.0027478 0.00074647 0.057152623 0.040898899
2013_09_002_A_24 14.4 0.0027478 0.00088382 0.06695957 9.335E-05
2013_09_002_A_30 4.6 0.0027478 0.00088382 0.06695957 0.000298522
2013_09_002_A_53 1.4 0.0027478 0.00088382 0.06695957 0.002173941
2013_09_002_A_66 1.8 0.0027478 0.00088848 0.068025228 0.00129225
Sample ID Comments
2012_03_001_A_6 No Salt
2012_03_001_A_7 No Salt
2012_03_001_A_11 No Salt
2012_04_002_A_15 Questionable head data, due to changes in salt cone effect on Nation
2012_05_001_A_12 Questionable head data, due to changes in salt cone effect on Nation
2012_05_001_A_15 Questionable head data, due to changes in salt cone effect on Nation
2012_05_001_A_21 Questionable head data, due to changes in salt cone effect on Nation, Clear started at 196 ml eluted
2012_05_001_A_27 Volume clear eluded after deposition,
2012_06_001_A_12 Head data taken before and after scan only
2012_06_001_A_18 Head data taken before and after scan only
2012_06_001_A_24 Head data taken before and after scan only, Clear started at 182 ml eluted
2012_06_001_A_30 Volume clear eluded after deposition, same head data
2012_06_002_A_24
2012_06_002_A_27 Clear started at 188 ml eluted
2012_06_002_A_30 Volume clear eluded after deposition, same head data
2012_06_003_A_15 Later scans look bad
68


2012_06_003_A_21 Later scans look bad
2013_01_002_A_42 deposition
2013_01_002_A_48 deposition
2013_01_002_A_54 No Flow, after deposition, Clear started at 377 ml eluted
2013_01_002_A_88 clear flow with partial recycle
2013_01_002_A_41 deposition
2013_01_002_A_47 deposition
2013_01_002_A_53 No Flow, after deposition, Clear started at 377 ml eluted
2013_01_002_A_82 clear flow with partial recycle
2013_01_002_A_40 deposition
2013_01_002_A_46 deposition
2013_01_002_A_52 No Flow, after deposition, Clear started at 377 ml eluted
2013_01_002_A_75 clear flow with partial recycle
2013_02_001_A_47 No Flow, after deposition, Nafion/salt problems, No Pressure Equilibrium, Clear Flow started at 356 ml eluted
2013_02_001_A_56 clear flow, nafion problems, No Pressure Equilibrium
2013_02_001_A_62 clear flow, nafion problems, No Pressure Equilibrium
2013_02_002_A_20 deposition, Nafion Equil Not Great
2013_02_002_A_26 deposition, Nafion Equil Not Great
2013_02_002_A_47 deposition, no flow, Nafion Equil Not Great, Clear flow started at 332 ml eluted
2013_02_002_A_62 Clear Flow, Nafion Equil Not Great
2013_02_002_A_22 deposition, Nafion Equil Not Great
2013_02_002_A_28 deposition, Nafion Equil Not Great
2013_02_002_A_50 deposition, no flow, Nafion Equil Not Great, Clear flow started at 332 ml eluted
Sample ID Comments
2013_02_002_A_64 Clear Flow, Nafion Equil Not Great
2013_02_002_A_24 deposition, Nafion Equil Not Great
2013_02_002_A_30 deposition, Nafion Equil Not Great
2013_02_002_A_53 deposition, no flow, Nafion Equil Not Great, Clear flow started at 332 ml eluted
2013_02_002_A_66 Clear Flow, Nafion Equil Not Great
2013_03_001_A_26 deposition, bad head data
2013_03_001_A_3 2 deposition, bad head data
2013_03_001_A_47 deposition, no flow, bad head data, Clear flow started at 343 ml eluted
2013_03_001_A_6 2 Clear Flow, bad head data
2013_03_001_A_28 deposition, bad head data
2013_03_001_A_34 deposition, bad head data
2013_03_001_A_50 deposition, no flow, bad head data, Clear flow started at 343 ml eluted
2013_03_001_A_64 Clear Flow, bad head data
2013_03_001_A_36 deposition, bad head data
2013_03_001_A_53 deposition, no flow, bad head data, Clear flow started at 343 ml eluted
69


2013_03_001_A_66 Clear Flow, bad head data
2013_03_008_A_20 deposition
2013_03_008_A_26 deposition
2013_03_008_A_47 deposition, no flow, Clear flow started at 485 ml eluted
2013_03_008_A_6 2 Clear Flow
2013_03_008_A_22 deposition
2013_03_008_A_28 deposition
2013_03_008_A_50 deposition, no flow, Clear flow started at 485 ml eluted
2013_03_008_A_64 Clear Flow
2013_03_008_A_24 deposition
2013_03_008_A_30 deposition
2013_03_008_A_53 deposition, no flow, Clear flow started at 485 ml eluted
2013_03_008_A_66 Clear Flow
2013_04_001_A_20 deposition, scan maxed out at later times
2013_04_001_A_26 deposition
2013_04_001_A_2 2 deposition
2013_04_001_A_24 deposition
2013_04_001_A_30 deposition
2013_04_018_A_20 deposition, scan maxed out at later times
2013_04_018_A_26 deposition
2013_04_018_A_32 deposition, no flow
2013_04_018_A_22 deposition
2013_04_018_A_28 deposition
2013_04_018_A_50 deposition, no flow, Clear flow started at 307 ml eluted
2013_04_018_A_64 Clear Flow
2013_04_018_A_24 deposition
Sample ID Comments
2013_04_018_A_30 deposition
2013_04_018_A_53 deposition, no flow, Clear flow started at 307 ml eluted
2013_04_018_A_66 Clear Flow
2013_06_002_A_20 Deposittion flow, bad later data
2013_06_002_A_26 Deposittion flow, bad later data
2013_06_002_A_32 Deposittion flow, bad later data
2013_06_002_A_22 deposition
2013_06_002_A_28 deposition
2013_06_002_A_50 deposition, no flow, Clear flow started at 492 ml eluted
2013_06_002_A_64 Clear Flow
2013_06_002_A_24 No Transducer DATA Dep Flow
2013_06_002_A_30 No Transducer DATA Dep Flow
70


2013_06_002_A_53 No Transducer DATA Dep Flow, No Flow, Clear flow started at 492 ml eluted
2013_06_002_A_66 No Transducer DATA Clear Flow
2013_08_001_A_20 deposition
2013_08_001_A_26 deposition
2013_08_001_A_47 deposition, no flow, Clear flow started at 513 ml eluted
2013_08_001_A_6 2 Clear Flow.
2013_08_001_A_2 2 deposition
2013_08_001_A_28 deposition
2013_08_001_A_50 deposition, no flow,, Clear flow started at 513 ml eluted
2013_08_001_A_64 Clear Flow
2013_08_001_A_24 deposition
2013_08_001_A_30 deposition
2013_08_001_A_53 deposition, no flow, Clear flow started at 513 ml eluted
2013_08_001_A_66 Clear Flow
2013_08_002_A_20 deposition
2013_08_002_A_26 deposition
2013_08_002_A_47 deposition, no flow, Clear flow started at 520 ml eluted
2013_08_002_A_62 Clear Flow.
2013_08_002_A_22 deposition
2013_08_002_A_28 deposition
2013_08_002_A_50 deposition, no flow,, Clear flow started at 520 ml eluted
2013_08_002_A_64 Clear Flow
2013_08_002_A_24 deposition
2013_08_002_A_30 deposition
2013_08_002_A_53 deposition, no flow, Clear flow started at 520 ml eluted
2013_08_002_A_66 Clear Flow
2013_08_003_A_20 deposition, No Nation Equilibrium
2013_08_003_A_26 deposition, No Nation Equilibrium
2013_08_003_A_47 deposition, no flow, No Nation Equilibrium Clear flow started at 521 ml eluted
Sample ID Comments
2013_08_003_A_6 2 Clear Flow., No Nation Equilibrium
2013_08_003_A_22 deposition, No Nation Equilibrium
2013_08_003_A_28 deposition, No Nation Equilibrium
2013_08_003_A_50 deposition, no flow,, No Nation Equilibrium Clear flow started at 521 ml eluted
2013_08_003_A_64 Clear Flow, No Nation Equilibrium
2013_08_003_A_24 deposition, No Nation Equilibrium
2013_08_003_A_30 deposition, No Nation Equilibrium
2013_08_003_A_53 deposition, no flow, No Nation Equilibrium Clear flow started at 521 ml eluted
2013_08_003_A_66 Clear Flow, No Nation Equilibrium
71


2013_09_001_A_20 deposition
2013_09_001_A_26 deposition
2013_09_001_A_47 deposition, no flow, Clear flow started at 527 ml eluted
2013_09_001_A_6 2 Clear Flow.
2013_09_001_A_2 2 deposition
2013_09_001_A_28 deposition
2013_09_001_A_50 deposition, no flow,, Clear flow started at 527 ml eluted
2013_09_001_A_64 Clear Flow, No Clear Linear Region for Df
2013_09_001_A_24 deposition, No Clear Linear Region for Df
2013_09_001_A_30 deposition, No Clear Linear Region for Df
2013_09_001_A_53 deposition, no flow, No Clear Linear Region for Df, Clear flow started at 527 ml eluted
2013_09_001_A_66 Clear Flow, No Clear Linear Region for Df
2013_09_002_A_20 deposition
2013_09_002_A_26 deposition
2013_09_002_A_47 deposition, no flow, Clear flow started at 248 ml eluted
2013_09_002_A_62 Clear Flow.
2013_09_002_A_22 deposition
2013_09_002_A_28 deposition
2013_09_002_A_50 deposition, no flow,, Clear flow started at 248 ml eluted
2013_09_002_A_64 Clear Flow
2013_09_002_A_24 deposition
2013_09_002_A_30 deposition
2013_09_002_A_53 deposition, no flow, Clear flow started at 248 ml eluted
2013_09_002_A_66 Clear Flow
72


Results From Rifle Samples
Collectec
4-15-13
Well ID Sample # Scan ID Settled / Agitated Sample SLS Amplification Flow rate (ml/min) Colloid Concentration (g/ml) Colloid Concentration (ppm)
LR01 2 2013_04_003_A_2 Settled 0.65 650 1.86047E-05 18.60465116
LR01 2 2013_04_003_B_1 Agitated 0.65 650 1.86047E-05 18.60465116
LR01 3 2013_04_004_A_2 Settled 0.65 0 1.86047E-05 18.60465116
LR01 3 2013_04_004_B_2 Agitated 0.65 0 1.86047E-05 18.60465116
FP101 6 2013_04_006_A_2 Settled 0.65 640 6.74419E-06 6.744186047
FP101 6 2013_04_006_B_1 Agitated 0.65 640 6.74419E-06 6.744186047
FP101 7 2013_04_007_B_2 Agitated 0.65 0 6.74419E-06 6.744186047
CD03 10 2013_04_009_A_2 Settled 0.45 880 1.51163E-05 15.11627907
CD03 10 2013_04_009_B_2 Agitated 0.45 880 1.51163E-05 15.11627907
CD03 11 2013_04_010_A_2 Settled 0.45 0 1.51163E-05 15.11627907
CD03 11 2013_04_010_B_2 Agitated 0.45 0 1.51163E-05 15.11627907
G51 14 2013_04_012_A_2 Settled 0.45 450 1.81395E-05 18.13953488
G51 14 2013_04_012_B_2 Agitated 0.45 450 1.81395E-05 18.13953488
G51 15 2013_04_013_A_2 Settled 0.45 0 1.81395E-05 18.13953488
G51 15 2013_04_013_B_2 Agitated 0.45 0 1.81395E-05 18.13953488
Well ID pH Temperature (deg C) Conductivity (uS/cm) Ionic Strength (M) Fractal Dimension RA2 95% Conf Interv
LR01 7.44 10.8 1634 0.026144 2.21 0.958 0.111
LR01 7.44 10.8 1634 0.026144 1.71 0.898 0.139
LR01 7.44 10.8 1634 0.026144 2.45 0.974 0.096
LR01 7.44 10.8 1634 0.026144 1.52 0.939 0.093
FP101 7.26 9.4 3300 0.0528 1.69 0.943 0.1
FP101 7.26 9.4 3300 0.0528 1.81 0.958 0.092
FP101 7.26 9.4 3300 0.0528 2.27 0.916 0.166
CD03 7.3 9 3100 0.0496 1.74 0.984 0.054
CD03 7.3 9 3100 0.0496 1.82 0.984 0.056
CD03 7.3 9 3100 0.0496 1.96 0.979 0.07
CD03 7.3 9 3100 0.0496 2.09 0.972 0.086
G51 7.51 8.2 2785 0.04456 1.85 0.994 0.034
G51 7.51 8.2 2785 0.04456 1.82 0.993 0.036
G51 7.51 8.2 2785 0.04456 1.78 0.987 0.05
G51 7.51 8.2 2785 0.04456 1.71 0.979 0.06
73


Comments
Well ID
LR01
LR01
LR01
LR01
FP101
FP101
FP101
CD03
CD03
CD03
CD03
G51
G51
G51
G51
Unknown Colloids, Monitor Well
Unknown Colloids, Monitor Well
Unknown Colloids, Monitor Well
Unknown Colloids, Monitor Well
Clay Colloids, Monitor Well
Clay Colloids, Monitor Well
Clay Colloids, Monitor Well
Ferric Oxide Colloids, Acetate and Dissolved 02 Injections
Ferric Oxide Colloids, Acetate and Dissolved 02 Injections
Ferric Oxide Colloids, Acetate and Dissolved 02 Injections
Ferric Oxide Colloids, Acetate and Dissolved 02 Injections
Bio-colloids, Well Clogged Due to 3 Successive Acetate Injections
Bio-colloids, Well Clogged Due to 3 Successive Acetate Injections
Bio-colloids, Well Clogged Due to 3 Successive Acetate Injections
Bio-colloids, Well Clogged Due to 3 Successive Acetate Injections
74


Appendix B
Additional Method Information
Specific Deposit Calibration Curve
Motivation
In order to quantify the effect of deposit fractal dimension on permeability, it is crucial that
we also know the specific deposit of colloidal aggregates in the precise area of the flow cell that is
being scanned. Prior to this technique, we had planned to employ a mass balance approach using a
spectrometer at the inlet and outlet of the flow cell. Unfortunately a simple mass balance would not
supply information about the specific cross section for which we have a fractal dimension
measurement. The best solution to this problem will utilize intensity scan data that we regularly
collect for each scan.
Theory for Static Light Scattering Concentration Scans
In order to determine specific deposit independently of deposit morphology, the technique
used to measure specific deposit data can only be a function of colloid concentration, not colloid
structure or any other variable that could change with each scan. On the I vs. Q plot, the only point
that is theoretically independent of deposit morphology is at Q = 1/r. Since the colloid radius is
constant, regardless of aggregate structure, the scattered light intensity at 1/r should only be a function
of colloid concentration at that point. Theoretical calculations by Benjamin Gilbert on 12/7/2012
show the assumption of morphology-independent scattering at Q = 1/r to be approximately correct.
Flow Cell Preparation and Scan Procedure
For the calibration curve, 7 different colloid concentrations initially (0 ppm, 1 ppm, 3 ppm, 10
ppm, 30 ppm, 100 ppm, and 300 ppm) will be considered for four salt concentrations, 2mM, 8mM,
and 16mM. Later it was found that flow cell deposits were higher than 300ppm, so experiments were
run with an upper range of 1246 ppm. In order to keep solution mixtures homogeneous for each of
the 7 scans, a batch of clear (colloid free) solution should be partitioned to 7 samples. This is
important in order to keep index matching constant for each scan set. The samples should then be
refrigerated; this will help slow the hydration of Nafion in the flow cell. The flow cell, with flow
ports capped, should be dry packed with exactly 6.5 grams of Nafion. Add the desired concentration
of colloids to the solution, then hydrate the Nafion by solution injection with a syringe through a
pressure port. Mix the solution with the Nafion during hydration by repeated inversion. After the cell
has become saturated and is air free, close all pressure ports and continue to mix the Nafion and
colloid solution until the Nafion becomes immobile. Wait at least one hour for the flow cell and its
contents to reach temperature equilibrium before scanning.
Take SLS scans for multiple areas in the flow cell, these values will be averaged during
analysis. Visually inspect each scanned region for bubbles or contaminants. Note any temperature
changes during the scan. Repeat this procedure for duplicate and triplicate scans. Then repeat for
each salt concentration that will be used for future experiments.
75


Data Analysis
Average the intensity data throughout the cell for each concentration, leaving out any data
scanned in a region with bubbles or contaminants. Analyze the data as if it were a normal SLS scan.
For the Concentration Curve, plot intensity values at Q = 1/r versus the concentration for that scan.
Results
Figure 1: F vs QA-1 for all scans (includes blank) from lppm to 300ppm, where F is the raw intensity
corrected for the transmission factor and the cross-sectional area of the scattering region, per Mays el
al. (2011).
£
S
T vs qA-l
0.45 Amp All Sets
qA-l (nmA-l)
Oppm 2012_10_001_A
lppm 2012_10_002_A
3ppm 2012_10_003_A
1 Oppm 2012_10_004_A
30ppm 2012_10_005_A
lOOppm 2012_11_001_A
300ppm 2012_11_002_A
Oppm 2012_11_004_ADuplicate
1 ppm 2012_ll_005_ADuplicate
3 ppm 2012_11_006_A Duplicate
10 ppm 2012_11_007_A Duplicate
30 ppm 2012_11_008_A Duplicate
100 ppm 2012_11_009_A Duplicate
300ppm2012_ll_010_ADuplicate
Oppm 2012_12_001_A Triplicate
1 ppm 2012_12_002_A Triplicate
-= 3 ppm 2012_12_003_A Triplicate
lOppm 2012_12_004_ATriplicate
30 ppm 2012_12_005_A Triplicate
100 ppm 2012_12_006_A Triplicate
300 ppm 2013_01_001_A Triplicate
Table 1: F vs concentration.
Colloid Concentration (ppm) I' at 1/r 1st Set (mV) I' at 1/r 2nd Set (mV) I' at 1/r 3rd Set (mV) I' at 1/r Average (mV) Standard Deviation (mV)
0 7.96E-11 7.01E-11 5.26E-11 6.74E-11 1.37E-11
0.802568218 8.18E-11 5.17E-11 6.54E-11 6.63E-11 1.51E-11
2.407704655 9.90E-11 7.17E-11 6.84E-11 7.97E-11 1.68E-11
8.025682183 5.52E-10 4.07E-10 4.02E-10 4.54E-10 8.53E-11
24.07704655 5.89E-10 3.60E-10 5.47E-10 4.99E-10 1.22E-10
80.25682183 1.12E-09 1.09E-09 1.59E-09 1.27E-09 2.80E-10
240.7704655 2.23E-08 2.87E-08 3.07E-08 2.72E-08 4.40E-09
76


Figure 2: F vs Concentration. Note: the point at 0.1 ppm is actually the blank (0 ppm); it was
changed to facilitate plotting on a log-log plot.
If vs Concentration
Concentration (ppm)
1st Set
2nd Set
3rd Set
Average
Table 2: I vs concentration (blank has been subtracted), where I = F Ivlank per Mays et al. (2011).
Colloid Concentration (ppm) I" at 1/r 1st Set (mV) I" at 1/r 2nd Set (mV) I" at 1/r 3rd Set (mV) I" at 1/r Average (mV) Standard Deviation (mV)
0.802568218 2.22E-12 -1.84E-11 1.28E-11 -1.12E- 12 1.59E-11
2.407704655 1.95E-11 1.65E-12 1.58E-11 1.23E- 11 9.41E-12
8.025682183 4.73E-10 3.37E-10 3.49E-10 3.86E- 10 7.50E-11
24.07704655 5.10E-10 2.90E-10 4.94E-10 4.31E- 10 1.23E-10
80.25682183 1.04E-09 1.02E-09 1.54E-09 1.20E- 09 2.92E-10
240.7704655 2.22E-08 2.86E-08 3.07E-08 2.72E- 08 4.41E-09
77


Figure 3: I vs concentration
I vs Concentration
Concentration (ppm)
1st Set
2nd Set
3rd Set
Average
Figure 4: I vs concentration average, with exponential trend-line and standard deviation error bars.
I vs Concentration
)( Average
-----Expon. (Average)
Later scans at different ionic strength and colloid concentrations are summarized in figure 5.
Note that triplicate scans were not made for higher concentrations.
78


Concentration vs I 2 mM, 8mM, and
16 mM
I" (mV)
Figure 5 Concentration versus Fall data.
Discussion
Triplicate scans (Figures 2-3) indicate that this procedure is very repeatable. The line fit is
not linear, but repeatability leads us to believe that this is a reasonable technique. Concentrations
below 10 ppm show up as noise and are therefore omitted from the final curve. If future
concentration calibration curve scans (for varying ionic strength) are also repeatable, the efficacy of
this technique will have further confirmation.
Why is the calibration curve exponential, rather than linear? That is, why does increasing the
deposited colloid concentration from 25 to 50 ppm generate a smaller jump in scattering intensity than
increasing the deposited colloid concentration from 50 to 75 ppm? This is not clear, but here is one
potential explanation: Does the photo avalanche detector used to measure raw intensity, I, have a
nonlinear dependence on stimulation intensity?
Scans at different ionic strength seemed to have little effect on the curve. Unfortunately,
Concentration results seem to lose precision at higher colloid concentrations. The technique works
very well at low concentrations, but is still useful at higher concentrations.
79


Working with Nation
Nafion is, as far as we have found, the most suitable index matched porous media material for
use in our colloidal clogging experiments. Most importantly, Nafion is nicely index matched with a
fairly benign solution of isopropanol and water. The pore scale properties of the Nafion grains
effectively retain enough colloidal aggregate to cause clogging which is critical for the experiment.
Finally, hydrated Nafion is has a sufficiently rigid structure to minimize movement of the porous
media, this allows us to normalize SLS scans with a colloid free blank with the same media structure.
Unfortunately, Nafion is far from ideal. The following section will explain some of the challenges of
working with Nafion, as well as some procedural solutions.
Grain Uniformity
Nafion is available in multiple size ranges. For our experiment we used 16 to 35 mesh grains.
A grain size distribution is fine since natural porous media also exhibits a distribution of grain
diameters. Unfortunately the distribution of Nafion grain size changes from batch to batch. Also with
time and movement, smaller grains settle to the bottom of containers, making the grains larger near
the top of the container. In order to have matching media conditions between experiments it became
necessary to combine and thoroughly mix different batches of Nafion. Also, to keep Nafion evenly
mixed in the container, the container should be repeatedly inverted before apportioning.
Hydrating Nafion and Clogging
It was found that hydrating dry Nafion inside the flow cell was the most efficient way to load
and de-air the Nafion. However, the grains approximately double in size upon hydration. The result
is that small dry grains get lodged near flow inlets, outlets, and pressure ports, then swell and cause
clogs. To minimize Nafion induced clogging, the flow cell orifices were fitted with specific screening
near outlets and inlets, then pressure ports were fitted with probes.
The Effect of Flow Velocity
Hydraulic conductivity changes as the Nafion properties change. It was found that changing
flow velocity led to changes in hydraulic conductivity which took a significant amount of time to
regain equilibrium. As a rule of thumb, its best not to change the flow rate. Even during Nafion
hydration, the flow rate should match that of the experiment.
The Effect of Ionic Concentration
Ionic strength has a huge effect on the swelling potential of Nafion. Higher salt contents limit
the swelling of the Nafion. Higher salt concentrations lead to higher porosity. The effect is less
pronounced at ionic strengths above 0.05M. At lower salt concentrations, the Nafion is extremely
sensitive. Variations of salt content as low as 0.1% were shown to throw off Nafion hydraulic
conductivity equilibrium.
The Effect of Temperature
It would seem that temperature also affects the swelling potential of Nafion. Care should be
taken to ensure stable temperatures during experiments.
80


Water Jewel Blank Test
Purpose
Water jewels would seem to be a suitable index matched porous media on which bio-fdms can be
cultivated, and then analyzed for fractal dimension by static light scattering. To accomplish this, bio-
films will be grown on water jewels then sent to our lab for analysis. One assemblage of water jewels
will be used for bio-fdm growth, while another will be used as a blank (bio-fdm free) to use for the
SLS data analysis. The concern is that index matching of fluid and media is not perfect, so water
jewel packing differences between the two sets of water jewels could cause the blank to be non-
representative of the sample containing bio-fdms.
Methods
A column will be loosely packed with hydrated water jewels, and then fdled with deionized water.
SLS scans will be performed on the column at three amplification levels: 0.25, 0.45, and 0.65 amp.
The column will then be removed from the apparatus, inverted several times to redistribute the water
jewels, and then rescanned at the same amplifications. The data will then be analyzed. If there are no
major discrepancies between the two sets of scans, it follows that water jewels can be used as a blank
and should be suitable for bio-film fractal dimension measurement.
Results
Water Jewel Blank Test, 0.45 Amp
Scan 1
Scan 2, Agitated
81


0.0000001
Water Jewel BlanlrTest, 0.65 Amp
Scan 1
Scan 2, Agitated
Nation Blank at 0.3 Amp
Nafion Blank
Q (nmA-l)
Interpretation
It appears that water jewel packing has little effect on SLS measurement. Any differences between
the two scan sets appear to be noise since they are not repeated at different amplifications. For
comparison, a plot of a Nafion blank has been included, showing that the Nafion scatters substantially
more light than the water jewels. Also, the water jewels have a transmission factor of about 86%,
which is very good, especially when compared with the Nafion which is closer to 10%. The
conclusion is that water jewels should work very well for the bio-film scans.
Further Information
Prior to this experiment, Ben Gilbert asked if the water jewels could be sterilized. So dehydrated
water jewels were placed in an autoclave. After sterilization the water jewels were hydrated with
deionized water. Upon visual inspection, the water jewels appeared unaffected by the sterilization
process.
Water jewels are very sensitive to salt. Even at very low ionic concentrations, the water jewels do not
swell to their normal size or have suitable index matching when in a saline environment.
Furthermore, water jewels are not rigid. For use in clogging experiments, this makes them useless.
As deposits form, the water jewels would squish down from the vertical pressure, making SLS
measurements worthless.
82


Full Text

PAGE 1

L INKING COLLOID DEPOSIT MORPHOLOGY AND CLOGGING : INSIGHT S BY MEASUREMENT OF DEPOSIT FRACTAL DIMENSION by ERIC JAMES ROTH B.F.A. University of Colorado Boulder, 2002 B.S. University of Colorado Denver, 2011 A thesis submitted to the Faculty of the Graduate School of the University of Color ado in partial fulfilment of the requirements for the degree of Master of Science Civil Engineering Program 2013

PAGE 2

ii This thesis for the Master of Science degree by Eric James Roth has been approved for the Civil Engineering Program by David C. Mays C h a i r James C.Y. Guo Tim C. Lei November 12, 2013

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iii Roth, Eric James (M.S. Civil Engineering) Linking Colloid Deposit Morphology and Clogging: Insights through Categorization by Fractal Dimension Thesis directed by Assistant Professor David C. Mays ABSTRACT Clogging is an important limitation to essentially any technology or environmental process involving flow in porous media. Examples include (1) groundwater remediation, (2) managed or natural aquifer recharge, (3) hydrocarbon reservoir damage, (4) head loss in water treatment filters, (5) fouling in porous media reactors, and (6) nutrient flow for plants or bacteria. Clogging, that is, a detrimental reduction in permeability, is a common theme in each of these examples. Clogging results from a number of mechanisms, including deposition of colloidal particles (such as clay minerals), which is the focus of this research. Colloid deposits reduce porosity, which is recognized to play an important role in clogging, as expressed in the Kozeny Carman equation. However, recent research has demonstrated that colloid deposit morphology is also a cruci al variable in the clogging process. Accordingly, this thesis reports a series of laboratory experiments with the goal of quantifying deposit morphology as a fractal dimension, using an innovative technique based on static light scattering (SLS) in refrac tive index matched (RIM) porous media. For experiments conducted at constant flow, with constant influent suspension concentration, and initially clean porous media, results indicate that increased clogging is associated with colloid deposits having small er fractal dimensions, that is, more dendritic and space filling deposits. This result is consistent with previous research that quantified colloid deposit morphology using an empirical parameter. Clogging by colloid deposits also provides insight into t he more complex clogging mechanisms of bio clogging mineralization, and bio mineralization Although this line of work was originally motivated by problems of clogging in groundwater remediation, the methods used and the insight gained by correlating clo gging with fractal dimension are expected to have relevance to other

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iv areas where flow in porous media overlaps with colloid science: Hydrogeology, petrology, water treatment, and chemical engineering. The form and content of this abstract are approved. I recommend its publication. Approved: David C. Mays

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v DEDICATION effort to create a more balanced world. Also to those who realize that natural systems are complex, and that a complete understanding of natural processes worth a shot. Importantly, I would like to de dicate this thesis to my family. Thanks to my parents Jim and Vera my brother Paul and m y girlfriend Sarah for support and inspiration. In particular, I dedicate this thesis to my daughter Ivy, w ith the hopes that insights gained through my research might improve the natural environment that will someday be her inheritance

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vi ACKN OWLEDGEMENTS This research has passed through many hands before reaching mine. First, I must thank Dr. David C. Mays the Principal Investigator for this project David kept the fire burning thro ugh almost a decade of research which was sometimes extremely frustrating and always difficult. done my phase of the research without the efforts of my predecessors and collaborators : Asnoldo Benitez, Kevin Kennedy, Kevin Harris, Adam Kanold, Orion Cannon, Ryan Taylor, and Michael Mont Eton I would also like to thank Dr. Tim Lei for his optics expertise, Dr. Benjamin Gilbert for his unparalleled knowledge of fractals and their measurement, and Ken Williams for his much appreciated help at the Old Rifle field site. The U.S. Department of E nergy Subsurface Biochemical Research program provided funding for this research which was essential.

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vii TABLE OF CONTENT S C hapter 1. I 1.1 1.1.1 1.1.2 2 1.1.3 1.2 4 1.2 .1 Flow Through Porous Media... 4 1.2 .2 Colloids and Clogging 6 1.2.3 7 1.3 1.3.1 1.3.2 Problem Statement 8 1.4 Research 1.5 Experimental 2. ... 3. .. 3.1 Summary

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viii 3.2 Apparatus . 14 3.2.1 Fluid 3.2.2 Static 3.2.3 Head 3.3 Porous Media and Index 3.4 Colloids . 16 3.5 Other 3.5.1 Specific . 16 3.5.2 Porosity 3.5.3 Critical 17 3.6 Running 3.7 Data 3.7.1 Fractal 3.7.2 Data Reduction.. 4. 4.1 Critical Conc 20 4.2 Individual Sample s 20 4.3 Sample 29 5. ... 3 5.1 Individual 43 5.2 Sample 43 5.3 Overall 43 5.4 Discussion 44 References

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ix A ppendix A Experimental Data B.

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x LIST OF FIGURES Figure 1.1 Clogging 1.2 3.1 Experimental s 14 3.3 Flow cell during operation 3.4 Flow cell s 3.5 Static light scattering s 3.6 IQ plot for determination of fractal d 4.1 21 4.2 Linear region of IQ plot with slope equal to fractal dimension 21 .. 22 .. 22 23 24 4.7 24 25 4.9 Fractal dimension versus pore v 26

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xi 26 27 4.13 28 28 4.16 Fractal dimension vers 29 30 4.19 Normalized hydraulic conductivity versus pore volumes 30 31 31 4.22a 32 4.23a c Specifi 33 4.24a c Fractal dime nsion versus specific deposit 34 4.25a c Normalized hydraulic conductivity versus fractal di mension by pore flow velocity..35 4.26a c 36 4.27a c Normalized hydraulic conductivity versus radius of gyration by pore flow velocity..37 4.28 Fractal dimension versus specific deposit, all regions, by pore flow 38 4.29 Normalized hydraulic conductivity versus radius of gyration, 74 m/day pore flow 39

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xii 4.30 Normalized hydraulic conductivity versus radius of gyration, 138 m/day pore flow velocity, 0.049 M io 4.31 Normalized hydraulic conductivity versus radius of gyration, 292 m/day pore flow 40 4.32 Normalized hydraulic conduc tivity versus radius of gyration, 569 m/day pore flow 40 4.33 Normalized hydraulic conductivity versus radius of gyration, 588 m/day pore flow 41 4.34 Normalized hydraulic conductivity versus radius of gyration, 691 m/day pore flow 41 4.35 Normalized hydraulic conductivity versus radius of gyration, 1197 m/day po re flow 42 4.36 Normalized hydraulic conductivity versus radius of gyration, 1439 m/day pore flow 42

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xiii LIST OF TABLES Table 1.1 Typical Value .. 3 ...20

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1 1. I n t r o d u c t i o n 1.1 Motivation 1.1.1 Groundwater Remediation One responsibility of environmental and water resources engineers is to mitigate contaminated groundwater, and within this broad category, there is perhaps no better case study than uranium contamination at former mill sites. The Old Rifle site in Rifle, Colorado is a prime example At Rifle, uranium mine tailings were originally deposited in close proximity to the Colorado River. Over time uranium seeped into the soil, contaminating the saturated zone and eventually the river. In mine tailings, the source of c ontamination, were removed. Unfortunately, uranium had already contaminated a significant amount of soil. Luckily, as with many soil contamina nt s, the uranium can be mitigated by injecting specific chemicals into the contaminated zone. At Rifle, one suc cessful technique has been to supply acetate to G eobacter bacteria already present in the soil. Acetate bolsters the bacterial colonies by supplying a source of organic carbon. The bacteria reduce mobile U(VI) to immobile U(IV). The end result is that t he uranium stays in the contaminated area and out of the river. This process works quite well as long as the chemical amendments can uniformly be applied to contaminated areas. Sadly, uniform application has proven very difficult. In situ bioremediati on efforts like the previous example are constantly plagued by clogging problems. Often, well screens get caked with bio films created by the very bacteria stimulated by remediation efforts. These bio films cause well screen clogging, making injection or extraction difficult or impossible. Clogs from mineral precipitates and suspended solids can also inhibit pumping efficiency. Another problem is that clogging is present throughout saturated soils, causing large volumes of soil to have much diminished p ermeability. In the clogged soil zones, preferential pathways are forged through the soil matrix. These preferential pathways are like tiny aqueducts, carrying large flow volume through the pathways instead of evenly through all the soil. To visualize t his idea, think of a dish sponge with a drinking straw stuck through it. While the soil immediately adjacent to the

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2 preferential pathway has plenty of exposure to the chemicals, the rest of the soil does not. Therefore, a tremendous volume of chemical can be injected with little effect on the contamination. 1.1.2 Other Applications An in situ bioremediation site is not the only situation where clogging is a problem. Clogs have a detrimental effect on pumping efficiency for groundwater and petroleum extraction. For purification processes, filters must be back washed or replaced depending on the amount of clogging. Some reactors and fuel cells utilize flow through porous media; cl ogs once again knock down the efficiency. Stopping clogging is not the only reason to study the phenomenon. Clogs have a major effect on permeability, an effect which is poorly understood and rarely considered. In many scientific studies, a better under standing of permeability could be of great use. As an example, recently in situ genomic mapping of subsurface microbial communities has become an area of great interest. Thanks to increased computing power, the classification and niche differentiation of bacteria in the subsurface has become possible at a greater scale. These bacteria are responsible for a multitude of natural processes which, as is apparent from modern bio remediation techniques, can be utilized for the benefit of man. Like any living organism, subsurface bacteria are affected by the environment in which they are found. Their environment is the soil. When water infiltrates the soil, it supplies or removes materials that can support or suppress the growth of certain bacterial colonies. Therefore, the ease of water flow is a key parameter in understanding which bacteria prefer which conditions. A greater understanding of permeability, specifically at a micro scale is a puzzle piece which should prove invaluable as the scientific commun ity continues to focus on microbes. 1.1.3 Problems with Current Models The conveyance of fluids is a very old technology. Consequently, there is a great wealth of knowledge on the subject. Unfortunately, there is also a deficit of understanding when it comes to clogging and resulting effects on permeability. A handful of equations are commonly used to model flow thro ugh porous media including the Kozeny Carma n equation which relates hydraulic

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3 conductivity (K) to mean grain size and porosity of the media Kozeny Carma n is the most widely used equation for estimating hydraulic conductivity and permeability, but the values calculated are generally inaccurate by multiple orders of magnitude when compared with measured values. Subsurface flow is very comple x and more information is needed. To show just how variable K values can be in the physic al world, refer to T able 1.1. Kozeny Carma n only considers fluid and media properties, not the characteristics of the suspended solids in the fluid. Table 1.1 Typ ical Values of Hydraulic Conductivity (Fitts, 2002) Material Hydraulic Conductivity, K (cm/sec) Clean Sand 10 1 to 1 Silty Sand 10 5 to 10 1 Clay 10 10 to 10 6 Limestone and Dolomite 10 7 to 1 Sandstone 10 8 to 10 3 Igneous and Metamorphic Rock 10 11 to 10 2 Shale 10 14 to 10 8

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4 1.2 Background 1.2.1 Flow Through Porous Media Whether considering groundwater, petroleum reservoirs, or filtration processes, the fluid flow of concern is in part controlled by the porous media through which it travels Essentially porous media consists of the combination of impermeable space and voids through which the fluid can pass. Porosity is a property of the porous media equal to the fraction of media volume containing void space. Where is porosity, is volume of voids, and is the total volume Conventionally, porosity and grain size distribution of the media are used to calculate the hydraulic conductivity of the media using the Kozeny Carma n equation (Fitts 2002): where is hydraulic conductivity is the unit weight divided by the viscosity of water, is porosity, and is the median grain size of the media. Hydraulic conductivity can also be calculated using the permeability (Fitts, 2002): where and are the unit weight and dynamic viscosity of water.

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5 is flow rate, is manometer head difference over manometer distance s and is cross sectional area. icable for laminar flows with a Reynold s number less than 10, ideally less than 1 (Fitts, 2002). Reynolds number, R can be calculated using chara cteristic length L (for flow through porous media, this is mean grain diameter), velocity V dynamic viscosity and fluid density H ydraulic head is synonymous with energy potential, fluids flow from high to low potential i.e. high to low head. This head difference drives all fluid flows, and is described by a form of the Bernoulli Equation: is total head at a definite location in the f low regime is pressure over specific weight of fluid and describes the portion of energy supplied by pressure, is the energy from elevation above datum, is velocity squared over doubled gravity and describes the energy supplied by fluid mov ement, and is energy lost from friction. Flow rate is the volume of fluid movement over time and can be calculated by taking cross sectional area, A multiplied by flow velocity, V Pore flow velocity is similar to V but describes the velocity for the fluid passing through porous media.

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6 Specific deposit is another important consideration when looking at clogging. For the purposes of this thesis specific deposit , is the volume of colloids V c divided by the volume of the measured area in the flow cell (total volume, V t ). 1.2 .2 Colloids and Clogging Water flows contribute greatly to solid transport and redistribution. For surface flows, this can easily be seen in the gravel and sand left behind in the street gutter after a heavy rain. For groundwater, the porous media and slow flow velocities limit the size of solids that can be carried. Colloids are partic le s with diameters between 10 9 and 10 5 meters. Stable colloids, colloids which have not formed aggregates, stay suspended in the fluid. Clay and silt particles, bacteria, mineral precipitates, viruses, NAPL droplets, and bio films can all be considered colloids. In most situations, the pore s through which f luid flows are large enough in relation to stable colloids as to easily allow passage. However, when chemical conditions are suitable for aggregation, the resulting colloidal aggregates can get caught in the pore throats. Depending on the specific deposi t (the amount of deposited material) and theoretically deposit morphology (structu re of aggregates), permeability can be reduced. This loss of permeability is considered clogging. Figure 1.1 Clogging by colloid al aggregates with different deposit morphology (Mays, 2010)

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7 1.2.3 Fractal Dimension The idea of fractal dimension, or fractional dimension was popularized by Benoit Mandelbrot in 1967. While studying the coastline of Norway, Mandelbrot considered how the length of coastline measured increased as the scale of measure ment was reduced. In the case of this coastline, the fractal dimension quantifies how the number of scaled increments changes with the scale o f the increment. In other words, fractal dimension is a measure of geometric complexity as a function of scale. Fractal dimension can be useful in describing the compactness of a shape. A straight line would have a fractal dimension of one. A slightly curved line coul d be described as having a fractal dimension of 1.2, perhaps fill ing the space a little more than the completely straight line. Note that this compactness property is different than density. This measure of compactness comes in very handy for describing aggregate structures. Two aggregates with identical mass and density could have completely different fractal dimension. When considering multiple colloid aggregates that have become lodged in a pore space, aggregates with lower fractal dimension would ta ke up more space, and according to the theory of this study, should cause differences in fluid flow. Figure 1.2 Fractal dimension of aggregate structures (Min, 2006) For this study the fractal dimension is considered by the mass length relationship. Wh ere M is mass, L is characteristic length (radius of gyration), and D f is fractal dimension.

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8 Since specific deposit has a direct effect on hydraulic conductivity, it is useful to also consider the expanded equation for fractal dimension. Spec ific deposit can be recalculated as N which is the number of colloid particl e s, k o is a constant of proportionality assumed to be one for this experiment, is radius of gyration, is colloid radius, and D f is fractal dimension. 1.3 Overview 1.3.1 Type of Research This is exploratory research, with the goal of improving our fundamental knowledge about factors influencing hydraulic conductivity in porous media. This facet of clogging has not been fully investigated, so any result s will be presented for the first time. Ideally, the data from these experiments can be used to create a model that could be used in conjunction with historic models. 1.3.2 Problem Statement Hydraulic conductivity is a measure used to gauge the ease of fluid flow through porous media. The K value is used in a multitude of fields including groundwater remediation, water and petroleum extraction, reactor design, and for filtration processes. However, the models which cal culate K in systems with colloids are often inaccurate by orders of magnitude. An improved fundamental knowledge concerning the role of clogging by colloid aggregates would improve the accuracy of K calculations. Hypothetically, the deposit morphology of colloid aggregate structures in conjunction with specific deposit measurements should fill in some gaps in knowledge. A method for measuring deposit morphology is being investigated in this thesis. By measuring colloid aggregate structures by fractal di mension, morphology can be considered as a function of mass and characteristic length. The fractal dimension measurement will supply crucial information about the overall compactness of

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9 aggregate structures. Further, by considering fractal dimension in c onjunction with specific deposit, head loss, and clean bed porosity, the role of deposit morphology in clogging will be more apparent. 1.4 Research Scope As shown by Kanold (2008), Nafion can be used as refractive index matched porous media. Cannon (2010 ) shows that fractal dimension could be measured in the Nafion. Mont Eton (2011) demonstrated that static light scattering measurements could be made in a flow cell containing Nafion as the refractive index matched porous media. Current research will sta rt by improving the SLS and flow apparatus for ease of use and dependability. Next, extensive d ata acquisition will be performed by running experiments with index matched porous media with flow. Head loss data will be collected as colloid aggregates are deposited and cause clogging in the flow cell. Additionally, techniques for measuring specific deposit and porosity will be developed. After data collection, analysis will be performed and conclusions about the role of deposit morphology in clogging will be made. 1.5 Experimental Framework T his research involves the non de structive, real time measurement of colloid aggregate deposition in a flow cell containing transparent porous media. Measurements of head loss and specific deposit will be collected simultaneously with deposit fractal dimension. The static light scatteri ng (SLS) bench was designed by Tim Lei, the flow cell manifold was designed by Orion Cannon, porous media was ind ex matched to fluid by Adam Kan old, and aggregate fractal dimension measurement was tested by Michael Mont Eton. For the research contained in this thesis, flow cell manifold improvements were made including an improved flow cell manifold interface and a quick mounting system for the manifold to the SLS bench improvements were made to the SLS bench including a light proof, dust inhibiting, co oling system which also had to isolate the bench from vibration. Other SLS bench improvements included a v ert ical actuator for the flow cell and the repair of the pneumatic vibration damping system. P ressure transducers were added to the flow cell for he ad data, a method for measuring specific deposit with the SLS apparatus was developed, a method for measuring porosity of porous

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10 media was developed, and the ionic strength at which colloids would aggregate was determined (critical coagulation concentratio n). After an iterative process of testing and improving the setup, flow experiments were conducted at varying ionic concentration s and flow rate s Data w ere collected, analysed, and conclusion s were made.

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11 2. L i t e r a t u r e R e v i e w Mays (2007) explains colloid dynamics in aqueous environments under a variety of conditions. Colloids are defined as suspended constituents with a characteristic diameter of 1nm to 10 m. Stable c olloids tend to disperse in an aqueous environment, and consequ ently settle very slowly. However, flocculation will occur with the right combination of ionic strength, counter ion valence and pH. Colloids have very high surface area to volume ratios, therefore their behaviour is dominated by surface chemistry. Elec trostatic repulsion will cause dispersion, while van der Waals forces can lead to flocculation under the right conditions. Which forces will dominate is controlled by ionic strength, sodium adsorption ratio, and pH. Quirk Schofield diagrams plot ionic st rength versus sodium adsorption ratio to show where the critical coagulation concentration (CCC) occurs. Above the CCC line, colloids flocculate, while below the line colloids disperse Mays (2010) applies these concepts to the topic of clogging in filters soils, and membranes noting that t he mechanism for clogging in soils and dead end membranes is opposite that of granular media filters. The article ends by signalling the need for further research, using innovative new methods for measuring in situ dep osit fractal dimension and deposit location. Proof of principle for such a method is reported by Mays et al. (2011) for batch mode, or a non flow condition. Mays et al. explain the motivation, methods, results, and limitations of static light scattering through index matched porous media to reveal colloidal structure. Most importantly, fractal dimensions were obtained fo r test samples by using linear regression of data points. SLS provides real time information on dynamic colloidal aggregation, deposition, restructuring, and mobilization. SLS techniques provide less detailed geometric information than microtomography an d confocal microscopy, and thus would be most effectively utilized in conjunction with other techniques. Technical details on SLS are provided in t he review by Bushell et al (2002) which discusses fractal geometry and the techniques used to quantify frac tal properties. The basic theory behind the fractal description of aggregates is discussed, along with computer simulations of the phenomena. Bushell et al (2002) discusses the strengths and limitations of many techniques, but for the purposes

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12 of this su mmary, light scattering is the most important. Scattering measurements compare scattered light or radiation with scattering angle The result of this analysis is a quantitative measurement of fractal geometry, useful for understanding complex, chaotic, an d disordered systems. Objects found in real physical processes must have a mass fractal dimension between 1 and 3. Computer simulations which follow fractal theory have been widely used to better understand processes which form natural fractals. However these computer models are insufficient for describing real aggregation processes. This is because aggregation controls fractal dimension, fractal dimension does not control the aggregation process. Light scattering is preferable for structures of sever al microns in size. Light scattering is fast, easy and inexpensive but is complicated by interactions of light and matter. Aggregates are fractal in terms of kinetics in that they show scale invariance with time. On their own, aggregates restructure in a self similar process called Brownian motion. However, when aggregat es are exposed to fluid shea r forces, the process is no longer self similar which is apparent from a curved fractal regime in scattering plots. Additional insight into SLS is provided b y the review of Sorensen (2001), which discusses how fractal aggregates scatter and absorb light. Sorensen considers aggregate behavio u r, e xplaining that aggregation is random, leading to fractal geometry as a means of measureme nt A key result of his a n alysis is shown in Figure 3.6 Performing SLS in porous media requires transparent porous media, which is reviewed by Izkander (2010) who discusses the use of transparent media for modelling soil. In the book, three choices for transparent media are investigated: silica pow der, silica gel, and aquabeads (also know as waterjewels) Amorphous silica powder can be used to model clays, silica gels can model sands, and aquabeads can model sedime

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13 3 E x p e r i m e n t a l M e t h o d s 3.1 Summary of Experimental Approach A stream of index matched fluid containing colloids and salt wil l be eluted through a glass column packed with transparent media. A laser will be passed thro ugh the flow column Light will interact with colloids and their structures, not the transparent porous media. S t atic light scattering data will be collected. Data is then analysed using a log log plot of scattered light intensity, I vers u s scattering angle translated into the scattering wave vector Q The slope of the linear region of the resulting plot is equal to fractal dimension. Head data, specific deposit, and porosity will be collected and considered for further data analysis. Numerous sampl es will be analysed with varying ionic strength and flow velocity. A thorough explanation of the SLS measurement process can be found in the thesis by Michael E. Mont Eton ( 2011 ) Figure 3.1 Experimental summary

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14 Figure 3.2 Experimental summary 3.2 Apparatus Components 3.2 .1 Fluid Flow System Flow begins with two peristaltic pumps with adjustable flow rate. One pump supplies flow from a reservoir containing stable colloids, the other pump supplies flow from a reservoir containing a salt solution The two flows join at a confluence point downstream from the pumps at which point mixing begins. Next the flow enters the flow cell and flows through the porous media. Fluid exits the flow cell and then continues into a graduated cylinder as waste. Figure 3.3 and 3.4 Flow cell during operation and flow cell schematic (schematic by Ben Gilbert). 3. 2 .2 Static Light Scattering Bench The static light scat tering bench was designed by Tim Lei Benjamin Gilbert, and David Mays A n intensity controlled helium neon laser with a 633nm wavelength is passed through optical components, then through the flow cell. Light is scattered from the colloid aggregates. The scattered light intensity is measured by the rotating detector assembly as a function of scat tering angle

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15 Figure 3. 5 Static light scattering setup (Mays et al. 2011) 3. 2 .3 Head Data System Head loss is measured across the pressure ports on the flow cell. Tubing fro m the ports are routed into Vali dyne (Northridge, CA) transducers. Vali dyne software then logs the data. Head loss is measured for four distinct regions: inlet, middle, and outlet region of the flow cell, and one overall head loss measurement from the top to bottom of the flow cell manifold. 3.3 Porous Media and Index Matched F luid For static light scattering to work, the porous media in the experiments required a high degree of transparency. In order to achieve media invisibility, the media grains had to have the same index of refraction as the fluid. Nafion, a synthetic pol ymer developed by Walther Grot of DuPont and used as a membrane for a variety of chemical processes, was found to be a good porous media candidate. Nafion is clear when hydrated, and is somewhat rigid making it a good surrogate for soil. As deciphered b y Adam Kan old, a solution of 42 % 2 Propanol (isopropyl alcohol or IPA ) and 58% deionised water has the same index of refraction as the Nafion. The Nafion used i n the experiment was 16 35 mesh and the IPA/H 2 O mixture has a dynamic viscosity of 0.0027478 (Pang et al. 2007).

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16 3.4 Colloids and Aggregation The colloids used in the experiments were carboxyl ate modified poly styrene microspheres, made by Se radyn (Thermo Fisher, Indianapolis, IN) The spheres had a uniform di ameter of 106 nm and were stabilized with carboxylate In order to initiate aggregation, the microspheres were exposed to magnesium chloride. For the experiments, varying salt concentrations were used. 3.5 Other Measurements 3.5.1 Specific Deposit It was necessary to know the t ime depende nt concentration of colloid deposits at specific locations in the flow cell. It was necessary for these specific deposit measurements to be made in a non destructive manner, in real time. Unfortunately, there was no known method to accomplish this. So a technique was developed using the SLS setup to measure scattered light intensity at a position independent of dep osit morphology. Refer to A ppendix B to see a full explanation of the technique. The specific deposit measurements taken from th is technique have proven to be repeatable Triplicate scans of unique samples were in accord at lower concentrations. At higher concentrations, values are not as accurate, but still within reasonable tolerances for error. 3.5.2 Porosity The Nafion used in the experiment was 16 35 mesh when dry. However, hydration of Nafion approximately doubles the volume. Furthermore, in order to limit porous media compression during colloid deposition, enough Nafion was added to the flow cell to be in slight compression. Salinity also effects the swelling potential of the Nafion and ionic strength is a variable for experimental runs. For these reasons, the porosity had to be measured in the flow cell for each salt concentration used in the experiment A technique was developed which injected vegetable oil into the void space. The volume of oil was then divided by the total flow cell volume to find the poros ity.

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17 3.5.3 Critical Coagulation Concentration In order to know what salt concentrations t o use for aggregation, it was necessary to find the critical coagulation concentration, the salt concentration at which aggregation starts when increasing salt concentration For critical coagulation concentration determination, varying amounts of MgCl 2 w ere added to the isopropanol and water solution with the microspheres. The salt concentration which caused aggregate settling in a reasonable amount of time was found to be between 1 and 2 mM 3.5.4 Collection and Analysis of Rifle Field Samples In ord er to see the efficacy of laboratory results, it was useful to analyze water samples from the field. There was an opportunity to sample from the DOE Old Rifle field site in Rifle Colorado. With the help of Ken Williams, the site director, eight samples w ere collected from four different wells. Samples were collected at a higher flow rate, then collected with a flow rate of zero. Measurements for temperature and specific conductance were made at the field site. Samples were transported back to the lab in de aired vessels inside of a cooler. At the lab the concentration of colloids was determined by weighing the material left on a 0.2 micron filter. Batch samples were then prepared and scanned using the SLS apparatus. A comparison could now be made between results from lab experiments and field samples. 3.6 Running the Experiments Solutions were prepared and glassware was thoroughly washed in a caustic detergent, then rinsed with deionized water in advance of experiments. The appropriate amount of dry Nafion was added to the flow cell and then hydrated with IPA/H 2 O solution. The Nafion was allowed to hydrate over night with a constant flow of fresh solution. The next day, the flow cell was hook ed u p to pre calibrated transducers, flow was initiated at the target flow rate with no colloids, and equilibrium was checked. Equilibrium was assumed when the hydraulic conductivity was stable, this ensured that the Nafion was not swelling or compressing Next the SLS bench is calibrated by aligning the laser and flow column The flow cell undergoes a blank scan with no colloids present, to be used in later

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18 calculations. Deposition flow (flow with colloids) is then started, along with a stopwatch and data logging. Scans are performed at different flow cell positions through the duration of deposition flow. Flow is then stopped, and all regions of the flow cell are once again scanned. A clear flow (flow with no colloids) is started and more scans are performed. 3.7 Data Analysis 3.7.1 Fractal Dimension For fractal dimension measurements, the scattering intensity verses scattering wave vector values are plotted on a log the fractal dimension (Sorensen 2001) Other points to note on the plot are at the beginning and end of the linear region. As seen in the following figur e, radius of gyration (R g ) and individual colloid radius (r) can also be found in the IQ plot. Figure 3.6 IQ plot for determination of fractal dimension (modified from Sorensen 2001) 1/R g 1/ r

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19 Later in the data analysis, it was found that radius of gyration might be a key parameter for consideration. Unfortunately, the radius of gyration for aggregates in the experiment were found at a very low scattering angle, which could not be measured using our apparatus. Instead, radius of gyration was calculated by u sing the measured fractal dimension and specific deposit. In order to make this calculations some very big assumptions were necessary. First, it was assumed that there would be one aggregate per pore space. Next, the number of pore spaces per cell was e stimated by counting Nafion grains. There is a large amount of error associated with these assumptions, thus radius of gyration measurements are not exact. 3.7.2 Data Reduction There were multiple data streams for each experiment. Using Microso ft Exce l, all data were combined into spreadsheets for consideration. Plots were then created in order to check the validity of results and find possible correlations. Correlations were supported by R 2 value and by comparison of trend line slope error associate d with the 95% confidence interval.

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20 4. S u m m a r y o f R e s u l t s 4.1 Critical Coagulation Concentration and Porosity Critical coagulation concentration, or the minimum salt concentration at which colloids form aggregates within a reasonable amount of t ime (less than 5 minutes) was determined to be approximately 2 mM for magnesium chloride with the polystyrene micro spheres used for the experiment. For 6.5 grams of Nafion in the flow cell, porosity for various concentrations of MgCl 2 are summarized in T able 4.1. Table 4.1 Porosity at various ionic concentration Ionic Concentration MgCl 2 (mM) Ionic Strength ( m M) Porosity 1 3 0.05 2 6 0.11 4 12 0.22 8 24 0.26 16 48 0.26 4.2 Individual Samples A total of 23 flow cell samples were successfully analysed, with a total of 169 SLS scans. While carrying out the experiment on individual samples, it became evident that certain reoccurring behaviours were exhibited during each run. As an example, results from scans on s ample 2013_01_ 002_A will be presented here. For information on other samples, refer to A ppendix A For this sampl e, influent flow rate was 10. 34 mL /min, with an ionic concentration of 2 mM MgCl 2 and an influent colloid concentration of 100 ppm. S LS s cans were conduc ted at three flow cell positions: inlet, mid, and outlet regions during influent flow. Intensity, I, versus scattering wave vector, Q, data

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21 was collected for each scan and then analysed using the IQ plot. Notice that different flow types are contained in the IQ plot. The first two scans are during colloid deposition, then one scan was performed while flow was stopped, and finally one scan after a colloid free (clear) solution flow. Figure 4.1 IQ plot for mid dle region Figure 4.2 Linear region of IQ plot with slope equal to fractal dimension Head loss and specific deposit data were collected simultaneously with the SLS scans. Notice that head loss increases during colloid deposition flow, indicating clogging. Furthermore, specific 1.00E 09 1.00E 08 1.00E 07 1.00E 06 1.00E 05 0.0001 0.001 0.01 0.1 Intensity I" (mV) Q (nm^ 1) I" vs Q, Middle Region 155.1 ml Eluded 315.4 ml Eluded 377.41 ml Eluded, No Flow 782.4 ml Clear Soln. Eluded y = 1E 12x 2.044 R = 0.9952 y = 1E 10x 1.62 R = 0.9841 y = 2E 09x 1.261 R = 0.9608 y = 1E 10x 1.587 R = 0.9854 1.00E 10 1.00E 09 1.00E 08 1.00E 07 1.00E 06 1.00E 05 0.001 0.01 0.1 Intensity I" (mV) Q (nm^ 1) I" vs Q, Mid Region 155.1 ml Eluted 315.4 ml Eluted 377.41 ml Eluted, No Flow 782.4 ml Clear Soln. Eluted

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22 deposit also incr eases as deposition flow continues. For this sample deposition flow was stopped at approximately 400 mL eluted, then clear solution was eluted for the remainder of data collection. During the clear flow, head loss and specific deposit both decrease with time. Note, normalized head loss, dH/dHo, does not usually dip below 1 for most samples. The pulse at 900ml eluted indicates a momentary clog in the inlet region. Figure 4.3 Head loss data during deposition and clear flow Figure 4 .4 Specific deposit data

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23 One of the more interesting results of the individual scans was the evolution of fractal dimension with time. For all samples, fractal dimension would decrease as deposition flow commenced, then increase as clear flow was eluted Figure 4.5 Fractal dimension during deposition and clear flow After performing analysis on all of the samples, the data could be compiled. Th e following plots show all of the data, excluding only scans which did not meet minimum quality assurance cr iteria. These plots show general trends without considering the effects of multiple variables. The other variables are taken into account in the results of the next section. Trend lines are provided for plots with trend line slopes higher than the 95% c onfidence interval, though correlations for unsorted data were relatively weak.

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24 Figure 4.6 Fractal dimension versus normalized hydraulic conductivity Figure 4.7 Fractal dimension versus pore flow velocity y = 1.4832x + 0.4316 R = 0.2268 0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 0 0.2 0.4 0.6 0.8 1 1.2 Fractal Dimension K/Ko 0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 0 500 1000 1500 2000 2500 3000 3500 Fractal Dimension Pore Flow Velocity (m/day)

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25 Figure 4.8 Fractal d imension versus ionic strength Figure 4.9 Fractal dimension versus pore volumes eluted 0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 0 0.01 0.02 0.03 0.04 0.05 0.06 Fractal Dimension Ionic Strength (M) y = 0.0067x + 1.9077 R = 0.083 0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 0 20 40 60 80 100 120 Fractal Dimension Pore Volumes Eluted

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26 Figure 4.10 Fractal dimension versus specific deposit Figure 4.11 Reynolds number versus fractal dimension y = 0.004x + 2.1147 R = 0.6035 0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 0 50 100 150 200 250 300 350 400 450 500 Fractal Dimension Specific Deposit (ppm) 0.01 0.1 1 10 0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 Reynold's Number Fractal Dimension

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27 Figure 4.12 Normalized hydraulic conductivity versus specific deposit The preceding shotgun plots of data show some overall trends, but many correlations were weak since R 2 values were typically below 0.5. However, the observed trends do indicate a link between low fractal dimension and clogging as well as high specific deposi t and clogging. Interestingly, for this unfiltered data there seemed to be little effect on fractal dimension from ionic concentration or pore flow velocity. Samples collected from the Old Rifle field site were also successfully measured for ionic stren gth and scanned using the SLS bench. It is note worthy that the fractal dimension of aggregates from the Rifle site are of similar magnitude to aggregates produced in the lab. Also well G51 was severely clogged Well G51 samples exhibited low fractal d imension and high specific deposit which would indicate clogging according to lab data Rifle samples were scanned with the SLS apparatus twice, once before repeated inversion and once after. y = 0.001x + 0.9219 R = 0.4052 0 0.2 0.4 0.6 0.8 1 1.2 0 50 100 150 200 250 300 350 400 450 500 K/Ko Specific Deposit (ppm)

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28 Figure 4.13 Fract al dimension versus flow rate, R ifle sampl es Figure 4.14 Fractal dimension versus ionic strength, Rifle samples Figure 4.1 5 Fractal dimension versus pore fluid colloid concentration 1.4 1.6 1.8 2 2.2 2.4 2.6 0 200 400 600 800 1000 Fractal Dimension Flowrate (ml/min) Injection Well CD03 Injection Well G51 Monitor Well LR01 Monitor Well FP101 1.4 1.6 1.8 2 2.2 2.4 2.6 0.02 0.03 0.04 0.05 0.06 Fractal Dimension Ionic Strength (M) Injection Well CD03 Injection Well G51 Monitor Well LR01 Monitor Well FP101 1.4 1.6 1.8 2 2.2 2.4 2.6 0 5 10 15 20 Fractal Dimension Concentration (ppm) Injection Well CD03 Injection Well G51 Monitor Well LR01 Monitor Well FP101

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29 4.3 Sample Sets Sample sets consist of data that have been grouped or removed in order to eliminate ancillary variables. First for quality assurance individual scans in which the straight transmission factor was less than or equal to 0.1% were removed since this was the maximum colloid deposition for which the SLS apparatus could take dependable readings. Nex t, sample runs in which the Nafion did not hit equilibrium were removed since this would produce inaccurate head data probably due to changing porosity The remaining data was grouped by flow cell position, pore flow velocity, and flow type (colloid depo sition, no flow, or clear flow). The clear flow groups seemed to exhibit different characteristics which made sense due to the different flow regime. However, deposit flow and no flow data were in agreement and thus were combined. The plots were usually left with three or fewer points. However the data appear very linear, with trend line R 2 values around 0.9 and significant correlation with consideration of the 95% confidence interval. Importantly, all the data groups show the same trends with similar accuracy. The plots shown in figures 16 through 2 1 are for the outlet region, pore velocity of 1197 m/day, ionic strength of 0.006 M, and exclude the clear flow regime. Figure 4.16 Fractal dimension versus specific deposit y = 0.0099x + 2.3187 R = 0.9931 1.0 1.2 1.4 1.6 1.8 2.0 2.2 2.4 0 10 20 30 40 50 60 70 Fractal Dimension Concentration (ppm)

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30 Figure 4.17 Fractal dimens ion versus normalized hydraulic conductivity Figure 4.18 Normalized hydraulic conductivity versus specific deposit Figure 4.19 Normalized hydraulic conductivity versus pore volumes eluted y = 4.0061x 1.7471 R = 0.9909 1.0 1.2 1.4 1.6 1.8 2.0 2.2 2.4 0.86 0.88 0.9 0.92 0.94 0.96 0.98 1 1.02 Fractal Dimension K/Ko y = 0.0025x + 1.0148 R = 0.9998 0.86 0.88 0.9 0.92 0.94 0.96 0.98 1 1.02 0 10 20 30 40 50 60 70 K/Ko Concentration (ppm) y = 0.001x + 1.066 R = 0.982 0.85 0.9 0.95 1 1.05 0 50 100 150 200 250 300 K/Ko Pore Volumes Eluted

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31 Figure 4.20 Fractal dimension versus pore volumes eluted Figure 4.21 Specific deposit versus pore volumes eluted The preceding data is representative of most pore velocity/cell position combinations. The plots clearly indicate a dependence on specific deposit and fractal dimension for hydraulic conductivity. Importantly, there is also a clear connection between fractal dimension and specific deposit. A summary for all the groups was necessary in order to see reoccurring trends. Plots grouped by the previous criteria were then combined by pore flow velocity Only data sets with at least three points were considered. Note that the 3000 m/day pore flow velocity data included in the fo llowing plots is for a salt concentration below the critical coagulation concentration, so the colloids did not aggregate. y = 0.0027x + 2.5151 R = 0.9486 1.0 1.2 1.4 1.6 1.8 2.0 2.2 2.4 0 50 100 150 200 250 300 Fractal Dimension Pore Volumes Eluted y = 0.2741x 20.44 R = 0.979 0 20 40 60 80 0 50 100 150 200 250 300 Specific Deposit (ppm) Pore Volumes Eluted

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32 Figure s 4.22 a c Fractal dimen sion versus pore volumes eluted by pore flow velocity. As shown in figures 4.23a c, correlation between fractal dimension and pore volumes eluted is excellent for most data sets. There is a slight variation depending on which region is being scanned, but behaviour is similar for sets with common ionic strength Of note is the different slope for the 3000 m L /day data set, which is the only data set for which I
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33 Figure 4.23 a c Specific dep osit versus pore volumes eluted by pore flow velocity As shown in figures 4.24a c, as expected, specific deposit increases with pore volumes eluted and decreases toward the outlet. Correlation is once again excellent for all data sets. Note 3000m/day, which exhibited no accumulation due to lack of aggregation. 0 50 100 150 200 250 300 0 200 400 600 800 Specific Deposit (ppm) Pore Volumes Eluted 74 m/day 569 m/day 588 m/day 1439 m/day 3000 m/day 0 50 100 150 200 250 300 0 200 400 600 800 Specific Deposit (ppm) Pore Volumes Eluted 74 m/day 569 m/day 1197 m/day 1439 m/day 3000 m/day 0 50 100 150 200 250 300 0 200 400 600 800 Specific Deposit (ppm) Pore Volumes Eluted 74 m/day 138 m/day 569 m/day 1197 m/day 1439 m/day (a) Inlet Region (b) Middle Region Region (c) Outlet Region

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34 Figure 4. 24 a c Fractal dimension versus specific deposit by pore flow velocity. For fractal dimension versus specific deposit a correlation between different pore flow velocities starts to become apparent, especially toward the inlet. This indicates that specific deposit and fractal dimension are connected. The connection starts to break down near the outlet, possibly indicating that straining could have an effect. 0.5 1 1.5 2 2.5 0 50 100 150 200 250 300 Fractal Dimension Specific Deposit (ppm) 74 m/day 569 m/day 588 m/day 1439 m/day 3000 m/day 0.5 1 1.5 2 2.5 0 50 100 150 200 250 300 Fractal Dimension Specific Deposit (ppm) 74 m/day 569 m/day 1197 m/day 1439 m/day 3000 m/day 0.5 1 1.5 2 2.5 0 50 100 150 200 250 300 Fractal Dimension Specific Deposit (ppm) 74 m/day 138 m/day 569 m/day 1197 m/day 1439 m/day (a) Inlet Region (b) Middle Region Region (c) Outlet Region

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35 F igure 4.25 a c Normalized hydraulic conductivity versus fractal dimension by pore flow velocity. For normalized hydraulic conductivity versus fractal dimension, correlations are good with the exception of 1439m/day. However behaviour is quite different among data sets. Note tha t 3000m/day shows no drop in hydraulic conductivity due to the lack of accumulation. 0.4 0.5 0.6 0.7 0.8 0.9 1 1.1 0.5 1 1.5 2 2.5 K/Ko Fractal Dimension 74 m/day 569 m/day 588 m/day 1439 m/day 3000 m/day 0.4 0.5 0.6 0.7 0.8 0.9 1 1.1 0.5 1 1.5 2 2.5 K/Ko Fractal Dimension 74 m/day 569 m/day 1197 m/day 1439 m/day 3000 m/day 0.4 0.5 0.6 0.7 0.8 0.9 1 1.1 0.5 1 1.5 2 2.5 K/Ko Fractal Dimension 74 m/day 138 m/day 569 m/day 1197 m/day 1439 m/day (a) Inlet Region (b) Middle Region Region (c) Outlet Region

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36 Figure 4. 26 a c Normalized hydraulic conductivity versus specific deposit by pore flow velocity. Normalized hydraulic conductivity versus specific deposit shows good correlation for each data set. As expected, clogging increases with an increase in specific deposit. Behaviour seems to be very dependent on scan region. 0.4 0.5 0.6 0.7 0.8 0.9 1 1.1 0 50 100 150 200 250 300 K/Ko Specific Deposit (ppm) 74 m/day 569 m/day 588 m/day 1439 m/day 3000 m/day 0.4 0.5 0.6 0.7 0.8 0.9 1 1.1 0 50 100 150 200 250 300 K/Ko Specific Deposit (ppm) 74 m/day 569 m/day 1197 m/day 1439 m/day 3000 m/day 0.4 0.5 0.6 0.7 0.8 0.9 1 1.1 0 50 100 150 200 250 300 K/Ko Specific Deposit (ppm) 74 m/day 138 m/day 569 m/day 1197 m/day 1439 m/day (a) Inlet Region (b) Middle Region Region (c) Outlet Region

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37 Figure 4. 27 a c Normalized hydraulic conductivity versus radius of gyration by pore flow velocity. Note that radius of gyration was calculated using assumptions stated in section 3.7.1, and may be very inaccu rate. However, the R g should give a good estimate for purposes of investigating behaviour. Radius of gyration accounts for specific deposit and fractal dimension, so it makes sense that correlations are exhibited. 1439m/day once again shows poor correla tion. 0.4 0.5 0.6 0.7 0.8 0.9 1 1.1 1.E 05 1.E 04 1.E 03 1.E 02 1.E 01 1.E+00 1.E+01 1.E+02 1.E+03 K/Ko Radius of Gyration (m) 74 m/day 569 m/day 588 m/day 1439 m/day 3000 m/day 0.4 0.5 0.6 0.7 0.8 0.9 1 1.1 1.E 05 1.E 04 1.E 03 1.E 02 1.E 01 1.E+00 1.E+01 1.E+02 1.E+03 K/Ko Radius of Gyration (m) 74 m/day 569 m/day 1197 m/day 1439 m/day 3000 m/day 0.4 0.5 0.6 0.7 0.8 0.9 1 1.1 1.E 05 1.E 04 1.E 03 1.E 02 1.E 01 1.E+00 1.E+01 1.E+02 1.E+03 K/Ko Radius of Gyration (m) 74 m/day 138 m/day 569 m/day 1197 m/day 1439 m/day (a) Inlet Region (b) Middle Region Region (c) Outlet Region

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38 After considering the grouped data sets, it seemed likely th at specific dep osit and fractal dimension work in tandem to influence clogging. When specific deposit increased, fractal dimension decreased, and clogging became more pronounced. It follo ws that radius of gyration, which accounts for specific deposit and fractal dimension could be the key to understanding clogging. Data was considered at all flow cell locations for the last round of investigation. Keep in mind that radius of gyration wa s calculated (not measured) with assumptions. Figure 4.28 Fractal dimension versus specific deposit, all regions, by pore flow velocity. For fractal dimension versus specific deposit, it would appear that a clear yet somewhat noisy pattern emerges. Indicating that there is a non linear relationship between the two, seemingly independent of pore flow velocity (which due to the effects of salt on Nafion, is also independent of porosity). Normalized hydraulic con ductivity versus radius of gyration for all regions i s shown in Figures 4.30 through 4.37 Excellen t correlation was found for five out of eight pore flow velocities considered While trend line slopes and magnitudes were similar for some of the data set s, an overall correlation unifying all data was still not clear. 0 0.5 1 1.5 2 2.5 3 0 50 100 150 200 250 300 350 Fractal Dimension Specific Deposit (ppm) Fractal Dimension vs Specific Deposit 74 m/day 0.049 M 138 m/day 0.049 M 292 m/day 0.048 M 569 m/day 0.048 M 588 m/day 0.024 M 691 m/day 0.012 M 1197 m/day 0.006 M 1439 m/day 0.006 M 3000 m/day 0.003 M

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39 Figure 4.29 Normalized hydraulic conductivity versus radius of gyration 74 m/day pore flow velocity, 0.049M ionic strength Figure 4.30 Normalized hydraulic conductivity versus radius of gyration, 138 m/day pore flow velocity, 0.049M ionic strength. y = 0.046ln(x) + 0.488 R = 0.845 0.4 0.5 0.6 0.7 0.8 0.9 1 1.1 1.E 05 1.E 04 1.E 03 1.E 02 1.E 01 1.E+00 1.E+01 K/Ko Radius of Gyration (m) K/Ko vs Radius of Gyration 74 m/day 0.049 M y = 0.040ln(x) + 0.574 R = 0.953 0.4 0.5 0.6 0.7 0.8 0.9 1 1.1 1.E 05 1.E 04 1.E 03 1.E 02 1.E 01 1.E+00 1.E+01 K/Ko Radius of Gyration (m) K/Ko vs Radius of Gyration 138 m/day 0.049 M

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40 Figure 4.31 Normalized hydraulic conductivity versus radius of gyration, 292 m/day pore flow velocity, 0.048 M ionic strength. Figure 4.32 Norma lized hydraulic conductivity versus radius of gyration, 569 m/day pore flow velocity, 0.048M ionic strength. y = 0.023ln(x) + 0.789 R = 0.922 0.4 0.5 0.6 0.7 0.8 0.9 1 1.1 1.E 05 1.E 04 1.E 03 1.E 02 1.E 01 1.E+00 1.E+01 K/Ko Radius of Gyration (m) K/Ko vs Radius of Gyration 292 m/day 0.048 M 0.4 0.5 0.6 0.7 0.8 0.9 1 1.1 1.E 05 1.E 04 1.E 03 1.E 02 1.E 01 1.E+00 1.E+01 K/Ko Radius of Gyration (m) K/Ko vs Radius of Gyration 569 m/day 0.048 M

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41 Figure 4.33 Normalized hydraulic conductivity versus radius of gyration, 588 m/day pore flow velocity, 0.024M ionic strength. Figure 4.34 No rmalized hydraulic conductivity versus radius of gyration, 691 m/day pore flow velocity, 0.012M ionic strength. y = 0.029ln(x) + 0.772 R = 0.977 0.4 0.5 0.6 0.7 0.8 0.9 1 1.1 1.E 05 1.E 04 1.E 03 1.E 02 1.E 01 1.E+00 1.E+01 K/Ko Radius of Gyration (m) K/Ko vs Radius of Gyration 588 m/day 0.024 M 0.4 0.5 0.6 0.7 0.8 0.9 1 1.1 1.E 05 1.E 04 1.E 03 1.E 02 1.E 01 1.E+00 1.E+01 K/Ko Radius of Gyration (m) K/Ko vs Radius of Gyration 691 m/day 0.012 M

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42 Figure 4.35 Normalized hydraulic conductivity versus radius of gyration, 1197 m/day pore flow velocity, 0.006M ionic strength. Figure 4.36 Normalized hydraulic conductivity versus radius of gyration, 1439 m/day pore flow velocity, 0.006M ionic strength. The preceding results show that flow cell region can perhaps be disregarded when considering hydraulic conductivity versus radius of gyrat ion. It follows that radius of gyration is possibly unaffected by straining effects. y = 0.046ln(x) + 0.576 R = 0.908 0.4 0.5 0.6 0.7 0.8 0.9 1 1.1 1.E 05 1.E 04 1.E 03 1.E 02 1.E 01 1.E+00 1.E+01 K/Ko Radius of Gyration (m) K/Ko vs Radius of Gyration 1197 m/day 0.006M 0.4 0.5 0.6 0.7 0.8 0.9 1 1.1 1.E 05 1.E 04 1.E 03 1.E 02 1.E 01 1.E+00 1.E+01 K/Ko Radius of Gyration (m) K/Ko vs Radius of Gyration 1439 m/day 0.006 M

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43 5. C o n c l u s i o n s a n d D i s c u s s i o n 5.1 Individual Samples The first noteworthy conclusion is that the data supports a reaffirmation that fractal dimension can be measured in a flow cell containing index matched porous media. Judging from the low colloid accumulation and unchanged hydraulic conductivity, solutions with an ionic concentration below one millimolar MgCl 2 do not provide favorable conditions for aggreg ation, colloid deposition, nor clogging. With volume eluted and change in flow regime, the fractal dimension varies. During colloid deposition, fractal dimension decreases as clogging increases, indicating that a lower fractal dimension can be associate d with increased clogging. When a colloid free flow is supplied to the clogged column, fractal dimension once again increases as clogging decreases. Interestingly, some samples showed hydraulic conductivity higher than clean bed conditions, after colloid deposition and clear flows were applied. Important trends were noted when the entirety of data collected was plotted. Significant correlation was apparent from the plots of fractal dimension versus normalized hydraulic conductivity, specific deposit vers us normalized hydraulic conductivity, and fractal dimension versus specific deposit. These findings indicate that fractal dimension and specific deposit might work in tandem with respect to hydraulic conductivity. Also, Reynolds number for all samples fe ll below ten, Samples collected at the Old Rifle field site had fractal dimensions ranging from 1.5 to 2.5. This is a similar to the samples created in the lab, indicating that experimental results could be considered for field conditions. Finally, the sample from well G51 at the Rifle site had higher fractal dimension and colloid concentrations than the other wells sampled. Judging from trends found in la b samples, this well should exhibit more clogging. In fact, well G51 was severely clogged, further supporting conclusions from lab experiments. 5.2 Sample Sets By grouping samples by common variables, excellent correlation was achieved for many of the plots. Specifically, data grouped by pore flow velocity, flow cell region, and flow regime showed R 2 above 0.9 and significant correlation by consideration of 95% confidence interval for fractal dimension versus normalized hydraulic conductivity, specific deposit versus normalized hydraulic conductivity, and fractal dimension versus specific deposit. Combining the plots at various pore flow velocities showed some correlation s There is strong evidence that radius of gyration measurements could be the m issing link which would relate fractal dimension and specific deposit with hydraulic conductivity. Unfortunately, measuring radius of gyration was not possible with the SLS appa ratus used in the experiment 5.3 Overall Conclusions It appears that fractal dimension and specific deposit are connected. Furthermore, these parameters have been shown to have a significant connection to clogging. This connection is shown in the analysis of almost all samples. Further experimentation is necessary to find the c onnection

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44 between fractal dimension and specific deposit and the resulting effect on clogging. Specifically by the use of an SLS setup that can measure radius of gyration. As seen in figure 4.29, there seems to be a non linear relationship between fractal dimension and specific deposit. This finding supplies an interesting insight into the formation of aggregate deposits. The next step here would be to further calibrate the in situ concentration measurement technique developed during this research specifically at higher concentrations. 5.4 Discussion This experiment has yielded compelling results. Fractal dimension does seem to have a significant impact on clogging. When specific deposit is also considered, the effects on permeability are unde niable. It would appear likely that measurement of the radius of gyration could be key to understanding the clogging process. The next step of this research would be to run more lab experiments with an updated SLS apparatus which could measure radius of gyration. New experimental parameters would also be very useful since working with Nafion had some hidden pitfalls which have now been discovered. It is also time to investigate more field samples in order to collect empirical evidence.

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45 REFERENCES measurement of the mass fractal dimension of Interface Science 95, 1 19. Fitts, C. (2002). Groundwater Science. London: Academic Press. U.S. Izkander, Magued. (2010). Modelling with Transparent Soils, 1 st Ed., Springer, Berlin. Scho field Diagram to Explain Environmental Colloid Journal of Natural Resources & Life Sciences Education, Volume 36, 45 52. Mays, D. C. (2010). End Journal of Environmental Engineering, 136(5), 475 480. Funding Request to Office of Biological and Environmental Research, 1 30. Mays, D.C., Cannon, O.T., Kanold, A. scattering resolves colloid structure in index Journal of Colloid and Interface Science, doi:10.1016/j.jcis.2011.06.046. Min, M., Dominik, C. Hovenier, J.W., de Koter, A m Astronomy and Astrophysics, 445, 1005 1014. Mont ranular Media 1 Propanol and 2 Soren Aerosol Science and Technology, 35(2), 648 655.

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46 Appendix A Experimental Data and Results y = 0.0011x + 0.0013 R = 0.2134 0.0002 0 0.0002 0.0004 0.0006 0.0008 0.001 0.0012 0.0014 0.0016 0.0018 0 0.2 0.4 0.6 0.8 1 1.2 Morphology Parameter (ppm^ 1) K/Ko Morphology Parameter vs K/Ko y = 1E 06x + 0.0005 R = 0.0652 0.0002 0 0.0002 0.0004 0.0006 0.0008 0.001 0.0012 0.0014 0.0016 0.0018 0 50 100 150 200 250 300 350 Morphology Parameter (ppm^ 1) Specific Deposit (ppm) Morphology Parameter vs Specific Deposit

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47 0.0002 0 0.0002 0.0004 0.0006 0.0008 0.001 0.0012 0.0014 0.0016 0.0018 0 0.5 1 1.5 2 2.5 3 Morphology Parameter (ppm^ 1) Fractal Dimension Morphology Parameter vs Fractal Dimension 0.4 0.5 0.6 0.7 0.8 0.9 1 1.1 0 0.001 0.002 0.003 0.004 0.005 K/Ko Morphology Parameter K/Ko vs Morphology Parameter 74 m/day 0.049 M 138 m/day 0.049 M 292 m/day 0.048 M 569 m/day 0.048 M 588 m/day 0.024 M 691 m/day 0.012 M 1197 m/day 0.006M 1439 m/day 0.006 M 3000 m/day 0.003 M

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48 Sample ID Flowrate (ml/min) Flow Velocity (m/day) Average Pore Velocity (m/day) Ionic Conc (mM) Ionic Strength (M) Salt Type Nafion Size (mesh) 2012_03_001_A_6 0.71 9.0 0 60 100 2012_03_001_A_7 0.65 8.3 0 60 100 2012_03_001_A_11 0.63 8.0 0 60 100 2012_04_002_A_15 6.9 87.9 100 Ca(NO3)2 16 35 2012_05_001_A_12 7 89.1 100 Ca(NO3)2 16 35 2012_05_001_A_15 7 89.1 100 Ca(NO3)2 16 35 2012_05_001_A_21 7 89.1 100 Ca(NO3)2 16 35 2012_05_001_A_27 7 89.1 100 Ca(NO3)2 16 35 2012_06_001_A_12 3.45 43.9 100 Ca(NO3)2 16 35 2012_06_001_A_18 3.5 44.6 100 Ca(NO3)2 16 35 2012_06_001_A_24 3.5 44.6 100 Ca(NO3)2 16 35 2012_06_001_A_30 3.45 43.9 100 Ca(NO3)2 16 35 2012_06_002_A_24 1.83 23.3 100 Ca(NO3)2 16 35 2012_06_002_A_27 1.84 23.4 100 Ca(NO3)2 16 35 2012_06_002_A_30 1.7 21.6 100 Ca(NO3)2 16 35 2012_06_003_A_15 1.95 24.8 100 Ca(NO3)2 16 35 2012_06_003_A_21 1.95 24.8 100 Ca(NO3)2 16 35 2013_01_002_A_42 10.34 131.7 1197 2 0.006 MgCl2 16 35 2013_01_002_A_48 10.34 131.7 1197 2 0.006 MgCl2 16 35 2013_01_002_A_54 10.34 131.7 1197 2 0.006 MgCl2 16 35 2013_01_002_A_88 10.34 131.7 1197 2 0.006 MgCl2 16 35 2013_01_002_A_41 10.34 131.7 1197 2 0.006 MgCl2 16 35 2013_01_002_A_47 10.34 131.7 1197 2 0.006 MgCl2 16 35 2013_01_002_A_53 10.34 131.7 1197 2 0.006 MgCl2 16 35 2013_01_002_A_82 10.34 131.7 1197 2 0.006 MgCl2 16 35 2013_01_002_A_40 10.34 131.7 1197 2 0.006 MgCl2 16 35 2013_01_002_A_46 10.34 131.7 1197 2 0.006 MgCl2 16 35 2013_01_002_A_52 10.34 131.7 1197 2 0.006 MgCl2 16 35 2013_01_002_A_75 10.34 131.7 1197 2 0.006 MgCl2 16 35 2013_02_001_A_47 5.21 66.3 603 2 0.006 MgCl2 16 35 2013_02_001_A_56 5.21 66.3 603 2 0.006 MgCl2 16 35 2013_02_001_A_62 5.21 66.3 603 2 0.006 MgCl2 16 35 2013_02_002_A_20 5.4 68.8 659 1.81 0.00543 MgCl2 16 35 2013_02_002_A_26 5.4 68.8 659 1.81 0.00543 MgCl2 16 35 2013_02_002_A_47 5.4 68.8 659 1.81 0.00543 MgCl2 16 35 2013_02_002_A_62 5.3 67.5 647 1.81 0.00543 MgCl2 16 35 2013_02_002_A_22 5.4 68.8 659 1.81 0.00543 MgCl2 16 35 2013_02_002_A_28 5.4 68.8 659 1.81 0.00543 MgCl2 16 35

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49 2013_02_002_A_50 5.4 68.8 659 1.81 0.00543 MgCl2 16 35 Sample ID Flowrate (ml/min) Flow Velocity (m/day) Average Pore Velocity (m/day) Ionic Conc (mM) Ionic Strength (M) Salt Type Nafion Size (mesh) 2013_02_002_A_64 5.3 67.5 647 1.81 0.00543 MgCl2 16 35 2013_02_002_A_24 5.4 68.8 659 1.81 0.00543 MgCl2 16 35 2013_02_002_A_30 5.4 68.8 659 1.81 0.00543 MgCl2 16 35 2013_02_002_A_53 5.4 68.8 659 1.81 0.00543 MgCl2 16 35 2013_02_002_A_66 5.3 67.5 647 1.81 0.00543 MgCl2 16 35 2013_03_001_A_26 5.72 72.8 671 1.95 0.00585 MgCl2 16 35 2013_03_001_A_32 5.72 72.8 671 1.95 0.00585 MgCl2 16 35 2013_03_001_A_47 5.72 72.8 671 1.95 0.00585 MgCl2 16 35 2013_03_001_A_62 5.67 72.2 665 1.95 0.00585 MgCl2 16 35 2013_03_001_A_28 5.72 72.8 671 1.95 0.00585 MgCl2 16 35 2013_03_001_A_34 5.72 72.8 671 1.95 0.00585 MgCl2 16 35 2013_03_001_A_50 5.72 72.8 671 1.95 0.00585 MgCl2 16 35 2013_03_001_A_64 5.67 72.2 665 1.95 0.00585 MgCl2 16 35 2013_03_001_A_36 5.72 72.8 671 1.95 0.00585 MgCl2 16 35 2013_03_001_A_53 5.72 72.8 671 1.95 0.00585 MgCl2 16 35 2013_03_001_A_66 5.67 72.2 665 1.95 0.00585 MgCl2 16 35 2013_03_008_A_20 11.62 148.0 569 16.03 0.04809 MgCl2 16 35 2013_03_008_A_26 11.62 148.0 569 16.03 0.04809 MgCl2 16 35 2013_03_008_A_47 11.62 148.0 569 16.03 0.04809 MgCl2 16 35 2013_03_008_A_62 11.76 149.7 576 16.03 0.04809 MgCl2 16 35 2013_03_008_A_22 11.62 148.0 569 16.03 0.04809 MgCl2 16 35 2013_03_008_A_28 11.62 148.0 569 16.03 0.04809 MgCl2 16 35 2013_03_008_A_50 11.62 148.0 569 16.03 0.04809 MgCl2 16 35 2013_03_008_A_64 11.76 149.7 576 16.03 0.04809 MgCl2 16 35 2013_03_008_A_24 11.62 148.0 569 16.03 0.04809 MgCl2 16 35 2013_03_008_A_30 11.62 148.0 569 16.03 0.04809 MgCl2 16 35 2013_03_008_A_53 11.62 148.0 569 16.03 0.04809 MgCl2 16 35 2013_03_008_A_66 11.76 149.7 576 16.03 0.04809 MgCl2 16 35 2013_04_001_A_20 5.97 76.0 292 16.01 0.04803 MgCl2 16 35 2013_04_001_A_26 5.97 76.0 292 16.01 0.04803 MgCl2 16 35 2013_04_001_A_22 5.97 76.0 292 16.01 0.04803 MgCl2 16 35 2013_04_001_A_24 5.97 76.0 292 16.01 0.04803 MgCl2 16 35 2013_04_001_A_30 5.97 76.0 292 16.01 0.04803 MgCl2 16 35 2013_04_018_A_20 2.82 35.9 138 16.23 0.04869 MgCl2 16 35 2013_04_018_A_26 2.82 35.9 138 16.23 0.04869 MgCl2 16 35 2013_04_018_A_32 2.82 35.9 138 16.23 0.04869 MgCl2 16 35 2013_04_018_A_22 2.82 35.9 138 16.23 0.04869 MgCl2 16 35

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50 2013_04_018_A_28 2.82 35.9 138 16.23 0.04869 MgCl2 16 35 2013_04_018_A_50 2.82 35.9 138 16.23 0.04869 MgCl2 16 35 2013_04_018_A_64 2.82 35.9 138 16.23 0.04869 MgCl2 16 35 2013_04_018_A_24 2.82 35.9 138 16.23 0.04869 MgCl2 16 35 Sample ID Flowrate (ml/min) Flow Velocity (m/day) Average Pore Velocity (m/day) Ionic Conc (mM) Ionic Strength (M) Salt Type Nafion Size (mesh) 2013_04_018_A_30 2.82 35.9 138 16.23 0.04869 MgCl2 16 35 2013_04_018_A_53 2.82 35.9 138 16.23 0.04869 MgCl2 16 35 2013_04_018_A_66 2.82 35.9 138 16.23 0.04869 MgCl2 16 35 2013_06_002_A_20 12 152.8 588 8.027 0.024081 MgCl2 16 35 2013_06_002_A_26 12 152.8 588 8.027 0.024081 MgCl2 16 35 2013_06_002_A_32 12 152.8 588 8.027 0.024081 MgCl2 16 35 2013_06_002_A_22 12 152.8 588 8.027 0.024081 MgCl2 16 35 2013_06_002_A_28 12 152.8 588 8.027 0.024081 MgCl2 16 35 2013_06_002_A_50 12 152.8 588 8.027 0.024081 MgCl2 16 35 2013_06_002_A_64 12 152.8 588 8.027 0.024081 MgCl2 16 35 2013_06_002_A_24 12 152.8 588 8.027 0.024081 MgCl2 16 35 2013_06_002_A_30 12 152.8 588 8.027 0.024081 MgCl2 16 35 2013_06_002_A_53 12 152.8 588 8.027 0.024081 MgCl2 16 35 2013_06_002_A_66 12 152.8 588 8.027 0.024081 MgCl2 16 35 2013_08_001_A_20 11.86 151.0 690 3.953 0.011859 MgCl2 16 35 2013_08_001_A_26 11.86 151.0 690 3.953 0.011859 MgCl2 16 35 2013_08_001_A_47 11.86 151.0 690 3.953 0.011859 MgCl2 16 35 2013_08_001_A_62 11.86 151.0 690 3.953 0.011859 MgCl2 16 35 2013_08_001_A_22 11.86 151.0 690 3.953 0.011859 MgCl2 16 35 2013_08_001_A_28 11.86 151.0 690 3.953 0.011859 MgCl2 16 35 2013_08_001_A_50 11.86 151.0 690 3.953 0.011859 MgCl2 16 35 2013_08_001_A_64 11.86 151.0 690 3.953 0.011859 MgCl2 16 35 2013_08_001_A_24 11.86 151.0 690 3.953 0.011859 MgCl2 16 35 2013_08_001_A_30 11.86 151.0 690 3.953 0.011859 MgCl2 16 35 2013_08_001_A_53 11.86 151.0 690 3.953 0.011859 MgCl2 16 35 2013_08_001_A_66 11.86 151.0 690 3.953 0.011859 MgCl2 16 35 2013_08_002_A_20 12.53 159.5 1439 2.016 0.006048 MgCl2 16 35 2013_08_002_A_26 12.53 159.5 1439 2.016 0.006048 MgCl2 16 35 2013_08_002_A_47 12.53 159.5 1439 2.016 0.006048 MgCl2 16 35 2013_08_002_A_62 12.53 159.5 1439 2.016 0.006048 MgCl2 16 35 2013_08_002_A_22 12.53 159.5 1439 2.016 0.006048 MgCl2 16 35 2013_08_002_A_28 12.53 159.5 1439 2.016 0.006048 MgCl2 16 35 2013_08_002_A_50 12.53 159.5 1439 2.016 0.006048 MgCl2 16 35 2013_08_002_A_64 12.53 159.5 1439 2.016 0.006048 MgCl2 16 35

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51 2013_08_002_A_24 12.53 159.5 1439 2.016 0.006048 MgCl2 16 35 2013_08_002_A_30 12.53 159.5 1439 2.016 0.006048 MgCl2 16 35 2013_08_002_A_53 12.53 159.5 1439 2.016 0.006048 MgCl2 16 35 2013_08_002_A_66 12.53 159.5 1439 2.016 0.006048 MgCl2 16 35 2013_08_003_A_20 11.63 148.1 1.011 0.003033 MgCl2 16 35 2013_08_003_A_26 11.63 148.1 1.011 0.003033 MgCl2 16 35 2013_08_003_A_47 11.63 148.1 1.011 0.003033 MgCl2 16 35 Sample ID Flowrate (ml/min) Flow Velocity (m/day) Average Pore Velocity (m/day) Ionic Conc (mM) Ionic Strength (M) Salt Type Nafion Size (mesh) 2013_08_003_A_62 11.63 148.1 1.011 0.003033 MgCl2 16 35 2013_08_003_A_22 11.63 148.1 1.011 0.003033 MgCl2 16 35 2013_08_003_A_28 11.63 148.1 1.011 0.003033 MgCl2 16 35 2013_08_003_A_50 11.63 148.1 1.011 0.003033 MgCl2 16 35 2013_08_003_A_64 11.63 148.1 1.011 0.003033 MgCl2 16 35 2013_08_003_A_24 11.63 148.1 1.011 0.003033 MgCl2 16 35 2013_08_003_A_30 11.63 148.1 1.011 0.003033 MgCl2 16 35 2013_08_003_A_53 11.63 148.1 1.011 0.003033 MgCl2 16 35 2013_08_003_A_66 11.63 148.1 1.011 0.003033 MgCl2 16 35 2013_09_001_A_20 11.78 150.0 3000 0.983 0.002949 MgCl2 16 35 2013_09_001_A_26 11.78 150.0 3000 0.983 0.002949 MgCl2 16 35 2013_09_001_A_47 11.78 150.0 3000 0.983 0.002949 MgCl2 16 35 2013_09_001_A_62 11.78 150.0 3000 0.983 0.002949 MgCl2 16 35 2013_09_001_A_22 11.78 150.0 3000 0.983 0.002949 MgCl2 16 35 2013_09_001_A_28 11.78 150.0 3000 0.983 0.002949 MgCl2 16 35 2013_09_001_A_50 11.78 150.0 3000 0.983 0.002949 MgCl2 16 35 2013_09_001_A_64 11.78 150.0 3000 0.983 0.002949 MgCl2 16 35 2013_09_001_A_24 11.78 150.0 3000 0.983 0.002949 MgCl2 16 35 2013_09_001_A_30 11.78 150.0 3000 0.983 0.002949 MgCl2 16 35 2013_09_001_A_53 11.78 150.0 3000 0.983 0.002949 MgCl2 16 35 2013_09_001_A_66 11.78 150.0 3000 0.983 0.002949 MgCl2 16 35 2013_09_002_A_20 1.512 19.3 74 16.254 0.048762 MgCl2 16 35 2013_09_002_A_26 1.512 19.3 74 16.254 0.048762 MgCl2 16 35 2013_09_002_A_47 1.512 19.3 74 16.254 0.048762 MgCl2 16 35 2013_09_002_A_62 1.528 19.5 75 16.254 0.048762 MgCl2 16 35 2013_09_002_A_22 1.512 19.3 74 16.254 0.048762 MgCl2 16 35 2013_09_002_A_28 1.512 19.3 74 16.254 0.048762 MgCl2 16 35 2013_09_002_A_50 1.512 19.3 74 16.254 0.048762 MgCl2 16 35 2013_09_002_A_64 1.528 19.5 75 16.254 0.048762 MgCl2 16 35 2013_09_002_A_24 1.512 19.3 74 16.254 0.048762 MgCl2 16 35 2013_09_002_A_30 1.512 19.3 74 16.254 0.048762 MgCl2 16 35 2013_09_002_A_53 1.512 19.3 74 16.254 0.048762 MgCl2 16 35

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52 2013_09_002_A_66 1.528 19.5 75 16.254 0.048762 MgCl2 16 35 Sample ID Nafion Amount (g) Porosity Inlet Colloid Conc (ppm) Colloid Size (nm) Pore Fluid Colloid Conc. (ppm) Specific Deposit (ppm) Flow Cell Position 2012_03_001_A_6 5.5 125 99 255 2012_03_001_A_7 5.5 125 99 255 2012_03_001_A_11 5.5 125 99 255 2012_04_002_A_15 7 12 99 255 2012_05_001_A_12 7 125 99 255 2012_05_001_A_15 7 125 99 255 2012_05_001_A_21 7 125 99 255 2012_05_001_A_27 7 125 99 255 2012_06_001_A_12 7 125 99 255 2012_06_001_A_18 7 125 99 255 2012_06_001_A_24 7 125 99 255 2012_06_001_A_30 7 125 99 255 2012_06_002_A_24 7 125 99 255 2012_06_002_A_27 7 125 99 255 2012_06_002_A_30 7 125 99 255 2012_06_003_A_15 7 125 99 255 2012_06_003_A_21 7 125 99 255 2013_01_002_A_42 6.5 0.11 125 106 451 50 790 2013_01_002_A_48 6.5 0.11 125 106 1629 179 790 2013_01_002_A_54 6.5 0.11 125 106 1649 181 790 2013_01_002_A_88 6.5 0.11 125 106 1010 111 790 2013_01_002_A_41 6.5 0.11 125 106 117 13 580 2013_01_002_A_47 6.5 0.11 125 106 611 67 580 2013_01_002_A_53 6.5 0.11 125 106 1035 114 580 2013_01_002_A_82 6.5 0.11 125 106 543 60 580 2013_01_002_A_40 6.5 0.11 125 106 52 6 255 2013_01_002_A_46 6.5 0.11 125 106 301 33 255 2013_01_002_A_52 6.5 0.11 125 106 523 58 255 2013_01_002_A_75 6.5 0.11 125 106 403 44 255 2013_02_001_A_47 6.5 0.11 125 106 95 11 790 2013_02_001_A_56 6.5 0.11 125 106 108 12 790 2013_02_001_A_62 6.5 0.11 125 106 181 20 790 2013_02_002_A_20 6.5 0.10 136 106 60 6 790 2013_02_002_A_26 6.5 0.10 136 106 403 42 790 2013_02_002_A_47 6.5 0.10 136 106 1447 151 790

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53 2013_02_002_A_62 6.5 0.10 136 106 1438 150 790 2013_02_002_A_22 6.5 0.10 136 106 152 16 580 2013_02_002_A_28 6.5 0.10 136 106 630 66 580 2013_02_002_A_50 6.5 0.10 136 106 1629 170 580 Sample ID Nafion Amount (g) Porosity Inlet Colloid Conc (ppm) Colloid Size (nm) Pore Fluid Colloid Conc. (ppm) Specific Deposit (ppm) Flow Cell Position 2013_02_002_A_64 6.5 0.1043 136.4 106.0 1669.4 174.1 580 2013_02_002_A_24 6.5 0.1043 136.4 106.0 130.2 13.6 255 2013_02_002_A_30 6.5 0.1 136.4 106.0 445.022706 46.415868 255 2013_02_002_A_53 6.5 0.1 136.4 106.0 1157.50777 120.72806 255 2013_02_002_A_66 6.5 0.1 136.4 106.0 1193.99509 124.53369 255 2013_03_001_A_26 6.5 0.1 127.9 106.0 117.895408 12.791652 790 2013_03_001_A_32 6.5 0.1 127.9 106.0 340.773621 36.973938 790 2013_03_001_A_47 6.5 0.1 127.9 106.0 817.642166 88.714175 790 2013_03_001_A_62 6.5 0.1 127.9 106.0 843.416141 91.510651 790 2013_03_001_A_28 6.5 0.1 127.9 106.0 107.414029 11.654422 580 2013_03_001_A_34 6.5 0.1 127.9 106.0 320.264434 34.748691 580 2013_03_001_A_50 6.5 0.1 127.9 106.0 618.380274 67.09426 580 2013_03_001_A_64 6.5 0.1 127.9 106.0 614.553791 66.679086 580 2013_03_001_A_36 6.5 0.1 127.9 106.0 130.205251 14.12727 255 2013_03_001_A_53 6.5 0.1 127.9 106.0 224.829012 24.393948 255 2013_03_001_A_66 6.5 0.1085 127.9 106 227.637498 24.698669 255 2013_03_008_A_20 6.5 0.26 124.3 106 115.421252 30.009525 790 2013_03_008_A_26 6.5 0.26 124.3 106 493.106914 128.2078 790 2013_03_008_A_47 6.5 0.26 124.3 106 1104.15305 287.07979 790 2013_03_008_A_62 6.5 0.26 124.3 106 863.504878 224.51127 790 2013_03_008_A_22 6.5 0.26 124.3 106 99.478794 25.864486 580 2013_03_008_A_28 6.5 0.26 124.3 106 360.065798 93.617108 580 2013_03_008_A_50 6.5 0.26 124.3 106 748.501064 194.61028 580 2013_03_008_A_64 6.5 0.26 124.3 106 616.274211 160.23129 580 2013_03_008_A_24 6.5 0.26 124.3 106 159.88613 41.570394 255 2013_03_008_A_30 6.5 0.26 124.3 106 455.177266 118.34609 255 2013_03_008_A_53 6.5 0.26 124.3 106 706.908938 183.79632 255 2013_03_008_A_66 6.5 0.26 124.3 106 516.183659 134.20775 255 2013_04_001_A_20 6.5 0.26 124.5 106 91.3034289 23.738892 790 2013_04_001_A_26 6.5 0.26 124.5 106 834.386801 216.94057 790 2013_04_001_A_22 6.5 0.26 124.5 106 233.174931 60.625482 580 2013_04_001_A_24 6.5 0.26 124.5 106 246.894153 64.19248 255 2013_04_001_A_30 6.5 0.26 124.5 106 1110.48366 288.72575 255 2013_04_018_A_20 6.5 0.26 61.4 106 56.1618 14.602068 790

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54 2013_04_018_A_26 6.5 0.26 61.4 106 605.794477 157.50656 790 2013_04_018_A_32 6.5 0.26 61.4 106 1142.68532 297.09818 790 2013_04_018_A_22 6.5 0.26 61.4 106 130.144726 33.837629 580 2013_04_018_A_28 6.5 0.26 61.4 106 609.26777 158.40962 580 2013_04_018_A_50 6.5 0.26 61.4 106 1245.00206 323.70054 580 2013_04_018_A_64 6.5 0.26 61.4 106 1129.69409 293.72046 580 2013_04_018_A_24 6.5 0.26 61.4 106 72.2251405 18.778537 255 Sample ID Nafion Amount (g) Porosity Inlet Colloid Conc (ppm) Colloid Size (nm) Pore Fluid Colloid Conc. (ppm) Specific Deposit (ppm) Flow Cell Position 2013_04_018_A_30 6.5 0.26 61.4 106 291.416916 75.768398 255 2013_04_018_A_53 6.5 0.26 61.4 106 671.455783 174.5785 255 2013_04_018_A_66 6.5 0.26 61.4 106 447.436983 116.33362 255 2013_06_002_A_20 6.5 0.26 124.19 106 77.3540639 20.112057 790 2013_06_002_A_26 6.5 0.26 124.19 106 432.34905 112.41075 790 2013_06_002_A_32 6.5 0.26 124.19 106 919.552733 239.08371 790 2013_06_002_A_22 6.5 0.26 124.19 106 126.477158 32.884061 580 2013_06_002_A_28 6.5 0.26 124.19 106 424.99696 110.49921 580 2013_06_002_A_50 6.5 0.26 124.19 106 1196.16146 311.00198 580 2013_06_002_A_64 6.5 0.26 124.19 106 914.310578 237.72075 580 2013_06_002_A_24 6.5 0.26 124.19 106 198.683041 51.657591 255 2013_06_002_A_30 6.5 0.26 124.19 106 493.106914 128.2078 255 2013_06_002_A_53 6.5 0.26 124.19 106 863.504878 224.51127 255 2013_06_002_A_66 6.5 0.26 124.19 106 723.261008 188.04786 255 2013_08_001_A_20 6.5 0.2187075 126.07 106 124.326416 27.19112 790 2013_08_001_A_26 6.5 0.2187075 126.07 106 1073.03726 234.6813 790 2013_08_001_A_47 6.5 0.2187075 126.07 106 2059.04019 450.32753 790 2013_08_001_A_62 6.5 0.2187075 126.07 106 1889.82418 413.31872 790 2013_08_001_A_22 6.5 0.2187075 126.07 106 214.012151 46.806063 580 2013_08_001_A_28 6.5 0.2187075 126.07 106 853.687663 186.70789 580 2013_08_001_A_50 6.5 0.2187075 126.07 106 1573.86966 344.2171 580 2013_08_001_A_64 6.5 0.2187075 126.07 106 1162.45281 254.23715 580 2013_08_001_A_24 6.5 0.2187075 126.07 106 251.165214 54.931716 255 2013_08_001_A_30 6.5 0.2187075 126.07 106 616.274211 134.78379 255 2013_08_001_A_53 6.5 0.2187075 126.07 106 1110.48366 242.8711 255 2013_08_001_A_66 6.5 0.2187075 126.07 106 546.554156 119.53549 255 2013_08_002_A_20 6.5 0.11088 61.821 106 29.8 3.304224 790 2013_08_002_A_26 6.5 0.11088 61.821 106 105 11.6424 790 2013_08_002_A_47 6.5 0.11088 61.821 106 570 63.2016 790 2013_08_002_A_62 6.5 0.11088 61.821 106 455 50.4504 790 2013_08_002_A_22 6.5 0.11088 61.821 106 28.7 3.182256 580

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55 2013_08_002_A_28 6.5 0.11088 61.821 106 111 12.30768 580 2013_08_002_A_50 6.5 0.11088 61.821 106 498 55.21824 580 2013_08_002_A_64 6.5 0.11088 61.821 106 337 37.36656 580 2013_08_002_A_24 6.5 0.11088 61.821 106 30.4 3.370752 255 2013_08_002_A_30 6.5 0.11088 61.821 106 97.8 10.844064 255 2013_08_002_A_53 6.5 0.11088 61.821 106 318 35.25984 255 2013_08_002_A_66 6.5 0.11088 61.821 106 130 14.4144 255 2013_08_003_A_20 6 61.604 106 8.3 790 2013_08_003_A_26 6 61.604 106 12.5 790 2013_08_003_A_47 6 61.604 106 30.5 790 Sample ID Nafion Amount (g) Porosity Inlet Colloid Conc (ppm) Colloid Size (nm) Pore Fluid Colloid Conc. ( ppm) Specific Deposit (ppm) Flow Cell Position 2013_08_003_A_62 6 61.604 106 42.4 790 2013_08_003_A_22 6 61.604 106 10.8 580 2013_08_003_A_28 6 61.604 106 11.2 580 2013_08_003_A_50 6 61.604 106 18.5 580 2013_08_003_A_64 6 61.604 106 6.1 580 2013_08_003_A_24 6 61.604 106 14.7 255 2013_08_003_A_30 6 61.604 106 11.7 255 2013_08_003_A_53 6 61.604 106 0 255 2013_08_003_A_66 6 61.604 106 0 255 2013_09_001_A_20 6.5 0.05 126.715 106 26.3 1.315 790 2013_09_001_A_26 6.5 0.05 126.715 106 28.5 1.425 790 2013_09_001_A_47 6.5 0.05 126.715 106 13.2 0.66 790 2013_09_001_A_62 6.5 0.05 126.715 106 21.9 1.095 790 2013_09_001_A_22 6.5 0.05 126.715 106 16.6 0.83 580 2013_09_001_A_28 6.5 0.05 126.715 106 15.1 0.755 580 2013_09_001_A_50 6.5 0.05 126.715 106 19.7 0.985 580 2013_09_001_A_64 6.5 0.05 126.715 106 2.7 0.135 580 2013_09_001_A_24 6.5 0.05 126.715 106 0 0 255 2013_09_001_A_30 6.5 0.05 126.715 106 5.2 0.26 255 2013_09_001_A_53 6.5 0.05 126.715 106 11.7 0.585 255 2013_09_001_A_66 6.5 0.05 126.715 106 0 0 255 2013_09_002_A_20 6.5 0.26 30.66 106 62 16.12 790 2013_09_002_A_26 6.5 0.26 30.66 106 324 84.24 790 2013_09_002_A_47 6.5 0.26 30.66 106 858 223.08 790 2013_09_002_A_62 6.5 0.26 30.66 106 680 176.8 790 2013_09_002_A_22 6.5 0.26 30.66 106 60 15.6 580 2013_09_002_A_28 6.5 0.26 30.66 106 196 50.96 580 2013_09_002_A_50 6.5 0.26 30.66 106 446 115.96 580

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56 2013_09_002_A_64 6.5 0.26 30.66 106 387 100.62 580 2013_09_002_A_24 6.5 0.26 30.66 106 46.3 12.038 255 2013_09_002_A_30 6.5 0.26 30.66 106 122 31.72 255 2013_09_002_A_53 6.5 0.26 30.66 106 278 72.28 255 2013_09_002_A_66 6.5 0.26 30.66 106 244 63.44 255 Sample ID Volume Eluted (ml) Pore Volumes Eluted Clean Bed Head Loss (cm H2O) Clean Bed K (cm/min) dH /dHo Hyd Cond (cm/min) 2012_03_001_A_6 33.166667 2012_03_001_A_7 59.7 2012_03_001_A_11 159.2 2012_04_002_A_15 193.2 1.02 2012_05_001_A_12 35 2012_05_001_A_15 87.5 2012_05_001_A_21 196 2012_05_001_A_27 297.5 2012_06_001_A_12 25.875 2012_06_001_A_18 94.5 2012_06_001_A_24 182 2012_06_001_A_30 268.25 1.73 2012_06_002_A_24 111.63 2012_06_002_A_27 186.76 2012_06_002_A_30 272.15 2012_06_003_A_15 23.4 2012_06_003_A_21 86.775 2013_01_002_A_42 181 131.636364 6.5 1.75970048 1.07 1.649 2013_01_002_A_48 341 248 6.5 1.75970048 1.46 1.21 2013_01_002_A_54 377 274.181818 6.5 1.75970048 1.61 1.09 2013_01_002_A_88 1320 960 6.5 1.75970048 0.908 1.94 2013_01_002_A_41 155 112.727273 10 2.28761062 1.027 2.227 2013_01_002_A_47 315 229.090909 10 2.28761062 1.359 1.683 2013_01_002_A_53 377 274.181818 10 2.28761062 1.53 1.5 2013_01_002_A_82 1160 843.636364 10 2.28761062 1.16 1.967 2013_01_002_A_40 124 90.1818182 45.4 0.75581849 0.999 0.757 2013_01_002_A_46 290 210.909091 45.4 0.75581849 1.072 0.7049 2013_01_002_A_52 377 274.181818 45.4 0.75581849 1.15 0.66 2013_01_002_A_75 984 715.636364 45.4 0.75581849 1.054 0.717 2013_02_001_A_47 356 258.909091 2013_02_001_A_56 437 317.818182

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57 2013_02_001_A_62 617 448.727273 2013_02_002_A_20 22 16.8744008 3.8 1.57196088 1.04 1.516 2013_02_002_A_26 113 86.6730585 3.8 1.57196088 1.28 1.22 2013_02_002_A_47 332 254.650048 3.8 1.57196088 1.88 0.835 2013_02_002_A_62 578 443.336529 3.8 1.54285049 1.99 0.775 2013_02_002_A_22 49 37.5838926 11 1.08608206 1.101 0.98 2013_02_002_A_28 138 105.848514 11 1.08608206 1.32 0.825 2013_02_002_A_50 332 254.650048 11 1.08608206 1.95 0.557 Sample ID Volume Eluted (ml) Pore Volumes Eluted Clean Bed Head Loss (cm H2O) Clean Bed K (cm/min) dH/dHo Hyd Cond (cm/min) 2013_02_002_A_64 605 464.046021 11 1.06596943 1.964 0.543 2013_02_002_A_24 73 55.9923298 15 1.19469027 1.13 1.055 2013_02_002_A_30 165 126.558006 15 1.19469027 1.245 0.959 2013_02_002_A_53 332 254.650048 15 1.19469027 1.52 0.787 2013_02_002_A_66 629 482.454458 15 1.17256637 1.5 0.782 2013_03_001_A_26 129 95.1152074 2013_03_001_A_32 235 173.271889 2013_03_001_A_47 343 252.903226 2013_03_001_A_62 593 437.235023 2013_03_001_A_28 157 115.760369 2013_03_001_A_34 260 191.705069 2013_03_001_A_50 343 252.903226 2013_03_001_A_64 621 457.880184 2013_03_001_A_36 292 215.299539 2013_03_001_A_53 343 252.903226 2013_03_001_A_66 649 478.525346 2013_03_008_A_20 58 17.8461538 1.1 11.6854385 1.015 11.515 2013_03_008_A_26 267 82.1538462 1.1 11.6854385 1.105 10.57 2013_03_008_A_47 485 149.230769 1.1 11.6854385 1.17 9.99 2013_03_008_A_62 809 248.923077 1.1 11.8262269 1.22 9.7 2013_03_008_A_22 110 33.8461538 7.4 3.47404927 1.03 2.6 2013_03_008_A_28 320 98.4615385 7.4 3.47404927 1.11 2.4 2013_03_008_A_50 485 149.230769 7.4 3.47404927 1.18 2.27 2013_03_008_A_64 861 264.923077 7.4 3.51590529 1.248 2.189 2013_03_008_A_24 163 50.1538462 9.6 4.01686947 1.05 3.81 2013_03_008_A_30 372 114.461538 9.6 4.01686947 1.135 3.54 2013_03_008_A_53 485 149.230769 9.6 4.01686947 1.26 3.42 2013_03_008_A_66 914 281.230769 9.6 4.06526549 1.21 3.35 2013_04_001_A_20 24 7.38461538 1.99 3.31858407 0.996 3.32 2013_04_001_A_26 194 59.6923077 1.99 3.31858407 1.22 2.71

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58 2013_04_001_A_22 54 16.6153846 5.16 2.55968306 1.06 2.42 2013_04_001_A_24 81 24.9230769 6.45 3.07161967 1.1 2.79 2013_04_001_A_30 254 78.1538462 6.45 3.07161967 1.36 2.26 2013_04_018_A_20 17 5.23076923 1.14 2.73637634 1.1 2.5 2013_04_018_A_26 148 45.5384615 1.14 2.73637634 1.418 1.93 2013_04_018_A_32 250 76.9230769 1.14 2.73637634 1.77 1.54 2013_04_018_A_22 30 9.23076923 2.56 2.43708518 1.14 2.12 2013_04_018_A_28 161 49.5384615 2.56 2.43708518 1.5 1.62 2013_04_018_A_50 307 94.4615385 2.56 2.43708518 2.02 1.21 2013_04_018_A_64 512 157.538462 2.56 2.43708518 1.83 1.33 2013_04_018_A_24 42 12.9230769 3.3 2.83588093 1.144 2.48 Sample ID Volume Eluted (ml) Pore Volumes Eluted Clean Bed Head Loss (cm H2O) Clean Bed K (cm/min) dH /dHo Hyd Cond (cm/min) 2013_04_018_A_30 175 53.8461538 3.3 2.83588093 1.367 2.07 2013_04_018_A_53 307 94.4615385 3.3 2.83588093 1.71 1.66 2013_04_018_A_66 527 162.153846 3.3 2.83588093 1.517 1.87 2013_06_002_A_20 54 16.6153846 2.8 4.74083439 1 4.73 2013_06_002_A_26 216 66.4615385 2.8 4.74083439 1.068 4.437 2013_06_002_A_32 372 114.461538 2.8 4.74083439 1.27 3.733 2013_06_002_A_22 114 35.0769231 14.1 1.88288458 1.002 1.88 2013_06_002_A_28 264 81.2307692 14.1 1.88288458 1.095 1.719 2013_06_002_A_50 492 151.384615 14.1 1.88288458 1.245 1.514 2013_06_002_A_64 780 240 14.1 1.88288458 1.233 1.527 2013_06_002_A_24 162 49.8461538 2013_06_002_A_30 318 97.8461538 2013_06_002_A_53 492 151.384615 2013_06_002_A_66 834 256.615385 2013_08_001_A_20 47.4 17.3382257 6.4 2.04991704 1.2 1.7 2013_08_001_A_26 214 78.2780655 6.4 2.04991704 1.12 1.83 2013_08_001_A_47 513 187.647886 6.4 2.04991704 1.49 1.38 2013_08_001_A_62 810 296.286136 6.4 2.04991704 1.54 1.34 2013_08_001_A_22 113 41.3337448 18.9 1.3883036 1.03 1.34 2013_08_001_A_28 267 97.6646891 18.9 1.3883036 1.19 1.16 2013_08_001_A_50 513 187.647886 18.9 1.3883036 1.43 0.97 2013_08_001_A_64 863 315.672759 18.9 1.3883036 1.3 1.07 2013_08_001_A_24 160 58.5256564 28.6 1.37616808 1.07 1.28 2013_08_001_A_30 320 117.051313 28.6 1.37616808 1.21 1.14 2013_08_001_A_53 513 187.647886 28.6 1.37616808 1.33 1.04 2013_08_001_A_66 916 335.059383 28.6 1.37616808 1.202 1.145 2013_08_002_A_20 43.9 31.6738817 5.5 2.52011263 1.012 2.49

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59 2013_08_002_A_26 213 153.679654 5.5 2.52011263 1.086 2.321 2013_08_002_A_47 520 375.180375 5.5 2.52011263 1.21 2.08 2013_08_002_A_62 807 582.251082 5.5 2.52011263 0.97 2.7 2013_08_002_A_22 119 85.8585859 26.2 1.05806255 1.04 1.015 2013_08_002_A_28 269 194.083694 26.2 1.05806255 1.135 0.932 2013_08_002_A_50 520 375.180375 26.2 1.05806255 1.276 0.829 2013_08_002_A_64 859 619.76912 26.2 1.05806255 1.09 1.008 2013_08_002_A_24 157 113.275613 43.2 0.96254302 1.03 0.932 2013_08_002_A_30 326 235.209235 43.2 0.96254302 1.093 0.881 2013_08_002_A_53 520 375.180375 43.2 0.96254302 1.168 0.824 2013_08_002_A_66 918 662.337662 43.2 0.96254302 1.1 0.913 2013_08_003_A_20 46.5 2013_08_003_A_26 209 2013_08_003_A_47 521 Sample ID Volume Eluted (ml) Pore Volumes Eluted Clean Bed Head Loss (cm H2O) Clean Bed K (cm/min) dH/dHo Hyd Cond (cm/min) 2013_08_003_A_62 825 2013_08_003_A_22 98.9 2013_08_003_A_28 273 2013_08_003_A_50 521 2013_08_003_A_64 877 2013_08_003_A_24 157 2013_08_003_A_30 331 2013_08_003_A_53 521 2013_08_003_A_66 930 2013_09_001_A_20 47.1 75.36 7 1.86156764 1.01 1.844 2013_09_001_A_26 212 339.2 7 1.86156764 0.99 1.88 2013_09_001_A_47 527 843.2 7 1.86156764 0.986 1.889 2013_09_001_A_62 786 1257.6 7 1.86156764 0.929 2.007 2013_09_001_A_22 100 160 30.5 0.85449006 0.998 0.856 2013_09_001_A_28 265 424 30.5 0.85449006 0.991 0.863 2013_09_001_A_50 527 843.2 30.5 0.85449006 0.985 0.868 2013_09_001_A_64 834 1334.4 30.5 0.85449006 0.955 0.896 2013_09_001_A_24 153 244.8 44.5 0.87849259 1 0.878 2013_09_001_A_30 324 518.4 44.5 0.87849259 0.998 0.88 2013_09_001_A_53 527 843.2 44.5 0.87849259 0.988 0.889 2013_09_001_A_66 940 1504 44.5 0.87849259 0.97 0.906 2013_09_002_A_20 28 8.61538462 0.9 1.85840708 1.13 1.645 2013_09_002_A_26 116 35.6923077 0.9 1.85840708 1.38 1.34 2013_09_002_A_47 248 76.3076923 0.9 1.85840708 2.13 0.873

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60 2013_09_002_A_62 389 119.692308 0.9 1.87807276 1.85 1.01 2013_09_002_A_22 36.3 11.1692308 1.7 1.96772514 1.12 1.75 2013_09_002_A_28 124 38.1538462 1.7 1.96772514 1.44 1.35 2013_09_002_A_50 248 76.3076923 1.7 1.96772514 1.96 1.01 2013_09_002_A_64 395 121.538462 1.7 1.98854763 1.82 1.09 2013_09_002_A_24 43.1 13.2615385 1.8 2.78761062 1.03 2.7 2013_09_002_A_30 131 40.3076923 1.8 2.78761062 1.25 2.23 2013_09_002_A_53 248 76.3076923 1.8 2.78761062 1.43 1.96 2013_09_002_A_66 402 123.692308 1.8 2.81710914 1.39 2.02 Sample ID K/Ko Morph. Parameter (1/ppm) Fractal Dimension 95% Confidence Interval (+/ ) Df CI Df + CI Fractal Fit Range (Q^ 1) 2012_03_001_A_6 2.957 0.086 2.87 3.04 0.002 0.01 2012_03_001_A_7 3.01 0.076 2.93 3.09 0.002 0.01 2012_03_001_A_11 3.076 0.061 3.02 3.14 0.002 0.01 2012_04_002_A_15 2.906 0.159 2.75 3.07 0.002 0.006 2012_05_001_A_12 2.466 0.065 2.4 2.53 0.005 0.02 2012_05_001_A_15 2.187 0.053 2.13 2.24 0.005 0.02 2012_05_001_A_21 1.815 0.041 1.77 1.86 0.005 0.02 2012_05_001_A_27 1.984 0.057 1.93 2.04 0.005 0.02 2012_06_001_A_12 2.96 0.131 2.83 3.09 0.005 0.02 2012_06_001_A_18 2.297 0.051 2.25 2.35 0.005 0.02 2012_06_001_A_24 1.964 0.035 1.93 2 0.005 0.02 2012_06_001_A_30 2.118 0.046 2.07 2.16 0.005 0.02 2012_06_002_A_24 2.081 0.14 1.94 2.22 0.005 0.02 2012_06_002_A_27 2.524 0.123 2.4 2.65 0.005 0.02 2012_06_002_A_30 2.928 0.114 2.81 3.04 0.005 0.02 2012_06_003_A_15 2.36 0.031 2.33 2.39 0.002 0.02 2012_06_003_A_21 1.825 0.048 1.78 1.87 0.002 0.02 2013_01_002_A_42 0.937 7.33964E 05 1.853 0.04 1.81 1.89 0.002 0.02 2013_01_002_A_48 0.685 0.000127875 1.009 0.082 0.93 1.09 0.002 0.02 2013_01_002_A_54 0.621 0.000163131 0.91 0.074 0.84 0.98 0.002 0.02 2013_01_002_A_88 1.102 4.69449E 05 1.375 0.057 1.32 1.43 0.002 0.02 2013_01_002_A_41 0.973 0.000117608 2.044 0.034 2.01 2.08 0.002 0.02 2013_01_002_A_47 0.736 0.000271192 1.62 0.05 1.57 1.67 0.002 0.02 2013_01_002_A_53 0.655 0.000227605 1.261 0.061 1.2 1.32 0.002 0.02 2013_01_002_A_82 0.86 0.000144301 1.588 0.047 1.54 1.64 0.002 0.02 2013_01_002_A_40 1.001 9.55625E 06 2.25 0.036 2.21 2.29 0.002 0.02

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61 2013_01_002_A_46 0.932 0.000119069 2.015 0.061 1.95 2.08 0.002 0.02 2013_01_002_A_52 0.873 0.000134367 1.735 0.074 1.66 1.81 0.002 0.02 2013_01_002_A_75 0.949 6.58116E 05 1.829 0.054 1.78 1.88 0.002 0.02 2013_02_001_A_47 2.442 0.063 2.38 2.51 0.002 0.02 2013_02_001_A_56 2.259 0.052 2.21 2.31 0.002 0.02 2013_02_001_A_62 2.072 0.07 2 2.14 0.002 0.02 2013_02_002_A_20 0.96 0.000341936 2.722 0.048 2.67 2.77 0.005 0.02 2013_02_002_A_26 0.778 0.000331882 2.367 0.06 2.31 2.43 0.005 0.02 2013_02_002_A_47 0.531 0.000257239 1.352 0.095 1.26 1.45 0.005 0.02 2013_02_002_A_62 0.502 0.000286011 1.205 0.085 1.12 1.29 0.005 0.02 2013_02_002_A_22 0.908 0.000325121 2.235 0.041 2.19 2.28 0.005 0.02 2013_02_002_A_28 0.76 0.000233457 2.156 0.052 2.1 2.21 0.005 0.02 2013_02_002_A_50 0.512 0.000244115 1.705 0.065 1.64 1.77 0.005 0.02 Sample ID K/Ko Morph. Parameter (1/ppm) Fractal Dimension 95% Confidence Interval (+/ ) Df CI Df + CI Fractal Fit Range (Q^ 1) 2013_02_002_A_64 0.509 0.000240592 1.472 0.062 1.41 1.53 0.005 0.02 2013_02_002_A_24 0.883 0.000493 2.891 0.048 2.84 2.94 0.005 0.02 2013_02_002_A_30 0.803 0.000260534 2.547 0.042 2.51 2.59 0.005 0.02 2013_02_002_A_53 0.658 0.000201108 1.871 0.049 1.82 1.92 0.005 0.02 2013_02_002_A_66 0.667 0.000187973 1.901 0.042 1.86 1.94 0.005 0.02 2013_03_001_A_26 2.443 0.078 2.37 2.52 0.005 0.02 2013_03_001_A_32 2.378 0.046 2.33 2.42 0.005 0.02 2013_03_001_A_47 2.149 0.035 2.11 2.18 0.005 0.02 2013_03_001_A_62 2.038 0.05 1.99 2.09 0.005 0.02 2013_03_001_A_28 2.45 0.087 2.36 2.54 0.005 0.02 2013_03_001_A_34 2.559 0.044 2.52 2.6 0.005 0.02 2013_03_001_A_50 2.341 0.048 2.29 2.39 0.005 0.02 2013_03_001_A_64 2.35 0.041 2.31 2.39 0.005 0.02 2013_03_001_A_36 2.445 0.065 2.38 2.51 0.005 0.02 2013_03_001_A_53 2.475 0.048 2.43 2.52 0.005 0.02 2013_03_001_A_66 2.429 0.051 2.38 2.48 0.005 0.02 2013_03_008_A_20 0.986 6.12917E 05 1.812 0.035 1.78 1.85 0.002 0.02 2013_03_008_A_26 0.905 0.000103784 1.385 0.044 1.34 1.43 0.002 0.02 2013_03_008_A_47 0.855 7.37906E 05 0.94 0.065 0.88 1.01 0.002 0.02 2013_03_008_A_62 0.82 0.000120804 1.113 0.043 1.07 1.16 0.002 0.02 2013_03_008_A_22 0.748 0.001570618 2.048 0.02 2.03 2.07 0.002 0.02 2013_03_008_A_28 0.691 0.00056375 1.692 0.019 1.67 1.71 0.002 0.02 2013_03_008_A_50 0.654 0.00031603 1.377 0.026 1.35 1.4 0.002 0.02 2013_03_008_A_64 0.622 0.000434803 1.302 0.045 1.26 1.35 0.002 0.02 2013_03_008_A_24 0.948 0.000169246 1.879 0.031 1.85 1.91 0.002 0.02

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62 2013_03_008_A_30 0.881 0.000143677 1.548 0.03 1.52 1.58 0.002 0.02 2013_03_008_A_53 0.852 0.000117948 1.382 0.04 1.34 1.42 0.002 0.02 2013_03_008_A_66 0.824 0.00019689 1.539 0.04 1.5 1.58 0.002 0.02 2013_04_001_A_20 1.004 2.18395E 05 2.373 0.028 2.35 2.4 0.002 0.02 2013_04_001_A_26 0.82 0.00012502 1.162 0.054 1.11 1.22 0.002 0.02 2013_04_001_A_22 0.945 0.000123036 1.857 0.046 1.81 1.9 0.002 0.02 2013_04_001_A_24 0.909 0.000197904 1.77 0.052 1.72 1.82 0.002 0.02 2013_04_001_A_30 0.735 0.000149866 1.16 0.025 1.14 1.19 0.002 0.02 2013_04_018_A_20 0.9 0.000963156 2.208 0.049 2.16 2.26 0.002 0.02 2013_04_018_A_26 0.704 0.000316656 1.448 0.048 1.4 1.5 0.002 0.02 2013_04_018_A_32 0.565 0.000289126 1.013 0.062 0.95 1.08 0.002 0.02 2013_04_018_A_22 0.87 0.000554095 1.794 0.023 1.77 1.82 0.002 0.02 2013_04_018_A_28 0.665 0.000371394 1.454 0.035 1.42 1.49 0.002 0.02 2013_04_018_A_50 0.495 0.000338424 1.065 0.033 1.03 1.1 0.002 0.02 2013_04_018_A_64 0.545 0.000313865 1.113 0.039 1.07 1.15 0.002 0.02 2013_04_018_A_24 0.874 0.000964434 1.755 0.034 1.72 1.79 0.002 0.02 Sample ID K/Ko Morph. Parameter (1/ppm) Fractal Dimension 95% Confidence Interval (+/ ) Df CI Df + CI Fractal Fit Range (Q^ 1) 2013_04_018_A_30 0.73 0.000584769 1.477 0.043 1.43 1.52 0.002 0.02 2013_04_018_A_53 0.58 0.000466247 1.184 0.045 1.14 1.23 0.002 0.02 2013_04_018_A_66 0.66 0.000516084 1.193 0.051 1.14 1.24 0.002 0.02 2013_06_002_A_20 1 0 2 0.023 1.98 2.02 0.002 0.02 2013_06_002_A_26 0.936 7.77677E 05 1.65 0.032 1.62 1.68 0.002 0.02 2013_06_002_A_32 0.787 0.000138361 1.25 0.048 1.2 1.3 0.002 0.02 2013_06_002_A_22 0.998 7.91845E 06 2.06 0.017 2.04 2.08 0.002 0.02 2013_06_002_A_28 0.913 0.000109556 1.72 0.02 1.7 1.74 0.002 0.02 2013_06_002_A_50 0.804 9.63493E 05 1.17 0.034 1.14 1.2 0.002 0.02 2013_06_002_A_64 0.811 0.000120775 1.38 0.025 1.36 1.41 0.002 0.02 2013_06_002_A_24 1.92 0.035 1.89 1.96 0.002 0.02 2013_06_002_A_30 1.58 0.039 1.54 1.62 0.002 0.02 2013_06_002_A_53 1.29 0.045 1.25 1.34 0.002 0.02 2013_06_002_A_66 1.34 0.053 1.29 1.39 0.002 0.02 2013_08_001_A_20 0.8 0.000949388 1.93 0.036 1.89 1.97 0.002 0.02 2013_08_001_A_26 0.89 5.59141E 05 1.3 0.046 1.25 1.35 0.002 0.02 2013_08_001_A_47 0.64 0.000121416 0.319 0.07 0.25 0.39 0.002 0.02 2013_08_001_A_62 0.651 0.000126675 0.511 0.055 0.46 0.57 0.002 0.02 2013_08_001_A_22 0.97 7.1707E 05 2.05 0.032 2.02 2.08 0.002 0.02 2013_08_001_A_28 0.84 0.000106701 1.42 0.036 1.38 1.46 0.002 0.02 2013_08_001_A_50 0.67 0.000140859 0.529 0.053 0.48 0.58 0.002 0.02 2013_08_001_A_64 0.77 0.000120096 1.01 0.047 0.96 1.06 0.002 0.02

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63 2013_08_001_A_24 0.93 0.000147121 1.81 0.03 1.78 1.84 0.002 0.02 2013_08_001_A_30 0.83 0.00015844 1.48 0.03 1.45 1.51 0.002 0.02 2013_08_001_A_53 0.735 0.000149866 1.13 0.026 1.1 1.16 0.002 0.02 2013_08_001_A_66 0.83 0.000178651 1.46 0.04 1.42 1.5 0.002 0.02 2013_08_002_A_20 0.988 1.72 0.047 1.67 1.77 0.002 0.02 2013_08_002_A_26 0.92 0.000405448 2 0.074 1.93 2.07 0.002 0.02 2013_08_002_A_47 0.827 0.000174792 1.64 0.1 1.54 1.74 0.002 0.02 2013_08_002_A_62 1.03 3.22433E 05 1.79 0.093 1.7 1.88 0.002 0.02 2013_08_002_A_22 0.96 2.25 0.039 2.21 2.29 0.002 0.02 2013_08_002_A_28 0.881 0.000589175 2.43 0.051 2.38 2.48 0.002 0.02 2013_08_002_A_50 0.782 0.000262707 1.95 0.079 1.87 2.03 0.002 0.02 2013_08_002_A_64 0.915 0.000134768 2.11 0.077 2.03 2.19 0.002 0.02 2013_08_002_A_24 0.97 2.3 0.039 2.26 2.34 0.002 0.02 2013_08_002_A_30 0.914 0.00047023 2.27 0.048 2.22 2.32 0.002 0.02 2013_08_002_A_53 0.856 0.000254227 2.12 0.073 2.05 2.19 0.002 0.02 2013_08_002_A_66 0.91 0.000371422 2.33 0.052 2.28 2.38 0.002 0.02 2013_08_003_A_20 0 0 2013_08_003_A_26 1.89 0.151 1.74 2.04 0.002 0.02 2013_08_003_A_47 2.34 0.049 2.29 2.39 0.002 0.02 Sample ID K/Ko Morph. Parameter (1/ppm) Fractal Dimension 95% Confidence Interval (+/ ) Df CI Df + CI Fractal Fit Range (Q^ 1) 2013_08_003_A_62 2.04 0.057 1.98 2.1 0.002 0.02 2013_08_003_A_22 0 0 2013_08_003_A_28 0 0 2013_08_003_A_50 2.08 0.127 1.95 2.21 0.005 0.015 2013_08_003_A_64 3.1 0.163 2.94 3.26 0.005 0.015 2013_08_003_A_24 1.32 0.242 1.08 1.56 0.005 0.012 2013_08_003_A_30 0 0 2013_08_003_A_53 2.7 0.464 2.24 3.16 0.005 0.012 2013_08_003_A_66 0 0 2013_09_001_A_20 0.99 0.889 0.1574 0.73 1.05 0.003 0.02 2013_09_001_A_26 1.01 1.136 0.1448 0.99 1.28 0.003 0.02 2013_09_001_A_47 1.014 2.265 0.2435 2.02 2.51 0.003 0.02 2013_09_001_A_62 1.077 1.595 0.1288 1.47 1.72 0.003 0.02 2013_09_001_A_22 1.002 1.138 0.2205 0.92 1.36 0.008 0.02 2013_09_001_A_28 1.01 1.352 0.2146 1.14 1.57 0.008 0.02 2013_09_001_A_50 1.015 1.574 0.174 1.4 1.75 0.008 0.02 2013_09_001_A_64 1.048 0 0 2013_09_001_A_24 0.999 0 0 2013_09_001_A_30 1.002 0 0

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64 2013_09_001_A_53 1.011 0 0 2013_09_001_A_66 1.033 0 0 2013_09_002_A_20 0.885 0.001015936 2.044 0.0382 2.01 2.08 0.002 0.02 2013_09_002_A_26 0.72 0.000550961 1.554 0.0218 1.53 1.58 0.002 0.02 2013_09_002_A_47 0.47 0.000534557 1.092 0.0255 1.07 1.12 0.002 0.02 2013_09_002_A_62 0.54 0.000530629 1.142 0.0265 1.12 1.17 0.002 0.02 2013_09_002_A_22 0.89 0.000999965 1.721 0.0497 1.67 1.77 0.002 0.02 2013_09_002_A_28 0.69 0.001040095 1.584 0.0351 1.55 1.62 0.002 0.02 2013_09_002_A_50 0.512 0.000891351 1.363 0.0291 1.33 1.39 0.002 0.02 2013_09_002_A_64 0.55 0.000900258 1.423 0.0338 1.39 1.46 0.002 0.02 2013_09_002_A_24 0.96 0.000445372 2.297 0.0436 2.25 2.34 0.002 0.02 2013_09_002_A_30 0.8 0.000967492 2.1 0.0278 2.07 2.13 0.002 0.02 2013_09_002_A_53 0.69 0.000733304 1.785 0.0351 1.75 1.82 0.002 0.02 2013_09_002_A_66 0.72 0.000731604 1.864 0.0331 1.83 1.9 0.002 0.02 Sample ID Straight Transmission (%) Dyn. Viscosity Fluid, From Pang (kg/(m*s)) Clean Bed d50 calc with Kozeny Carmen (m) Reynolds Number, Clean Bed d50 Aggregate Radius of Gyration (m) 2012_03_001_A_6 0.0027478 2012_03_001_A_7 0.0027478 2012_03_001_A_11 0.0027478 2012_04_002_A_15 0.0027478 2012_05_001_A_12 0.0027478 2012_05_001_A_15 0.0027478 2012_05_001_A_21 0.0027478 2012_05_001_A_27 0.0027478 2012_06_001_A_12 0.0027478 2012_06_001_A_18 0.0027478 2012_06_001_A_24 0.0027478 2012_06_001_A_30 0.0027478 2012_06_002_A_24 0.0027478 2012_06_002_A_27 0.0027478 2012_06_002_A_30 0.0027478 2012_06_003_A_15 0.0027478 2012_06_003_A_21 0.0027478 2013_01_002_A_42 0.7 0.0027478 0.00306899 1.590061815 0.00120099 2013_01_002_A_48 0.1 0.0027478 0.00306899 1.590061815 18.9 2013_01_002_A_54 0.1 0.0027478 0.00306899 1.590061815 162.9 2013_01_002_A_88 0.2 0.0027478 0.00306899 1.590061815 0.070543303 2013_01_002_A_41 5.6 0.0027478 0.00349919 1.812949406 0.00024343

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65 2013_01_002_A_47 0.4 0.0027478 0.00349919 1.812949406 0.006130301 2013_01_002_A_53 0.2 0.0027478 0.00349919 1.812949406 0.257430453 2013_01_002_A_82 0.6 0.0027478 0.00349919 1.812949406 0.007198757 2013_01_002_A_40 16 0.0027478 0.00201134 1.042085583 7.85844E 05 2013_01_002_A_46 1.2 0.0027478 0.00201134 1.042085583 0.000438965 2013_01_002_A_52 0.5 0.0027478 0.00201134 1.042085583 0.002588433 2013_01_002_A_75 0.8 0.0027478 0.00201134 1.042085583 0.001288721 2013_02_001_A_47 4.2 0.0027478 0.0 2013_02_001_A_56 3.7 0.0027478 0.0 2013_02_001_A_62 2.6 0.0027478 0.0 2013_02_002_A_20 7.6 0.0027478 0.00316179 0.855507561 2.28959E 05 2013_02_002_A_26 0.6 0.0027478 0.00316179 0.855507561 0.000126917 2013_02_002_A_47 0.1 0.0027478 0.00316179 0.855507561 0.1 2013_02_002_A_62 0.1 0.0027478 0.00313237 0.831853823 0.7 2013_02_002_A_22 5.2 0.0027478 0.00262811 0.711105939 0.000129938 2013_02_002_A_28 0.5 0.0027478 0.00262811 0.711105939 0.000334394 2013_02_002_A_50 0.1 0.0027478 0.00262811 0.711105939 0.0 Sample ID Straight Transmission (%) Dyn. Viscosity Fluid, From Pang (kg/(m*s)) Clean Bed d50 calc with Kozeny Carmen (m) Reynolds Number, Clean Bed d50 Aggregate Radius of Gyration (m) 2013_02_002_A_64 0.1 0.0027478 0.00260366 0.69144473 0.037803485 2013_02_002_A_24 3.1 0.0027478 0.00275638 0.745814201 2.09565E 05 2013_02_002_A_30 0.5 0.0027478 0.00275638 0.745814201 0.0 2013_02_002_A_53 0.1 0.0027478 0.00275638 0.745814201 0.0 2013_02_002_A_66 0.1 0.0027478 0.00273074 0.72519335 0.0 2013_03_001_A_26 5.5 0.0027478 0.0 2013_03_001_A_32 1 0.0027478 0.0 2013_03_001_A_47 0.2 0.0027478 0.0 2013_03_001_A_62 0.2 0.0027478 0.0 2013_03_001_A_28 4.7 0.0027478 0.0 2013_03_001_A_34 0.9 0.0027478 0.0 2013_03_001_A_50 0.3 0.0027478 0.0 2013_03_001_A_64 0.3 0.0027478 0.000163405 2013_03_001_A_36 5.5 0.0027478 6.33965E 05 2013_03_001_A_53 2 0.0027478 7.25449E 05 2013_03_001_A_66 2.2 0.0027478 8.3603E 05 2013_03_008_A_20 7.4 0.0027478 0.00180955 1.053594383 0.001142425 2013_03_008_A_26 0.8 0.0027478 0.00180955 1.053594383 0.070667964 2013_03_008_A_47 0.2 0.0027478 0.00180955 1.053594383 132.2003646 2013_03_008_A_62 0.3 0.0027478 0.00182041 1.072692483 3.670156468

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66 2013_03_008_A_22 6.5 0.0027478 0.00098665 0.574472081 0.000336459 2013_03_008_A_28 1 0.0027478 0.00098665 0.574472081 0.00454141 2013_03_008_A_50 0.3 0.0027478 0.00098665 0.574472081 0.103856711 2013_03_008_A_64 0.4 0.0027478 0.00099258 0.584885315 0.206086052 2013_03_008_A_24 4.1 0.0027478 0.00106094 0.617724462 0.000951972 2013_03_008_A_30 0.8 0.0027478 0.00106094 0.617724462 0.015199454 2013_03_008_A_53 0.4 0.0027478 0.00106094 0.617724462 0.094559229 2013_03_008_A_66 0.7 0.0027478 0.00106731 0.628921716 0.017751557 2013_04_001_A_20 6.3 0.0027478 0.00096433 0.288466613 9.78218E 05 2013_04_001_A_26 0.2 0.0027478 0.00096433 0.288466613 1.664349307 2013_04_001_A_22 2.4 0.0027478 0.00084692 0.253344944 0.001309999 2013_04_001_A_24 2.1 0.0027478 0.00092775 0.277525481 0.002224465 2013_04_001_A_30 0.2 0.0027478 0.00092775 0.277525481 2.193772665 2013_04_018_A_20 11.1 0.0027478 0.00087566 0.123731943 0.000137698 2013_04_018_A_26 0.5 0.0027478 0.00087566 0.123731943 0.04410279 2013_04_018_A_32 0.1 0.0027478 0.00087566 0.123731943 28.75836996 2013_04_018_A_22 9 0.0027478 0.00082639 0.116769461 0.001350119 2013_04_018_A_28 0.6 0.0027478 0.00082639 0.116769461 0.041854654 2013_04_018_A_50 0.1 0.0027478 0.00082639 0.116769461 11.6751359 2013_04_018_A_64 0.2 0.0027478 0.00082639 0.116769461 4.672322302 2013_04_018_A_24 14.5 0.0027478 0.00089144 0.125961527 0.001209388 Sample ID Straight Transmission (%) Dyn. Viscosity Fluid, From Pang (kg/(m*s)) Clean Bed d50 calc with Kozeny Carmen (m) Reynolds Number, Clean Bed d50 Aggregate Radius of Gyration (m) 2013_04_018_A_30 2 0.0027478 0.00089144 0.125961527 0.020561448 2013_04_018_A_53 0.5 0.0027478 0.00089144 0.125961527 1.005206277 2013_04_018_A_66 1.1 0.0027478 0.00089144 0.125961527 0.630352498 2013_06_002_A_20 12.4 0.0027478 0.00115259 0.693032259 0.000366077 2013_06_002_A_26 1 0.0027478 0.00115259 0.693032259 0.006774995 2013_06_002_A_32 0.3 0.0027478 0.00115259 0.693032259 0.533611598 2013_06_002_A_22 5.4 0.0027478 0.00072637 0.436755022 0.000359255 2013_06_002_A_28 0.8 0.0027478 0.00072637 0.436755022 0.004156715 2013_06_002_A_50 0.1 0.0027478 0.00072637 0.436755022 2.012229437 2013_06_002_A_64 0.2 0.0027478 0.00072637 0.436755022 0.116339697 2013_06_002_A_24 2.7 0.0027478 0.000864803 2013_06_002_A_30 0.7 0.0027478 0.012396401 2013_06_002_A_53 0.3 0.0027478 0.308253184 2013_06_002_A_66 0.3 0.0027478 0.15102743 2013_08_001_A_20 5.2 0.0027478 0.0010372 0.616373682 0.000589769 2013_08_001_A_26 0.2 0.0027478 0.0010372 0.616373682 0.282925571

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67 2013_08_001_A_47 0.1 0.0027478 0.0010372 0.616373682 1.06488E+21 2013_08_001_A_62 0.1 0.0027478 0.0010372 0.616373682 20893601259 2013_08_001_A_22 1.7 0.0027478 0.00085356 0.507245461 0.000445533 2013_08_001_A_28 0.2 0.0027478 0.00085356 0.507245461 0.065045781 2013_08_001_A_50 0.1 0.0027478 0.00085356 0.507245461 3724762065 2013_08_001_A_64 0.1 0.0027478 0.00085356 0.507245461 26.1647877 2013_08_001_A_24 2.2 0.0027478 0.00084982 0.505023613 0.001613166 2013_08_001_A_30 0.4 0.0027478 0.00084982 0.505023613 0.029562767 2013_08_001_A_53 0.1 0.0027478 0.00084982 0.505023613 2.998761227 2013_08_001_A_66 0.6 0.0027478 0.00084982 0.505023613 0.032640061 2013_08_002_A_20 31.8 0.0027478 0.00362548 2.276222514 0.000540176 2013_08_002_A_26 6.3 0.0027478 0.00362548 2.276222514 0.000278526 2013_08_002_A_47 0.4 0.0027478 0.00362548 2.276222514 0.005123412 2013_08_002_A_62 0.5 0.0027478 0.00362548 2.276222514 0.001726338 2013_08_002_A_22 28.5 0.0027478 0.00234916 1.474892651 6.04099E 05 2013_08_002_A_28 4.4 0.0027478 0.00234916 1.474892651 6.25779E 05 2013_08_002_A_50 0.4 0.0027478 0.00234916 1.474892651 0.000770819 2013_08_002_A_64 0.8 0.0027478 0.00234916 1.474892651 0.000309685 2013_08_002_A_24 31.2 0.0027478 0.00224061 1.406743164 5.31522E 05 2013_08_002_A_30 7.7 0.0027478 0.00224061 1.406743164 9.74401E 05 2013_08_002_A_53 1.1 0.0027478 0.00224061 1.406743164 0.000289244 2013_08_002_A_66 4.4 0.0027478 0.00224061 1.406743164 9.07243E 05 2013_08_003_A_20 44.9 0.0027478 2013_08_003_A_26 42.5 0.0027478 2013_08_003_A_47 27.8 0.0027478 Sample ID Straight Transmission (%) Dyn. Viscosity Fluid, From Pang (kg/(m*s)) Clean Bed d50 calc with Kozeny Carmen (m) Reynolds Number, Clean Bed d50 Aggregate Radius of Gyration (m) 2013_08_003_A_62 24 0.0027478 2013_08_003_A_22 53.9 0.0027478 2013_08_003_A_28 50.2 0.0027478 2013_08_003_A_50 42.4 0.0027478 2013_08_003_A_64 37.8 0.0027478 2013_08_003_A_24 60.2 0.0027478 2013_08_003_A_30 59.8 0.0027478 2013_08_003_A_53 62.5 0.0027478 2013_08_003_A_66 54 0.0027478 2013_09_001_A_20 31.7 0.0027478 0.0109947 6.48972679 1.069505625 2013_09_001_A_26 31.4 0.0027478 0.0109947 6.48972679 0.029620503 2013_09_001_A_47 30.7 0.0027478 0.0109947 6.48972679 2.87895E 05 2013_09_001_A_62 31.7 0.0027478 0.0109947 6.48972679 0.000557106

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68 2013_09_001_A_22 36.5 0.0027478 0.00744899 4.396838481 0.017997839 2013_09_001_A_28 36.2 0.0027478 0.00744899 4.396838481 0.00223531 2013_09_001_A_50 34.8 0.0027478 0.00744899 4.396838481 0.000589363 2013_09_001_A_64 36.9 0.0027478 0.00744899 4.396838481 2013_09_001_A_24 39 0.0027478 0.00755289 4.458164156 2013_09_001_A_30 38.8 0.0027478 0.00755289 4.458164156 2013_09_001_A_53 36.4 0.0027478 0.00755289 4.458164156 2013_09_001_A_66 40.5 0.0027478 0.00755289 4.458164156 2013_09_002_A_20 9.6 0.0027478 0.00072164 0.05467226 0.000271591 2013_09_002_A_26 1.2 0.0027478 0.00072164 0.05467226 0.011634635 2013_09_002_A_47 0.3 0.0027478 0.00072164 0.05467226 5.163190695 2013_09_002_A_62 0.4 0.0027478 0.00072544 0.055542366 1.882479892 2013_09_002_A_22 14 0.0027478 0.00074256 0.056257292 0.001323948 2013_09_002_A_28 3 0.0027478 0.00074256 0.056257292 0.006710885 2013_09_002_A_50 0.8 0.0027478 0.00074256 0.056257292 0.082431212 2013_09_002_A_64 1 0.0027478 0.00074647 0.057152623 0.040898899 2013_09_002_A_24 14.4 0.0027478 0.00088382 0.06695957 9.335E 05 2013_09_002_A_30 4.6 0.0027478 0.00088382 0.06695957 0.000298522 2013_09_002_A_53 1.4 0.0027478 0.00088382 0.06695957 0.002173941 2013_09_002_A_66 1.8 0.0027478 0.00088848 0.068025228 0.00129225 Sample ID Comments 2012_03_001_A_6 No Salt 2012_03_001_A_7 No Salt 2012_03_001_A_11 No Salt 2012_04_002_A_15 Questionable head data, due to changes in salt conc effect on Nafion 2012_05_001_A_12 Questionable head data, due to changes in salt conc effect on Nafion 2012_05_001_A_15 Questionable h ead data, due to changes in salt conc effect on Nafion 2012_05_001_A_21 Questionable head data, due to changes in salt conc effect on Nafion, Clear started at 196 ml eluted 2012_05_001_A_27 Volume clear eluded after deposition, 2012_06_001_A_12 Head data taken before and after scan only 2012_06_001_A_18 Head data taken before and after scan only 2012_06_001_A_24 Head data taken before and after scan only, Clear started at 182 ml eluted 2012_06_001_A_30 Volume clear eluded after deposition, same head data 2012_06_002_A_24 2012_06_002_A_27 Clear started at 188 ml eluted 2012_06_002_A_30 Volume clear eluded after deposition, same head data 2012_06_003_A_15 Later scans look bad

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69 2012_06_003_A_21 Later scans look bad 2013_01_002_A_42 deposition 2013_01_002_A_48 deposition 2013_01_002_A_54 No Flow, after deposition, Clear started at 377 ml eluted 2013_01_002_A_88 clear flow with partial recycle 2013_01_002_A_41 deposition 2013_01_002_A_47 deposition 2013_01_002_A_53 No Flow, after deposition, Clear started at 377 ml eluted 2013_01_002_A_82 clear flow with partial recycle 2013_01_002_A_40 deposition 2013_01_002_A_46 deposition 2013_01_002_A_52 No Flow, after deposition, Clear started at 377 ml eluted 2013_01_002_A_75 clear flow with partial recycle 2013_02_001_A_47 No Flow, after deposition, Nafion/salt problems, No Pressure Equilibrium, Clear Flow started at 356 ml eluted 2013_02_001_A_56 clear flow, nafion problems, No Pressure Equilibrium 2013_02_001_A_62 clear flow, nafion problems, No Pressure Equilibrium 2013_02_002_A_20 deposition, Nafion Equil Not Great 2013_02_002_A_26 deposition, Nafion Equil Not Great 2013_02_002_A_47 deposition, no flow, Nafion Equil Not Great, Clear flow started at 332 ml eluted 2013_02_002_A_62 Clear Flow, Nafion Equil Not Great 2013_02_002_A_22 deposition, Nafion Equil Not Great 2013_02_002_A_28 deposition, Nafion Equil Not Great 2013_02_002_A_50 deposition, no flow, Nafion Equil Not Great, Clear flow started at 332 ml eluted Sample ID Comments 2013_02_002_A_64 Clear Flow, Nafion Equil Not Great 2013_02_002_A_24 deposition, Nafion Equil Not Great 2013_02_002_A_30 deposition, Nafion Equil Not Great 2013_02_002_A_53 deposition, no flow, Nafion Equil Not Great, Clear flow started at 332 ml eluted 2013_02_002_A_66 Clear Flow, Nafion Equil Not Great 2013_03_001_A_26 deposition, bad head data 2013_03_001_A_32 deposition, bad head data 2013_03_001_A_47 deposition, no flow, bad head data, Clear flow started at 343 ml eluted 2013_03_001_A_62 Clear Flow, bad head data 2013_03_001_A_28 deposition, bad head data 2013_03_001_A_34 deposition, bad head data 2013_03_001_A_50 deposition, no flow, bad head data, Clear flow started at 343 ml eluted 2013_03_001_A_64 Clear Flow, bad head data 2013_03_001_A_36 deposition, bad head data 2013_03_001_A_53 deposition, no flow, bad head data, Clear flow started at 343 ml eluted

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70 2013_03_001_A_66 Clear Flow, bad head data 2013_03_008_A_20 deposition 2013_03_008_A_26 deposition 2013_03_008_A_47 deposition, no flow, Clear flow started at 485 ml eluted 2013_03_008_A_62 Clear Flow 2013_03_008_A_22 deposition 2013_03_008_A_28 deposition 2013_03_008_A_50 deposition, no flow, Clear flow started at 485 ml eluted 2013_03_008_A_64 Clear Flow 2013_03_008_A_24 deposition 2013_03_008_A_30 deposition 2013_03_008_A_53 deposition, no flow, Clear flow started at 485 ml eluted 2013_03_008_A_66 Clear Flow 2013_04_001_A_20 deposition, scan maxed out at later times 2013_04_001_A_26 deposition 2013_04_001_A_22 deposition 2013_04_001_A_24 deposition 2013_04_001_A_30 deposition 2013_04_018_A_20 deposition, scan maxed out at later times 2013_04_018_A_26 deposition 2013_04_018_A_32 deposition, no flow 2013_04_018_A_22 deposition 2013_04_018_A_28 deposition 2013_04_018_A_50 deposition, no flow, Clear flow started at 307 ml eluted 2013_04_018_A_64 Clear Flow 2013_04_018_A_24 deposition Sample ID Comments 2013_04_018_A_30 deposition 2013_04_018_A_53 deposition, no flow, Clear flow started at 307 ml eluted 2013_04_018_A_66 Clear Flow 2013_06_002_A_20 Deposittion flow, bad later data 2013_06_002_A_26 Deposittion flow, bad later data 2013_06_002_A_32 Deposittion flow, bad later data 2013_06_002_A_22 deposition 2013_06_002_A_28 deposition 2013_06_002_A_50 deposition, no flow, Clear flow started at 492 ml eluted 2013_06_002_A_64 Clear Flow 2013_06_002_A_24 No Transducer DATA Dep Flow 2013_06_002_A_30 No Transducer DATA Dep Flow

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71 2013_06_002_A_53 No Transducer DATA Dep Flow, No Flow, Clear flow started at 492 ml eluted 2013_06_002_A_66 No Transducer DATA Clear Flow 2013_08_001_A_20 deposition 2013_08_001_A_26 deposition 2013_08_001_A_47 deposition, no flow, Clear flow started at 513 ml eluted 2013_08_001_A_62 Clear Flow. 2013_08_001_A_22 deposition 2013_08_001_A_28 deposition 2013_08_001_A_50 deposition, no flow, Clear flow started at 513 ml eluted 2013_08_001_A_64 Clear Flow 2013_08_001_A_24 deposition 2013_08_001_A_30 deposition 2013_08_001_A_53 deposition, no flow, Clear flow started at 513 ml eluted 2013_08_001_A_66 Clear Flow 2013_08_002_A_20 deposition 2013_08_002_A_26 deposition 2013_08_002_A_47 deposition, no flow, Clear flow started at 520 ml eluted 2013_08_002_A_62 Clear Flow. 2013_08_002_A_22 deposition 2013_08_002_A_28 deposition 2013_08_002_A_50 deposition, no flow, Clear flow started at 520 ml eluted 2013_08_002_A_64 Clear Flow 2013_08_002_A_24 deposition 2013_08_002_A_30 deposition 2013_08_002_A_53 deposition, no flow, Clear flow started at 520 ml eluted 2013_08_002_A_66 Clear Flow 2013_08_003_A_20 deposition, No Nafion Equilibrium 2013_08_003_A_26 deposition, No Nafion Equilibrium 2013_08_003_A_47 deposition, no flow, No Nafion Equilibrium Clear flow started at 521 ml eluted Sample ID Comments 2013_08_003_A_62 Clear Flow. No Nafion Equilibrium 2013_08_003_A_22 deposition, No Nafion Equilibrium 2013_08_003_A_28 deposition, No Nafion Equilibrium 2013_08_003_A_50 deposition, no flow, No Nafion Equilibrium Clear flow started at 521 ml eluted 2013_08_003_A_64 Clear Flow, No Nafion Equilibrium 2013_08_003_A_24 deposition, No Nafion Equilibrium 2013_08_003_A_30 deposition, No Nafion Equilibrium 2013_08_003_A_53 deposition, no flow, No Nafion Equilibrium Clear flow started at 521 ml eluted 2013_08_003_A_66 Clear Flow, No Nafion Equilibrium

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72 2013_09_001_A_20 deposition 2013_09_001_A_26 deposition 2013_09_001_A_47 deposition, no flow, Clear flow started at 527 ml eluted 2013_09_001_A_62 Clear Flow. 2013_09_001_A_22 deposition 2013_09_001_A_28 deposition 2013_09_001_A_50 deposition, no flow, Clear flow started at 527 ml eluted 2013_09_001_A_64 Clear Flow, No Clear Linear Region for Df 2013_09_001_A_24 deposition, No Clear Linear Region for Df 2013_09_001_A_30 deposition, No Clear Linear Region for Df 2013_09_001_A_53 deposition, no flow, No Clear Linear Region for Df, Clear flow started at 527 ml eluted 2013_09_001_A_66 Clear Flow, No Clear Linear Region for Df 2013_09_002_A_20 deposition 2013_09_002_A_26 deposition 2013_09_002_A_47 deposition, no flow, Clear flow started at 248 ml eluted 2013_09_002_A_62 Clear Flow. 2013_09_002_A_22 deposition 2013_09_002_A_28 deposition 2013_09_002_A_50 deposition, no flow, Clear flow started at 248 ml eluted 2013_09_002_A_64 Clear Flow 2013_09_002_A_24 deposition 2013_09_002_A_30 deposition 2013_09_002_A_53 deposition, no flow, Clear flow started at 248 ml eluted 2013_09_002_A_66 Clear Flow

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73 Results From Rifle Samples Collected 4 15 13 Well ID Sample # Scan ID Settled / Agitated Sample SLS Amplification Flow rate (ml/min) Colloid Concentration (g/ml) Colloid Concentration (ppm) LR01 2 2013_04_003_A_2 Settled 0.65 650 1.86047E 05 18.60465116 LR01 2 2013_04_003_B_1 Agitated 0.65 650 1.86047E 05 18.60465116 LR01 3 2013_04_004_A_2 Settled 0.65 0 1.86047E 05 18.60465116 LR01 3 2013_04_004_B_2 Agitated 0.65 0 1.86047E 05 18.60465116 FP101 6 2013_04_006_A_2 Settled 0.65 640 6.74419E 06 6.744186047 FP101 6 2013_04_006_B_1 Agitated 0.65 640 6.74419E 06 6.744186047 FP101 7 2013_04_007_B_2 Agitated 0.65 0 6.74419E 06 6.744186047 CD03 10 2013_04_009_A_2 Settled 0.45 880 1.51163E 05 15.11627907 CD03 10 2013_04_009_B_2 Agitated 0.45 880 1.51163E 05 15.11627907 CD03 11 2013_04_010_A_2 Settled 0.45 0 1.51163E 05 15.11627907 CD03 11 2013_04_010_B_2 Agitated 0.45 0 1.51163E 05 15.11627907 G51 14 2013_04_012_A_2 Settled 0.45 450 1.81395E 05 18.13953488 G51 14 2013_04_012_B_2 Agitated 0.45 450 1.81395E 05 18.13953488 G51 15 2013_04_013_A_2 Settled 0.45 0 1.81395E 05 18.13953488 G51 15 2013_04_013_B_2 Agitated 0.45 0 1.81395E 05 18.13953488 Well ID pH Temperature (deg C) Conductivity (uS/cm) Ionic Strength (M) Fractal Dimension R^2 95% Conf Interv LR01 7.44 10.8 1634 0.026144 2.21 0.958 0.111 LR01 7.44 10.8 1634 0.026144 1.71 0.898 0.139 LR01 7.44 10.8 1634 0.026144 2.45 0.974 0.096 LR01 7.44 10.8 1634 0.026144 1.52 0.939 0.093 FP101 7.26 9.4 3300 0.0528 1.69 0.943 0.1 FP101 7.26 9.4 3300 0.0528 1.81 0.958 0.092 FP101 7.26 9.4 3300 0.0528 2.27 0.916 0.166 CD03 7.3 9 3100 0.0496 1.74 0.984 0.054 CD03 7.3 9 3100 0.0496 1.82 0.984 0.056 CD03 7.3 9 3100 0.0496 1.96 0.979 0.07 CD03 7.3 9 3100 0.0496 2.09 0.972 0.086 G51 7.51 8.2 2785 0.04456 1.85 0.994 0.034 G51 7.51 8.2 2785 0.04456 1.82 0.993 0.036 G51 7.51 8.2 2785 0.04456 1.78 0.987 0.05 G51 7.51 8.2 2785 0.04456 1.71 0.979 0.06

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74 Well ID Comments LR01 Unknown Colloids, Monitor Well LR01 Unknown Colloids, Monitor Well LR01 Unknown Colloids, Monitor Well LR01 Unknown Colloids, Monitor Well FP101 Clay Colloids, Monitor Well FP101 Clay Colloids, Monitor Well FP101 Clay Colloids, Monitor Well CD03 Ferric Oxide Colloids, Acetate and Dissolved O2 Injections CD03 Ferric Oxide Colloids, Acetate and Dissolved O2 Injections CD03 Ferric Oxide Colloids, Acetate and Dissolved O2 Injections CD03 Ferric Oxide Colloids, Acetate and Dissolved O2 Injections G51 Bio colloids, Well Clogged Due to 3 Successive Acetate Injections G51 Bio colloids, Well Clogged Due to 3 Successive Acetate Injections G51 Bio colloids, Well Clogged Due to 3 Successive Acetate Injections G51 Bio colloids, Well Clogged Due to 3 Successive Acetate Injections

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75 Appendix B Additional Method Information Specific Deposit Calibration Curve Motivation In order to quantify the effect of deposit fractal dimension on permeability, it is crucial that we also know the specific deposit of colloidal aggregates in the precise area of the flow cell that is being scanned. Prior to this technique, we had planned to employ a mass balance approach using a spectrometer at the in let and outlet of the flow cell. Unfortunately a simple mass balance would not supply information about the specific cross section for which we have a fractal dimension measurement. The best solution to this problem will utilize intensity scan data that we regularly collect for each scan. Theory for Static Light Scattering Concentration Scans In order to determine specific deposit independently of deposit morphology, the technique used to measure specific deposit data can only be a function of colloid co ncentration, not colloid structure or any other variable that could change with each scan. On the I vs. Q plot, the only point that is theoretically independent of deposit morphology is at Q = 1/r. Since the colloid radius is constant, regardless of aggr egate structure, the scattered light intensity at 1/r should only be a function of colloid concentration at that point. Theoretical calculations by Benjamin Gilbert on 12/7/2012 show the assumption of morphology independent scattering at Q = 1/r to be appr oximately correct. Flow Cell Preparation and Scan Procedure For the calibration curve, 7 different colloid concentrations initially (0 ppm, 1 ppm, 3 ppm, 10 ppm, 30 ppm, 100 ppm, and 300 ppm) will be considered for four salt concentrations, 2mM, 8mM, and 16mM. Later it was found that flow cell deposits were higher than 300ppm, so experiments were run with an upper range of 1246 ppm. In order to keep solution mixtures homogeneous for each of the 7 scans, a batch of clear (colloid free) solution should be partitioned to 7 samples. This is important in order to keep index matching constant for each scan set. The samples should then be refrigerated; this will help slow the hydration of Nafion in the flow cell. The flow cell, with flow ports capped, should be dry packed with exactly 6.5 grams of Nafion. Add the desired concentration of colloids to the solution, then hydrate the Nafion by solution injection with a syringe through a pressure port. Mix the solution with the Nafion during hydration by repeated inversion. After the cell has become saturated and is air free, close all pressure ports and continue to mix the Nafion and colloid solution until the Nafion becomes immobile. Wait at least one hour for the flow cell and its contents to reach temperatur e equilibrium before scanning. Take SLS scans for multiple areas in the flow cell, these values will be averaged during analysis. Visually inspect each scanned region for bubbles or contaminants. Note any temperature changes during the scan. Repea t this procedure for duplicate and triplicate scans. Then repeat for each salt concentration that will be used for future experiments.

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76 Data Analysis Average the intensity data throughout the cell for each concentration, leaving out any data scanned in a region with bubbles or contaminants. Analyze the data as if it were a normal SLS scan. For the Concentration Curve, plot intensity values at Q = 1/r versus the concentration for that scan. Results 1 for all scans (includes blank) fro corrected for the transmission factor and the cross sectional area of the scattering region, per Mays et al. (2011). Colloid Concentration (ppm) I' at 1/r 1st Set (mV) I' at 1/r 2nd Set (mV) I' at 1/r 3rd Set (mV) I' at 1/r Average (mV) Standard Deviation (mV) 0 7.96E 11 7.01E 11 5.26E 11 6.74E 11 1.37E 11 0.802568218 8.18E 11 5.17E 11 6.54E 11 6.63E 11 1.51E 11 2.407704655 9.90E 11 7.17E 11 6.84E 11 7.97E 11 1.68E 11 8.025682183 5.52E 10 4.07E 10 4.02E 10 4.54E 10 8.53E 11 24.07704655 5.89E 10 3.60E 10 5.47E 10 4.99E 10 1.22E 10 80.25682183 1.12E 09 1.09E 09 1.59E 09 1.27E 09 2.80E 10 240.7704655 2.23E 08 2.87E 08 3.07E 08 2.72E 08 4.40E 09 1E 11 1E 10 1E 09 1E 08 1E 07 1E 06 1E 05 0.0001 0.001 0.01 I' (mV) q^ 1 (nm^ 1) I' vs q^ 1 0.45 Amp All Sets 0ppm 2012_10_001_A 1ppm 2012_10_002_A 3ppm 2012_10_003_A 10ppm 2012_10_004_A 30ppm 2012_10_005_A 100ppm 2012_11_001_A 300ppm 2012_11_002_A 0 ppm 2012_11_004_A Duplicate 1 ppm 2012_11_005_A Duplicate 3 ppm 2012_11_006_A Duplicate 10 ppm 2012_11_007_A Duplicate 30 ppm 2012_11_008_A Duplicate 100 ppm 2012_11_009_A Duplicate 300 ppm 2012_11_010_A Duplicate 0 ppm 2012_12_001_A Triplicate 1 ppm 2012_12_002_A Triplicate 3 ppm 2012_12_003_A Triplicate 10 ppm 2012_12_004_A Triplicate 30 ppm 2012_12_005_A Triplicate 100 ppm 2012_12_006_A Triplicate 300 ppm 2013_01_001_A Triplicate

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77 Concentration. Note: the point at 0.1 ppm is actually the blank (0 ppm); it was changed to facilitate plotting on a log log plot. I vlank per Mays et al. (2011). Colloid Concentr ation (ppm) I" at 1/r 1st Set (mV) I" at 1/r 2nd Set (mV) I" at 1/r 3rd Set (mV) I" at 1/r Average (mV) Standard Deviation (mV) 0.802568218 2.22E 12 1.84E 11 1.28E 11 1.12E 12 1.59E 11 2.407704655 1.95E 11 1.65E 12 1.58E 11 1.23E 11 9.41E 12 8.025682183 4.73E 10 3.37E 10 3.49E 10 3.86E 10 7.50E 11 24.07704655 5.10E 10 2.90E 10 4.94E 10 4.31E 10 1.23E 10 80.25682183 1.04E 09 1.02E 09 1.54E 09 1.20E 09 2.92E 10 240.7704655 2.22E 08 2.86E 08 3.07E 08 2.72E 08 4.41E 09 1.00E 11 1.00E 10 1.00E 09 1.00E 08 1.00E 07 0.1 1 10 100 1000 I' (mV) Concentration (ppm) I' vs Concentration 1st Set 2nd Set 3rd Set Average

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78 concentration line and standard deviation error bars. Later scans at different ionic strength and colloid concentrations are summarized in figure 5. Note that triplicate scans were not ma de for higher concentrations. 1.00E 11 1.00E 10 1.00E 09 1.00E 08 1.00E 07 0.1 1 10 100 1000 I' (mV) Concentration (ppm) I" vs Concentration 1st Set 2nd Set 3rd Set Average y = 3E 10e 0.0187x R = 0.9976 1.00E 11 1.00E 10 1.00E 09 1.00E 08 1.00E 07 1 10 100 1000 I' (mV) Concentration (ppm) I" vs Concentration Average Expon. (Average)

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79 Discussion Triplicate scans (Figures 2 3) indicate that this procedure is very repeatable. The line fit is not linear, but repeatability leads us to believe that this is a reasonable technique. Concentrations below 10 ppm show up as noise and are therefore omitted from the final curve. If future concentration calibration curve scans (for varying ionic strength) are also repeatable, the efficacy of this technique will have further confirmation. Why is the calibration curve exponential, rather than linear? That is, why does increasing the deposited colloid concentration from 25 to 50 ppm generate a smaller jump in scattering intensity than increasing the deposited colloid concentration from 50 to 75 ppm? This is not clear, but here is one potential explanation: Does the photo avalanche detector used to measure raw intensity, I, have a nonlinear dependence on stimulation intensity? Scans at different ionic strength seemed to have little effect on the curve. Unfortunately, Concentration results seem to lose precision at higher colloid concentrations. The technique works very well at low concentrations, but is still useful at higher concentrations. y = 3E+06x 0.515 R = 0.9304 0 200 400 600 800 1000 1200 1400 0 5E 08 0.0000001 1.5E 07 0.0000002 2.5E 07 0.0000003 Concentration (ppm) I" (mV) Concentration vs I" 2 mM, 8mM, and 16 mM 2 mM 16 mM All 8 mM Power (All)

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80 Working with Nafion Nafion is, as far as we have found, the most suitable index matched porous media material for use in our colloidal clogging experiments. Most importantly, Nafion is nicely index matched with a fairly benign solution of isopropanol and water. The pore scale properties of the Nafion grains effectively retain enough colloidal aggregate to cause clo gging which is critical for the experiment. Finally, hydrated Nafion is has a sufficiently rigid structure to minimize movement of the porous media, this allows us to normalize SLS scans with a colloid free blank with the same media structure. Unfortunat ely, Nafion is far from ideal. The following section will explain some of the challenges of working with Nafion, as well as some procedural solutions. Grain Uniformity Nafion is available in multiple size ranges. For our experiment we used 16 to 35 mesh grains. A grain size distribution is fine since natural porous media also exhibits a distribution of grain diameters. Unfortunately the distribution of Nafion grain size changes from batch to batch. Also with time and movement, smaller grains settle to the bottom of containers, making the grains larger near the top of the container. In order to have matching media conditions between experiments it became necessary to combine and thoroughly mix different batches of Nafion. Also, to keep Nafion evenly m ixed in the container, the container should be repeatedly inverted before apportioning. Hydrating Nafion and Clogging It was found that hydrating dry Nafion inside the flow cell was the most efficient way to load and de air the Nafion. However, the grain s approximately double in size upon hydration. The result is that small dry grains get lodged near flow inlets, outlets, and pressure ports, then swell and cause clogs. To minimize Nafion induced clogging, the flow cell orifices were fitted with specific screening near outlets and inlets, then pressur e ports were fitted with probes. The Effect of Flow Velocity Hydraulic conductivity changes as the Nafion properties change. It was found that changing flow velocity led to changes in hydraulic conductivity which took a significant amount of time to he flow rate. Even during Nafion hydration, the flow rate should match that of the experiment. The Effect of Ionic Concentration Ionic strength has a huge effect on the swelling potential of Nafion. Higher salt contents limit the swelling of the Nafion Higher salt concentrations lead to higher porosity. The effect is less pronounced at ionic strengths above 0.05M. At lower salt concentrations, the Nafion is extremely sensitive. Variations of salt content as low as 0.1% were shown to throw off Nafio n hydraulic conductivity equilibrium. The Effect of Temperature It would seem that temperature also affects the swelling potential of Nafion. Care should be taken to ensure stable temperatures during experiments.

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81 Water Jewel Blank Test Purpose Water j ewels would seem to be a suitable index matched porous media on which bio films can be cultivated, and then analyzed for fractal dimension by static light scattering. To accomplish this, bio films will be grown on water jewels then sent to our lab for ana lysis. One assemblage of water jewels will be used for bio film growth, while another will be used as a blank (bio film free) to use for the SLS data analysis. The concern is that index matching of fluid and media is not perfect, so water jewel packing d ifferences between the two sets of water jewels could cause the blank to be non representative of the sample containing bio films. Methods A column will be loosely packed with hydrated water jewels, and then filled with deionized water. SLS scans will be performed on the column at three amplification levels: 0.25, 0.45, and 0.65 amp. The column will then be removed from the apparatus, inverted several times to redistribute the water jewels, and then rescanned at the same amplifications. The data will the n be analyzed. If there are no major discrepancies between the two sets of scans, it follows that water jewels can be used as a blank and should be suitable for bio film fractal dimension measurement. Results 1E 13 1E 12 1E 11 0.0001 0.001 0.01 Intensity, I' (mV) Q (nm^ 1) Water Jewel Blank Test, 0.25 Amp Scan 1 Scan 2, Agitated 1E 12 1E 11 1E 10 1E 09 1E 08 0.0001 0.001 0.01 Intensity, I' (mV) Q (nm^ 1) Water Jewel Blank Test, 0.45 Amp Scan 1 Scan 2, Agitated

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82 Interpretation It appears that water jewel packing has little effect on SLS measurement. Any differences between the two scan sets appear to be noise since they are not repeated at different amplifications. For comparison, a plot of a Nafion blank has been included, showing that the Nafion scatters substantially more light than the water jewels. Also, the water jewels have a transmission factor of about 86%, which is very good, especially when compared with the Nafion which is closer to 10%. The conclusion is that water jewels should work very well for the bio film scans. Further Information Prior to this experiment, Ben Gilbert asked if the water jewels could be sterilized. So dehydrated water jewels were placed in an autoclave. After sterilization the water jewels were hydrated with dei onized water. Upon visual inspection, the water jewels appeared unaffected by the sterilization process. Water jewels are very sensitive to salt. Even at very low ionic concentrations, the water jewels do not swell to their normal size or have suitable i ndex matching when in a saline environment. Furthermore, water jewels are not rigid. For use in clogging experiments, this makes them useless. As deposits form, the water jewels would squish down from the vertical pressure, making SLS measurements worth less 1E 12 1E 11 1E 10 1E 09 1E 08 0.0000001 0.0001 0.001 0.01 Intensity, I' (mV) Q (nm^ 1) Water Jewel Blank Test, 0.65 Amp Scan 1 Scan 2, Agitated 1E 11 1E 10 1E 09 1E 08 0.0000001 0.0001 0.001 0.01 Intensity, I' (mV) Q (nm^ 1) Nafion Blank at 0.3 Amp Nafion Blank