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 fulfilment
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
ii
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 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 spacefilling 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
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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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DEDICATION
This thesis is dedicated to scientists who aren’t 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 it’s
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.
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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 couldn’t 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.
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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
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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
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Appendix
A. Experimental Data and Results……………………………………………………...……46
B. Additional Method Information………………………………………………………......75
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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
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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
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LIST OF TABLES
Table
1.1 Typical Values of Hydraulic Conductivity……………………………………………...…3
4.1 Porosity at various ionic concentration…………………………………………………...20
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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 1990’s 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
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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 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 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
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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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-Carman equation (Fitts, 2002):
where
is hydraulic conductivity,
porosity, and
is the unit weight divided by the viscosity of water,
is the median grain size of the media.
Hydraulic conductivity can also be calculated using the permeability
where
and
(Fitts, 2002):
are the unit weight and dynamic viscosity of water.
Finally, hydraulic conductivity is used to determine flow rate using Darcy’s Law:
4
is
is flow rate,
is manometer head difference over manometer distance s, and
is cross-sectional
area. Darcy’s 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 µ, and fluid density
ρ.
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:
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, is the energy from elevation above datum,
is velocity squared over doubled gravity and describes the energy supplied by fluid movement, and
is energy lost from friction.
Flow rate is the volume of fluid movement over time and can be calculated by taking crosssectional 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.
5
Specific deposit is another important consideration when looking at clogging. For the
purposes of this thesis, specific deposit, σ, is the volume of colloids Vc divided by the volume of the
measured area in the flow cell (total volume, Vt).
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 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 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)
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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.
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 Df is fractal dimension.
7
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, ko is a constant of proportionality assumed to be one for this
experiment,
is radius of gyration, α is colloid radius, and Df 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 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
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.
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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 1nm to
10µm. 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
waterjewels). 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, I, 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
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 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
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 IPA) and 58%
deionised water has the same index of refraction as the Nafion. The Nafion used in the experiment
was 16-35 mesh and the IPA/H2O mixture has a dynamic viscosity of 0.0027478
2007).
15
(Pang et al.
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/H2O 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 precalibrated 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 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-log plot. The absolute value of slope on the plot’s 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.
1/Rg
1/r
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 MgCl2
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
Intensity I" (mV)
1.00E-05
1.00E-06
155.1 ml Eluded
1.00E-07
315.4 ml Eluded
377.41 ml Eluded, No Flow
1.00E-08
1.00E-09
0.0001
782.4 ml Clear Soln. Eluded
0.001
0.01
0.1
Q (nm^-1)
Figure 4.1 IQ plot for middle region
I" vs Q, Mid Region
Intensity I" (mV)
1.00E-05
1.00E-06
1.00E-07
1.00E-08
1.00E-09
1.00E-10
0.001
0.01
Q (nm^-1)
0.1
y = 1E-12x-2.044
R² = 0.9952
155.1 ml Eluted
y = 1E-10x-1.62
R² = 0.9841
315.4 ml Eluted
y = 2E-09x-1.261
R² = 0.9608
377.41 ml Eluted,
No Flow
y = 1E-10x-1.587
R² = 0.9854
782.4 ml Clear
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, 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
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
3.5
Fractal Dimension
3.0
2.5
2.0
y = 1.4832x + 0.4316
R² = 0.2268
1.5
1.0
0.5
0.0
0
0.2
0.4
0.6
K/Ko
0.8
1
1.2
Figure 4.6 Fractal dimension versus normalized hydraulic conductivity
3.5
Fractal Dimension
3.0
2.5
2.0
1.5
1.0
0.5
0.0
0
500
1000
1500
2000
Pore Flow Velocity (m/day)
2500
Figure 4.7 Fractal dimension versus pore flow velocity
24
3000
3500
3.5
Fractal Dimension
3.0
2.5
2.0
1.5
1.0
0.5
0.0
0
0.01
0.02
0.03
Ionic Strength (M)
0.04
0.05
0.06
Figure 4.8 Fractal dimension versus ionic strength
3.5
Fractal Dimension
3.0
2.5
2.0
1.5
y = -0.0067x + 1.9077
R² = 0.083
1.0
0.5
0.0
0
20
40
60
Pore Volumes Eluted
80
Figure 4.9 Fractal dimension versus pore volumes eluted
25
100
120
3.5
2.5
y = -0.004x + 2.1147
R² = 0.6035
2.0
1.5
1.0
0.5
0.0
0
50
100
150
200
250
300
Specific Deposit (ppm)
350
400
450
Figure 4.10 Fractal dimension versus specific deposit
10
Reynold's Number
Fractal Dimension
3.0
1
0.0
0.5
1.0
1.5
2.0
2.5
3.0
0.1
0.01
Fractal Dimension
Figure 4.11 Reynolds number versus fractal dimension
26
3.5
500
1.2
1
K/Ko
0.8
0.6
0.4
y = -0.001x + 0.9219
R² = 0.4052
0.2
0
0
50
100
150
200
250
300
Specific Deposit (ppm)
350
400
450
500
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 the SLS apparatus
twice, once before repeated inversion and once after.
27
Fractal Dimension
2.6
2.4
2.2
Injection Well CD03
2
Injection Well G51
1.8
Monitor Well LR01
1.6
Monitor Well FP101
1.4
0
200
400
600
800
Flowrate (ml/min)
1000
Figure 4.13 Fractal dimension versus flow rate, Rifle samples
Fractal Dimension
2.6
2.4
2.2
Injection Well CD03
2
Injection Well G51
1.8
Monitor Well LR01
1.6
Monitor Well FP101
1.4
0.02
0.03
0.04
0.05
Ionic Strength (M)
0.06
Figure 4.14 Fractal dimension versus ionic strength, Rifle samples
Fractal Dimension
2.6
2.4
2.2
Injection Well CD03
2
Injection Well G51
1.8
Monitor Well LR01
1.6
Monitor Well FP101
1.4
0
5
10
15
Concentration (ppm)
20
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 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. 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
Fractal Dimension
region, pore velocity of 1197 m/day, ionic strength of 0.006 M, and exclude the clear flow regime.
2.4
2.2
2.0
1.8
1.6
1.4
1.2
1.0
y = -0.0099x + 2.3187
R² = 0.9931
0
10
20
30
40
Concentration (ppm)
50
Figure 4.16 Fractal dimension versus specific deposit
29
60
70
Fractal Dimension
2.4
2.2
2.0
1.8
1.6
1.4
y = 4.0061x - 1.7471
R² = 0.9909
1.2
1.0
0.86
0.88
0.9
0.92
0.94
K/Ko
0.96
0.98
1
1.02
1.02
1
0.98
0.96
0.94
0.92
0.9
0.88
0.86
y = -0.0025x + 1.0148
R² = 0.9998
0
10
20
30
40
Concentration (ppm)
50
60
70
Figure 4.18 Normalized hydraulic conductivity versus specific deposit
1.05
1
K/Ko
K/Ko
Figure 4.17 Fractal dimension versus normalized hydraulic conductivity
0.95
y = -0.001x + 1.066
R² = 0.982
0.9
0.85
0
50
100
150
200
Pore Volumes Eluted
250
Figure 4.19 Normalized hydraulic conductivity versus pore volumes eluted
30
300
Fractal Dimension
2.4
2.2
2.0
1.8
1.6
1.4
1.2
1.0
y = -0.0027x + 2.5151
R² = 0.9486
0
50
100
150
200
Pore Volumes Eluted
250
300
Specific Deposit (ppm)
Figure 4.20 Fractal dimension versus pore volumes eluted
80
y = 0.2741x - 20.44
R² = 0.979
60
40
20
0
0
50
100
150
200
Pore Volumes Eluted
250
300
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
Fractal Dimension
(a) Inlet Region
2.5
2
74 m/day
569 m/day
1.5
588 m/day
1
1439 m/day
0.5
0
400
600
Pore Volumes Eluted
800
3000 m/day
(b) Middle Region
Region
2.5
Fractal Dimension
200
2
74 m/day
569 m/day
1.5
1197 m/day
1
1439 m/day
0.5
0
200
400
600
Pore Volumes Eluted
800
3000 m/day
(c) Outlet Region
Fractal Dimension
2.5
2
74 m/day
138 m/day
1.5
569 m/day
1
1197 m/day
0.5
1439 m/day
0
200
400
600
Pore Volumes Eluted
800
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<CCC. Accordingly, the 3000
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
Specific Deposit (ppm)
300
250
200
74 m/day
150
569 m/day
100
588 m/day
50
1439 m/day
3000 m/day
0
0
200
400
600
800
Pore Volumes Eluted
(b) Middle Region
Region
Specific Deposit (ppm)
300
250
200
74 m/day
150
569 m/day
100
1197 m/day
1439 m/day
50
3000 m/day
0
0
200
400
600
Pore Volumes Eluted
800
(c) Outlet Region
Specific Deposit (ppm)
300
250
200
74 m/day
150
138 m/day
100
569 m/day
1197 m/day
50
1439 m/day
0
0
200
400
600
Pore Volumes Eluted
800
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
Fractal Dimension
2.5
2
74 m/day
569 m/day
1.5
588 m/day
1
1439 m/day
3000 m/day
0.5
0
100
150
200
Specific Deposit (ppm)
250
300
(b) Middle Region
Region
2.5
Fractal Dimension
50
2
74 m/day
569 m/day
1.5
1197 m/day
1
1439 m/day
3000 m/day
0.5
0
50
100
150
200
Specific Deposit (ppm)
250
300
(c) Outlet Region
Fractal Dimension
2.5
2
74 m/day
138 m/day
1.5
569 m/day
1
1197 m/day
1439 m/day
0.5
0
50
100
150
200
Specific Deposit (ppm)
250
300
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
1.1
1
K/Ko
0.9
74 m/day
0.8
569 m/day
0.7
588 m/day
0.6
1439 m/day
0.5
3000 m/day
0.4
0.5
1
1.5
Fractal Dimension
2
2.5
(b) Middle Region
Region
1.1
1
K/Ko
0.9
74 m/day
0.8
569 m/day
0.7
1197 m/day
0.6
1439 m/day
0.5
3000 m/day
0.4
0.5
1
1.5
Fractal Dimension
2
2.5
(c) Outlet Region
1.1
1
K/Ko
0.9
74 m/day
0.8
138 m/day
0.7
569 m/day
0.6
1197 m/day
0.5
1439 m/day
0.4
0.5
1
1.5
Fractal Dimension
2
2.5
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
1.1
1
K/Ko
0.9
74 m/day
0.8
569 m/day
0.7
588 m/day
0.6
1439 m/day
0.5
3000 m/day
0.4
0
50
100
150
200
Specific Deposit (ppm)
250
300
(b) Middle Region
Region
1.1
1
K/Ko
0.9
74 m/day
0.8
569 m/day
0.7
1197 m/day
0.6
1439 m/day
0.5
3000 m/day
0.4
0
50
100
150
200
Specific Deposit (ppm)
250
300
(c) Outlet Region
1.1
1
K/Ko
0.9
74 m/day
0.8
138 m/day
0.7
569 m/day
0.6
1197 m/day
0.5
1439 m/day
0.4
0
50
100
150
200
Specific Deposit (ppm)
250
300
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
1.1
1
K/Ko
0.9
74 m/day
0.8
569 m/day
0.7
588 m/day
0.6
0.5
1439 m/day
0.4
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
Radius of Gyration (m)
3000 m/day
1.1
(b) Middle Region
Region
1
K/Ko
0.9
74 m/day
0.8
569 m/day
0.7
1197 m/day
0.6
1439 m/day
0.5
0.4
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
Radius of Gyration (m)
3000 m/day
(c) Outlet Region
1.1
1
K/Ko
0.9
74 m/day
0.8
138 m/day
0.7
569 m/day
0.6
0.5
1197 m/day
0.4
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
Radius of Gyration (m)
1439 m/day
Figure 4.27a-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 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 round of investigation. Keep in mind that radius of
gyration was calculated (not measured) with assumptions.
Fractal Dimension vs Specific Deposit
3
Fractal Dimension
2.5
74 m/day 0.049 M
138 m/day 0.049 M
2
292 m/day 0.048 M
569 m/day 0.048 M
1.5
588 m/day 0.024 M
1
691 m/day 0.012 M
1197 m/day 0.006 M
0.5
1439 m/day 0.006 M
3000 m/day 0.003 M
0
0
50
100
150
200
250
Specific Deposit (ppm)
300
350
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 the data sets, an overall
correlation unifying all data was still not clear.
38
K/Ko vs Radius of Gyration
1.1
1
K/Ko
0.9
0.8
74 m/day 0.049 M
0.7
y = -0.046ln(x) + 0.488
R² = 0.845
0.6
0.5
0.4
1.E-05
1.E-04
1.E-03
1.E-02
1.E-01
Radius of Gyration (m)
1.E+00
1.E+01
Figure 4.29 Normalized hydraulic conductivity versus radius of gyration, 74 m/day pore flow
velocity, 0.049M ionic strength.
K/Ko vs Radius of Gyration
1.1
1
K/Ko
0.9
0.8
138 m/day 0.049 M
0.7
y = -0.040ln(x) + 0.574
R² = 0.953
0.6
0.5
0.4
1.E-05
1.E-04
1.E-03
1.E-02
1.E-01
Radius of Gyration (m)
1.E+00
1.E+01
Figure 4.30 Normalized hydraulic conductivity versus radius of gyration, 138 m/day pore flow
velocity, 0.049M ionic strength.
39
K/Ko vs Radius of Gyration
1.1
1
K/Ko
0.9
0.8
292 m/day 0.048 M
0.7
y = -0.023ln(x) + 0.789
R² = 0.922
0.6
0.5
0.4
1.E-05
1.E-04
1.E-03
1.E-02
1.E-01
Radius of Gyration (m)
1.E+00
1.E+01
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
1.1
1
K/Ko
0.9
0.8
569 m/day 0.048 M
0.7
0.6
0.5
0.4
1.E-05
1.E-04
1.E-03
1.E-02
1.E-01
Radius of Gyration (m)
1.E+00
1.E+01
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
1.1
1
K/Ko
0.9
0.8
588 m/day 0.024 M
0.7
y = -0.029ln(x) + 0.772
R² = 0.977
0.6
0.5
0.4
1.E-05
1.E-04
1.E-03
1.E-02
1.E-01
Radius of Gyration (m)
1.E+00
1.E+01
Figure 4.33 Normalized hydraulic conductivity versus radius of gyration, 588 m/day pore flow
velocity, 0.024M ionic strength.
K/Ko vs Radius of Gyration
1.1
1
K/Ko
0.9
0.8
691 m/day 0.012 M
0.7
0.6
0.5
0.4
1.E-05
1.E-04
1.E-03
1.E-02
1.E-01
Radius of Gyration (m)
1.E+00
1.E+01
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
1.1
1
K/Ko
0.9
0.8
1197 m/day 0.006M
0.7
y = -0.046ln(x) + 0.576
R² = 0.908
0.6
0.5
0.4
1.E-05
1.E-04
1.E-03
1.E-02
1.E-01
Radius of Gyration (m)
1.E+00
1.E+01
Figure 4.35 Normalized hydraulic conductivity versus radius of gyration, 1197 m/day pore flow
velocity, 0.006M ionic strength.
K/Ko vs Radius of Gyration
1.1
1
K/Ko
0.9
0.8
1439 m/day 0.006 M
0.7
0.6
0.5
0.4
1.E-05
1.E-04
1.E-03
1.E-02
1.E-01
Radius of Gyration (m)
1.E+00
1.E+01
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 Darcy’s 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.
Grot, W.G. (1982). “Nafion Membrane and its Applications”. Electrochemistry in Industry, Springer,
U.S.
Izkander, Magued. (2010). Modelling with Transparent Soils, 1st Ed., Springer, Berlin.
Mays, D.C. (2007). “Using the Quirk-Schofield Diagram to Explain Environmental Colloid
Dispersion Phenomena” Journal of Natural Resources & Life Sciences Education, Volume
36, 45-52.
Mays, D. C. (2010). “Contrasting Clogging in Granular Media Filters, Soils, and Dead-End
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.
Mays, D.C., Cannon, O.T., Kanold, A.W., Harris, K.J., Lei, T.C., Gilbert, B. (2011). “Static light
scattering resolves colloid structure in index-matched porous media” Journal of Colloid and
Interface Science, doi:10.1016/j.jcis.2011.06.046.
Min, M., Dominik, C. Hovenier, J.W., de Koter, A., Waters, L.B.F.M. (2006). “The 10 µm
amorphous silicate feature of fractal aggregates and compact particles with complex shapes”
Astronomy and Astrophysics, 445, 1005-1014.
Mont-Eton, M.E. (2011). “Quantifying the Morphology of Colloid Deposition in Granular Media
using Fractal Dimension” MS thesis U of Colorado, Denver.
Pang, F.M., Seng, C.E., Teng, T.T., Hakimi, M. (2007). “Densities and Viscosities of Aqueous
1-Propanol and 2-Propanol Solutions at Various Temperatures” U of Sains, Malaysia.
Sorensen, C. M., (2001). “Light Scattering by Fractal Aggregates: A Review” Aerosol Science and .
Technology, 35(2), 648-655.
45
Appendix A
Experimental Data and Results
Morphology Parameter vs K/Ko
0.0018
Morphology Parameter (ppm^-1)
0.0016
0.0014
0.0012
0.001
0.0008
0.0006
0.0004
0.0002
0
-0.0002
0
0.2
0.4
0.8 y = -0.0011x1 + 0.0013 1.2
R² = 0.2134
0.6
K/Ko
Morphology Parameter vs Specific Deposit
0.0018
Morphology Parameter (ppm^-1)
0.0016
0.0014
0.0012
0.001
0.0008
0.0006
0.0004
0.0002
0
-0.0002
0
50
100
150
200
y = -1E-06x + 0.0005
R²250
= 0.0652 300
Specific Deposit (ppm)
46
350
Morphology Parameter vs Fractal
Dimension
Morphology Parameter (ppm^-1)
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
Fractal Dimension
2
2.5
3
K/Ko vs Morphology Parameter
1.1
1
K/Ko
74 m/day 0.049 M
0.9
138 m/day 0.049 M
0.8
292 m/day 0.048 M
569 m/day 0.048 M
0.7
588 m/day 0.024 M
0.6
691 m/day 0.012 M
1197 m/day 0.006M
0.5
1439 m/day 0.006 M
0.4
3000 m/day 0.003 M
0
0.001
0.002
0.003
Morphology Parameter
47
0.004
0.005
Sample ID
Flowrate
(ml/min)
Flow
Velocity
(m/day)
2012_03_001_A_6
2012_03_001_A_7
2012_03_001_A_11
2012_04_002_A_15
2012_05_001_A_12
2012_05_001_A_15
2012_05_001_A_21
2012_05_001_A_27
2012_06_001_A_12
2012_06_001_A_18
2012_06_001_A_24
2012_06_001_A_30
2012_06_002_A_24
2012_06_002_A_27
2012_06_002_A_30
2012_06_003_A_15
2012_06_003_A_21
2013_01_002_A_42
2013_01_002_A_48
2013_01_002_A_54
2013_01_002_A_88
2013_01_002_A_41
2013_01_002_A_47
2013_01_002_A_53
2013_01_002_A_82
2013_01_002_A_40
2013_01_002_A_46
2013_01_002_A_52
2013_01_002_A_75
2013_02_001_A_47
2013_02_001_A_56
2013_02_001_A_62
2013_02_002_A_20
2013_02_002_A_26
2013_02_002_A_47
2013_02_002_A_62
2013_02_002_A_22
2013_02_002_A_28
0.71
0.65
0.63
6.9
7
7
7
7
3.45
3.5
3.5
3.45
1.83
1.84
1.7
1.95
1.95
10.34
10.34
10.34
10.34
10.34
10.34
10.34
10.34
10.34
10.34
10.34
10.34
5.21
5.21
5.21
5.4
5.4
5.4
5.3
5.4
5.4
9.0
8.3
8.0
87.9
89.1
89.1
89.1
89.1
43.9
44.6
44.6
43.9
23.3
23.4
21.6
24.8
24.8
131.7
131.7
131.7
131.7
131.7
131.7
131.7
131.7
131.7
131.7
131.7
131.7
66.3
66.3
66.3
68.8
68.8
68.8
67.5
68.8
68.8
Average
Pore
Velocity
(m/day)
1197
1197
1197
1197
1197
1197
1197
1197
1197
1197
1197
1197
603
603
603
659
659
659
647
659
659
48
Ionic
Conc
(mM)
0
0
0
100
100
100
100
100
100
100
100
100
100
100
100
100
100
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
1.81
1.81
1.81
1.81
1.81
1.81
Ionic
Strength
(M)
0.006
0.006
0.006
0.006
0.006
0.006
0.006
0.006
0.006
0.006
0.006
0.006
0.006
0.006
0.006
0.00543
0.00543
0.00543
0.00543
0.00543
0.00543
Salt Type
Ca(NO3)2
Ca(NO3)2
Ca(NO3)2
Ca(NO3)2
Ca(NO3)2
Ca(NO3)2
Ca(NO3)2
Ca(NO3)2
Ca(NO3)2
Ca(NO3)2
Ca(NO3)2
Ca(NO3)2
Ca(NO3)2
Ca(NO3)2
MgCl2
MgCl2
MgCl2
MgCl2
MgCl2
MgCl2
MgCl2
MgCl2
MgCl2
MgCl2
MgCl2
MgCl2
MgCl2
MgCl2
MgCl2
MgCl2
MgCl2
MgCl2
MgCl2
MgCl2
MgCl2
Nafion
Size
(mesh)
60-100
60-100
60-100
16-35
16-35
16-35
16-35
16-35
16-35
16-35
16-35
16-35
16-35
16-35
16-35
16-35
16-35
16-35
16-35
16-35
16-35
16-35
16-35
16-35
16-35
16-35
16-35
16-35
16-35
16-35
16-35
16-35
16-35
16-35
16-35
16-35
16-35
16-35
2013_02_002_A_50
5.4
68.8
659
1.81
0.00543
Sample ID
Flowrate
(ml/min)
Flow
Velocity
(m/day)
Average
Pore
Velocity
(m/day)
Ionic
Conc
(mM)
2013_02_002_A_64
2013_02_002_A_24
2013_02_002_A_30
2013_02_002_A_53
2013_02_002_A_66
2013_03_001_A_26
2013_03_001_A_32
2013_03_001_A_47
2013_03_001_A_62
2013_03_001_A_28
2013_03_001_A_34
2013_03_001_A_50
2013_03_001_A_64
2013_03_001_A_36
2013_03_001_A_53
2013_03_001_A_66
2013_03_008_A_20
2013_03_008_A_26
2013_03_008_A_47
2013_03_008_A_62
2013_03_008_A_22
2013_03_008_A_28
2013_03_008_A_50
2013_03_008_A_64
2013_03_008_A_24
2013_03_008_A_30
2013_03_008_A_53
2013_03_008_A_66
2013_04_001_A_20
2013_04_001_A_26
2013_04_001_A_22
2013_04_001_A_24
2013_04_001_A_30
2013_04_018_A_20
2013_04_018_A_26
2013_04_018_A_32
2013_04_018_A_22
5.3
5.4
5.4
5.4
5.3
5.72
5.72
5.72
5.67
5.72
5.72
5.72
5.67
5.72
5.72
5.67
11.62
11.62
11.62
11.76
11.62
11.62
11.62
11.76
11.62
11.62
11.62
11.76
5.97
5.97
5.97
5.97
5.97
2.82
2.82
2.82
2.82
67.5
68.8
68.8
68.8
67.5
72.8
72.8
72.8
72.2
72.8
72.8
72.8
72.2
72.8
72.8
72.2
148.0
148.0
148.0
149.7
148.0
148.0
148.0
149.7
148.0
148.0
148.0
149.7
76.0
76.0
76.0
76.0
76.0
35.9
35.9
35.9
35.9
647
659
659
659
647
671
671
671
665
671
671
671
665
671
671
665
569
569
569
576
569
569
569
576
569
569
569
576
292
292
292
292
292
138
138
138
138
1.81
1.81
1.81
1.81
1.81
1.95
1.95
1.95
1.95
1.95
1.95
1.95
1.95
1.95
1.95
1.95
16.03
16.03
16.03
16.03
16.03
16.03
16.03
16.03
16.03
16.03
16.03
16.03
16.01
16.01
16.01
16.01
16.01
16.23
16.23
16.23
16.23
49
MgCl2
16-35
Ionic
Strength
(M)
Salt Type
Nafion
Size
(mesh)
0.00543
0.00543
0.00543
0.00543
0.00543
0.00585
0.00585
0.00585
0.00585
0.00585
0.00585
0.00585
0.00585
0.00585
0.00585
0.00585
0.04809
0.04809
0.04809
0.04809
0.04809
0.04809
0.04809
0.04809
0.04809
0.04809
0.04809
0.04809
0.04803
0.04803
0.04803
0.04803
0.04803
0.04869
0.04869
0.04869
0.04869
MgCl2
MgCl2
MgCl2
MgCl2
MgCl2
MgCl2
MgCl2
MgCl2
MgCl2
MgCl2
MgCl2
MgCl2
MgCl2
MgCl2
MgCl2
MgCl2
MgCl2
MgCl2
MgCl2
MgCl2
MgCl2
MgCl2
MgCl2
MgCl2
MgCl2
MgCl2
MgCl2
MgCl2
MgCl2
MgCl2
MgCl2
MgCl2
MgCl2
MgCl2
MgCl2
MgCl2
MgCl2
16-35
16-35
16-35
16-35
16-35
16-35
16-35
16-35
16-35
16-35
16-35
16-35
16-35
16-35
16-35
16-35
16-35
16-35
16-35
16-35
16-35
16-35
16-35
16-35
16-35
16-35
16-35
16-35
16-35
16-35
16-35
16-35
16-35
16-35
16-35
16-35
16-35
2013_04_018_A_28
2013_04_018_A_50
2013_04_018_A_64
2013_04_018_A_24
2.82
2.82
2.82
2.82
35.9
35.9
35.9
35.9
138
138
138
138
16.23
16.23
16.23
16.23
0.04869
0.04869
0.04869
0.04869
MgCl2
MgCl2
MgCl2
MgCl2
16-35
16-35
16-35
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
2013_04_018_A_53
2013_04_018_A_66
2013_06_002_A_20
2013_06_002_A_26
2013_06_002_A_32
2013_06_002_A_22
2013_06_002_A_28
2013_06_002_A_50
2013_06_002_A_64
2013_06_002_A_24
2013_06_002_A_30
2013_06_002_A_53
2013_06_002_A_66
2013_08_001_A_20
2013_08_001_A_26
2013_08_001_A_47
2013_08_001_A_62
2013_08_001_A_22
2013_08_001_A_28
2013_08_001_A_50
2013_08_001_A_64
2013_08_001_A_24
2013_08_001_A_30
2013_08_001_A_53
2013_08_001_A_66
2013_08_002_A_20
2013_08_002_A_26
2013_08_002_A_47
2013_08_002_A_62
2013_08_002_A_22
2013_08_002_A_28
2013_08_002_A_50
2013_08_002_A_64
2.82
2.82
2.82
12
12
12
12
12
12
12
12
12
12
12
11.86
11.86
11.86
11.86
11.86
11.86
11.86
11.86
11.86
11.86
11.86
11.86
12.53
12.53
12.53
12.53
12.53
12.53
12.53
12.53
35.9
35.9
35.9
152.8
152.8
152.8
152.8
152.8
152.8
152.8
152.8
152.8
152.8
152.8
151.0
151.0
151.0
151.0
151.0
151.0
151.0
151.0
151.0
151.0
151.0
151.0
159.5
159.5
159.5
159.5
159.5
159.5
159.5
159.5
138
138
138
588
588
588
588
588
588
588
588
588
588
588
690
690
690
690
690
690
690
690
690
690
690
690
1439
1439
1439
1439
1439
1439
1439
1439
16.23
16.23
16.23
8.027
8.027
8.027
8.027
8.027
8.027
8.027
8.027
8.027
8.027
8.027
3.953
3.953
3.953
3.953
3.953
3.953
3.953
3.953
3.953
3.953
3.953
3.953
2.016
2.016
2.016
2.016
2.016
2.016
2.016
2.016
0.04869
0.04869
0.04869
0.024081
0.024081
0.024081
0.024081
0.024081
0.024081
0.024081
0.024081
0.024081
0.024081
0.024081
0.011859
0.011859
0.011859
0.011859
0.011859
0.011859
0.011859
0.011859
0.011859
0.011859
0.011859
0.011859
0.006048
0.006048
0.006048
0.006048
0.006048
0.006048
0.006048
0.006048
MgCl2
MgCl2
MgCl2
MgCl2
MgCl2
MgCl2
MgCl2
MgCl2
MgCl2
MgCl2
MgCl2
MgCl2
MgCl2
MgCl2
MgCl2
MgCl2
MgCl2
MgCl2
MgCl2
MgCl2
MgCl2
MgCl2
MgCl2
MgCl2
MgCl2
MgCl2
MgCl2
MgCl2
MgCl2
MgCl2
MgCl2
MgCl2
MgCl2
MgCl2
16-35
16-35
16-35
16-35
16-35
16-35
16-35
16-35
16-35
16-35
16-35
16-35
16-35
16-35
16-35
16-35
16-35
16-35
16-35
16-35
16-35
16-35
16-35
16-35
16-35
16-35
16-35
16-35
16-35
16-35
16-35
16-35
16-35
16-35
50
2013_08_002_A_24
2013_08_002_A_30
2013_08_002_A_53
2013_08_002_A_66
2013_08_003_A_20
2013_08_003_A_26
2013_08_003_A_47
12.53
12.53
12.53
12.53
11.63
11.63
11.63
159.5
159.5
159.5
159.5
148.1
148.1
148.1
Sample ID
Flowrate
(ml/min)
Flow
Velocity
(m/day)
2013_08_003_A_62
2013_08_003_A_22
2013_08_003_A_28
2013_08_003_A_50
2013_08_003_A_64
2013_08_003_A_24
2013_08_003_A_30
2013_08_003_A_53
2013_08_003_A_66
2013_09_001_A_20
2013_09_001_A_26
2013_09_001_A_47
2013_09_001_A_62
2013_09_001_A_22
2013_09_001_A_28
2013_09_001_A_50
2013_09_001_A_64
2013_09_001_A_24
2013_09_001_A_30
2013_09_001_A_53
2013_09_001_A_66
2013_09_002_A_20
2013_09_002_A_26
2013_09_002_A_47
2013_09_002_A_62
2013_09_002_A_22
2013_09_002_A_28
2013_09_002_A_50
2013_09_002_A_64
2013_09_002_A_24
2013_09_002_A_30
2013_09_002_A_53
11.63
11.63
11.63
11.63
11.63
11.63
11.63
11.63
11.63
11.78
11.78
11.78
11.78
11.78
11.78
11.78
11.78
11.78
11.78
11.78
11.78
1.512
1.512
1.512
1.528
1.512
1.512
1.512
1.528
1.512
1.512
1.512
148.1
148.1
148.1
148.1
148.1
148.1
148.1
148.1
148.1
150.0
150.0
150.0
150.0
150.0
150.0
150.0
150.0
150.0
150.0
150.0
150.0
19.3
19.3
19.3
19.5
19.3
19.3
19.3
19.5
19.3
19.3
19.3
1439
1439
1439
1439
Average
Pore
Velocity
(m/day)
3000
3000
3000
3000
3000
3000
3000
3000
3000
3000
3000
3000
74
74
74
75
74
74
74
75
74
74
74
51
2.016
2.016
2.016
2.016
1.011
1.011
1.011
0.006048
0.006048
0.006048
0.006048
0.003033
0.003033
0.003033
MgCl2
MgCl2
MgCl2
MgCl2
MgCl2
MgCl2
MgCl2
16-35
16-35
16-35
16-35
16-35
16-35
16-35
Ionic
Conc
(mM)
Ionic
Strength
(M)
Salt Type
Nafion
Size
(mesh)
1.011
1.011
1.011
1.011
1.011
1.011
1.011
1.011
1.011
0.983
0.983
0.983
0.983
0.983
0.983
0.983
0.983
0.983
0.983
0.983
0.983
16.254
16.254
16.254
16.254
16.254
16.254
16.254
16.254
16.254
16.254
16.254
0.003033
0.003033
0.003033
0.003033
0.003033
0.003033
0.003033
0.003033
0.003033
0.002949
0.002949
0.002949
0.002949
0.002949
0.002949
0.002949
0.002949
0.002949
0.002949
0.002949
0.002949
0.048762
0.048762
0.048762
0.048762
0.048762
0.048762
0.048762
0.048762
0.048762
0.048762
0.048762
MgCl2
MgCl2
MgCl2
MgCl2
MgCl2
MgCl2
MgCl2
MgCl2
MgCl2
MgCl2
MgCl2
MgCl2
MgCl2
MgCl2
MgCl2
MgCl2
MgCl2
MgCl2
MgCl2
MgCl2
MgCl2
MgCl2
MgCl2
MgCl2
MgCl2
MgCl2
MgCl2
MgCl2
MgCl2
MgCl2
MgCl2
MgCl2
16-35
16-35
16-35
16-35
16-35
16-35
16-35
16-35
16-35
16-35
16-35
16-35
16-35
16-35
16-35
16-35
16-35
16-35
16-35
16-35
16-35
16-35
16-35
16-35
16-35
16-35
16-35
16-35
16-35
16-35
16-35
16-35
2013_09_002_A_66
1.528
Sample ID
Nafion
Amount
(g)
2012_03_001_A_6
2012_03_001_A_7
2012_03_001_A_11
2012_04_002_A_15
2012_05_001_A_12
2012_05_001_A_15
2012_05_001_A_21
2012_05_001_A_27
2012_06_001_A_12
2012_06_001_A_18
2012_06_001_A_24
2012_06_001_A_30
2012_06_002_A_24
2012_06_002_A_27
2012_06_002_A_30
2012_06_003_A_15
2012_06_003_A_21
2013_01_002_A_42
2013_01_002_A_48
2013_01_002_A_54
2013_01_002_A_88
2013_01_002_A_41
2013_01_002_A_47
2013_01_002_A_53
2013_01_002_A_82
2013_01_002_A_40
2013_01_002_A_46
2013_01_002_A_52
2013_01_002_A_75
2013_02_001_A_47
2013_02_001_A_56
2013_02_001_A_62
2013_02_002_A_20
2013_02_002_A_26
2013_02_002_A_47
5.5
5.5
5.5
7
7
7
7
7
7
7
7
7
7
7
7
7
7
6.5
6.5
6.5
6.5
6.5
6.5
6.5
6.5
6.5
6.5
6.5
6.5
6.5
6.5
6.5
6.5
6.5
6.5
19.5
75
Porosity
Inlet
Colloid
Conc
(ppm)
Colloid
Size (nm)
125
125
125
12
125
125
125
125
125
125
125
125
125
125
125
125
125
125
125
125
125
125
125
125
125
125
125
125
125
125
125
125
136
136
136
99
99
99
99
99
99
99
99
99
99
99
99
99
99
99
99
99
106
106
106
106
106
106
106
106
106
106
106
106
106
106
106
106
106
106
0.11
0.11
0.11
0.11
0.11
0.11
0.11
0.11
0.11
0.11
0.11
0.11
0.11
0.11
0.11
0.10
0.10
0.10
52
16.254
0.048762
MgCl2
16-35
Pore Fluid
Colloid
Conc. (ppm)
Specific
Deposit
(ppm)
Flow
Cell
Position
50
179
181
111
13
67
114
60
6
33
58
44
11
12
20
6
42
151
255
255
255
255
255
255
255
255
255
255
255
255
255
255
255
255
255
790
790
790
790
580
580
580
580
255
255
255
255
790
790
790
790
790
790
451
1629
1649
1010
117
611
1035
543
52
301
523
403
95
108
181
60
403
1447
2013_02_002_A_62
2013_02_002_A_22
2013_02_002_A_28
2013_02_002_A_50
6.5
6.5
6.5
6.5
0.10
0.10
0.10
0.10
136
136
136
136
106
106
106
106
1438
152
630
1629
150
16
66
170
790
580
580
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
2013_02_002_A_24
2013_02_002_A_30
2013_02_002_A_53
2013_02_002_A_66
2013_03_001_A_26
2013_03_001_A_32
2013_03_001_A_47
2013_03_001_A_62
2013_03_001_A_28
2013_03_001_A_34
2013_03_001_A_50
2013_03_001_A_64
2013_03_001_A_36
2013_03_001_A_53
2013_03_001_A_66
2013_03_008_A_20
2013_03_008_A_26
2013_03_008_A_47
2013_03_008_A_62
2013_03_008_A_22
2013_03_008_A_28
2013_03_008_A_50
2013_03_008_A_64
2013_03_008_A_24
2013_03_008_A_30
2013_03_008_A_53
2013_03_008_A_66
2013_04_001_A_20
2013_04_001_A_26
2013_04_001_A_22
2013_04_001_A_24
2013_04_001_A_30
2013_04_018_A_20
6.5
6.5
6.5
6.5
6.5
6.5
6.5
6.5
6.5
6.5
6.5
6.5
6.5
6.5
6.5
6.5
6.5
6.5
6.5
6.5
6.5
6.5
6.5
6.5
6.5
6.5
6.5
6.5
6.5
6.5
6.5
6.5
6.5
6.5
0.1043
0.1043
0.1
0.1
0.1
0.1
0.1
0.1
0.1
0.1
0.1
0.1
0.1
0.1
0.1
0.1085
0.26
0.26
0.26
0.26
0.26
0.26
0.26
0.26
0.26
0.26
0.26
0.26
0.26
0.26
0.26
0.26
0.26
0.26
136.4
136.4
136.4
136.4
136.4
127.9
127.9
127.9
127.9
127.9
127.9
127.9
127.9
127.9
127.9
127.9
124.3
124.3
124.3
124.3
124.3
124.3
124.3
124.3
124.3
124.3
124.3
124.3
124.5
124.5
124.5
124.5
124.5
61.4
106.0
106.0
106.0
106.0
106.0
106.0
106.0
106.0
106.0
106.0
106.0
106.0
106.0
106.0
106.0
106
106
106
106
106
106
106
106
106
106
106
106
106
106
106
106
106
106
106
1669.4
130.2
445.022706
1157.50777
1193.99509
117.895408
340.773621
817.642166
843.416141
107.414029
320.264434
618.380274
614.553791
130.205251
224.829012
227.637498
115.421252
493.106914
1104.15305
863.504878
99.478794
360.065798
748.501064
616.274211
159.88613
455.177266
706.908938
516.183659
91.3034289
834.386801
233.174931
246.894153
1110.48366
56.1618
174.1
13.6
46.415868
120.72806
124.53369
12.791652
36.973938
88.714175
91.510651
11.654422
34.748691
67.09426
66.679086
14.12727
24.393948
24.698669
30.009525
128.2078
287.07979
224.51127
25.864486
93.617108
194.61028
160.23129
41.570394
118.34609
183.79632
134.20775
23.738892
216.94057
60.625482
64.19248
288.72575
14.602068
580
255
255
255
255
790
790
790
790
580
580
580
580
255
255
255
790
790
790
790
580
580
580
580
255
255
255
255
790
790
580
255
255
790
53
2013_04_018_A_26
2013_04_018_A_32
2013_04_018_A_22
2013_04_018_A_28
2013_04_018_A_50
2013_04_018_A_64
2013_04_018_A_24
6.5
6.5
6.5
6.5
6.5
6.5
6.5
0.26
0.26
0.26
0.26
0.26
0.26
0.26
61.4
61.4
61.4
61.4
61.4
61.4
61.4
106
106
106
106
106
106
106
605.794477
1142.68532
130.144726
609.26777
1245.00206
1129.69409
72.2251405
157.50656
297.09818
33.837629
158.40962
323.70054
293.72046
18.778537
790
790
580
580
580
580
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
2013_04_018_A_53
2013_04_018_A_66
2013_06_002_A_20
2013_06_002_A_26
2013_06_002_A_32
2013_06_002_A_22
2013_06_002_A_28
2013_06_002_A_50
2013_06_002_A_64
2013_06_002_A_24
2013_06_002_A_30
2013_06_002_A_53
2013_06_002_A_66
2013_08_001_A_20
2013_08_001_A_26
2013_08_001_A_47
2013_08_001_A_62
2013_08_001_A_22
2013_08_001_A_28
2013_08_001_A_50
2013_08_001_A_64
2013_08_001_A_24
2013_08_001_A_30
2013_08_001_A_53
2013_08_001_A_66
2013_08_002_A_20
2013_08_002_A_26
2013_08_002_A_47
2013_08_002_A_62
2013_08_002_A_22
6.5
6.5
6.5
6.5
6.5
6.5
6.5
6.5
6.5
6.5
6.5
6.5
6.5
6.5
6.5
6.5
6.5
6.5
6.5
6.5
6.5
6.5
6.5
6.5
6.5
6.5
6.5
6.5
6.5
6.5
6.5
0.26
0.26
0.26
0.26
0.26
0.26
0.26
0.26
0.26
0.26
0.26
0.26
0.26
0.26
0.2187075
0.2187075
0.2187075
0.2187075
0.2187075
0.2187075
0.2187075
0.2187075
0.2187075
0.2187075
0.2187075
0.2187075
0.11088
0.11088
0.11088
0.11088
0.11088
61.4
61.4
61.4
124.19
124.19
124.19
124.19
124.19
124.19
124.19
124.19
124.19
124.19
124.19
126.07
126.07
126.07
126.07
126.07
126.07
126.07
126.07
126.07
126.07
126.07
126.07
61.821
61.821
61.821
61.821
61.821
106
106
106
106
106
106
106
106
106
106
106
106
106
106
106
106
106
106
106
106
106
106
106
106
106
106
106
106
106
106
106
291.416916
671.455783
447.436983
77.3540639
432.34905
919.552733
126.477158
424.99696
1196.16146
914.310578
198.683041
493.106914
863.504878
723.261008
124.326416
1073.03726
2059.04019
1889.82418
214.012151
853.687663
1573.86966
1162.45281
251.165214
616.274211
1110.48366
546.554156
29.8
105
570
455
28.7
75.768398
174.5785
116.33362
20.112057
112.41075
239.08371
32.884061
110.49921
311.00198
237.72075
51.657591
128.2078
224.51127
188.04786
27.19112
234.6813
450.32753
413.31872
46.806063
186.70789
344.2171
254.23715
54.931716
134.78379
242.8711
119.53549
3.304224
11.6424
63.2016
50.4504
3.182256
255
255
255
790
790
790
580
580
580
580
255
255
255
255
790
790
790
790
580
580
580
580
255
255
255
255
790
790
790
790
580
54
2013_08_002_A_28
2013_08_002_A_50
2013_08_002_A_64
2013_08_002_A_24
2013_08_002_A_30
2013_08_002_A_53
2013_08_002_A_66
2013_08_003_A_20
2013_08_003_A_26
2013_08_003_A_47
6.5
6.5
6.5
6.5
6.5
6.5
6.5
6
6
6
Sample ID
Nafion
Amount
(g)
2013_08_003_A_62
2013_08_003_A_22
2013_08_003_A_28
2013_08_003_A_50
2013_08_003_A_64
2013_08_003_A_24
2013_08_003_A_30
2013_08_003_A_53
2013_08_003_A_66
2013_09_001_A_20
2013_09_001_A_26
2013_09_001_A_47
2013_09_001_A_62
2013_09_001_A_22
2013_09_001_A_28
2013_09_001_A_50
2013_09_001_A_64
2013_09_001_A_24
2013_09_001_A_30
2013_09_001_A_53
2013_09_001_A_66
2013_09_002_A_20
2013_09_002_A_26
2013_09_002_A_47
2013_09_002_A_62
2013_09_002_A_22
2013_09_002_A_28
2013_09_002_A_50
6
6
6
6
6
6
6
6
6
6.5
6.5
6.5
6.5
6.5
6.5
6.5
6.5
6.5
6.5
6.5
6.5
6.5
6.5
6.5
6.5
6.5
6.5
6.5
0.11088
0.11088
0.11088
0.11088
0.11088
0.11088
0.11088
Porosity
0.05
0.05
0.05
0.05
0.05
0.05
0.05
0.05
0.05
0.05
0.05
0.05
0.26
0.26
0.26
0.26
0.26
0.26
0.26
61.821
61.821
61.821
61.821
61.821
61.821
61.821
61.604
61.604
61.604
106
106
106
106
106
106
106
106
106
106
111
498
337
30.4
97.8
318
130
8.3
12.5
30.5
12.30768
55.21824
37.36656
3.370752
10.844064
35.25984
14.4144
580
580
580
255
255
255
255
790
790
790
Inlet
Colloid
Conc
(ppm)
Colloid
Size (nm)
Pore Fluid
Colloid
Conc. (ppm)
Specific
Deposit
(ppm)
Flow
Cell
Position
61.604
61.604
61.604
61.604
61.604
61.604
61.604
61.604
61.604
126.715
126.715
126.715
126.715
126.715
126.715
126.715
126.715
126.715
126.715
126.715
126.715
30.66
30.66
30.66
30.66
30.66
30.66
30.66
106
106
106
106
106
106
106
106
106
106
106
106
106
106
106
106
106
106
106
106
106
106
106
106
106
106
106
106
42.4
10.8
11.2
18.5
6.1
14.7
11.7
0
0
26.3
28.5
13.2
21.9
16.6
15.1
19.7
2.7
0
5.2
11.7
0
62
324
858
680
60
196
446
1.315
1.425
0.66
1.095
0.83
0.755
0.985
0.135
0
0.26
0.585
0
16.12
84.24
223.08
176.8
15.6
50.96
115.96
790
580
580
580
580
255
255
255
255
790
790
790
790
580
580
580
580
255
255
255
255
790
790
790
790
580
580
580
55
2013_09_002_A_64
2013_09_002_A_24
2013_09_002_A_30
2013_09_002_A_53
2013_09_002_A_66
6.5
6.5
6.5
6.5
6.5
Sample ID
Volume
Eluted (ml)
2012_03_001_A_6
2012_03_001_A_7
2012_03_001_A_11
2012_04_002_A_15
2012_05_001_A_12
2012_05_001_A_15
2012_05_001_A_21
2012_05_001_A_27
2012_06_001_A_12
2012_06_001_A_18
2012_06_001_A_24
2012_06_001_A_30
2012_06_002_A_24
2012_06_002_A_27
2012_06_002_A_30
2012_06_003_A_15
2012_06_003_A_21
2013_01_002_A_42
2013_01_002_A_48
2013_01_002_A_54
2013_01_002_A_88
2013_01_002_A_41
2013_01_002_A_47
2013_01_002_A_53
2013_01_002_A_82
2013_01_002_A_40
2013_01_002_A_46
2013_01_002_A_52
2013_01_002_A_75
2013_02_001_A_47
2013_02_001_A_56
33.166667
59.7
159.2
193.2
35
87.5
196
297.5
25.875
94.5
182
268.25
111.63
186.76
272.15
23.4
86.775
181
341
377
1320
155
315
377
1160
124
290
377
984
356
437
0.26
0.26
0.26
0.26
0.26
30.66
30.66
30.66
30.66
30.66
Clean
Bed
Head
Loss (cm
H2O)
Pore
Volumes
Eluted
106
106
106
106
106
Clean Bed K
(cm/min)
387
46.3
122
278
244
100.62
12.038
31.72
72.28
63.44
dH/dHo
Hyd Cond
(cm/min)
1.02
1.73
131.636364
248
274.181818
960
112.727273
229.090909
274.181818
843.636364
90.1818182
210.909091
274.181818
715.636364
258.909091
317.818182
56
6.5
6.5
6.5
6.5
10
10
10
10
45.4
45.4
45.4
45.4
1.75970048
1.75970048
1.75970048
1.75970048
2.28761062
2.28761062
2.28761062
2.28761062
0.75581849
0.75581849
0.75581849
0.75581849
1.07
1.46
1.61
0.908
1.027
1.359
1.53
1.16
0.999
1.072
1.15
1.054
1.649
1.21
1.09
1.94
2.227
1.683
1.5
1.967
0.757
0.7049
0.66
0.717
580
255
255
255
255
2013_02_001_A_62
2013_02_002_A_20
2013_02_002_A_26
2013_02_002_A_47
2013_02_002_A_62
2013_02_002_A_22
2013_02_002_A_28
2013_02_002_A_50
617
22
113
332
578
49
138
332
448.727273
16.8744008
86.6730585
254.650048
443.336529
37.5838926
105.848514
254.650048
Sample ID
Volume
Eluted (ml)
Pore
Volumes
Eluted
2013_02_002_A_64
2013_02_002_A_24
2013_02_002_A_30
2013_02_002_A_53
2013_02_002_A_66
2013_03_001_A_26
2013_03_001_A_32
2013_03_001_A_47
2013_03_001_A_62
2013_03_001_A_28
2013_03_001_A_34
2013_03_001_A_50
2013_03_001_A_64
2013_03_001_A_36
2013_03_001_A_53
2013_03_001_A_66
2013_03_008_A_20
2013_03_008_A_26
2013_03_008_A_47
2013_03_008_A_62
2013_03_008_A_22
2013_03_008_A_28
2013_03_008_A_50
2013_03_008_A_64
2013_03_008_A_24
2013_03_008_A_30
2013_03_008_A_53
2013_03_008_A_66
2013_04_001_A_20
2013_04_001_A_26
605
73
165
332
629
129
235
343
593
157
260
343
621
292
343
649
58
267
485
809
110
320
485
861
163
372
485
914
24
194
464.046021
55.9923298
126.558006
254.650048
482.454458
95.1152074
173.271889
252.903226
437.235023
115.760369
191.705069
252.903226
457.880184
215.299539
252.903226
478.525346
17.8461538
82.1538462
149.230769
248.923077
33.8461538
98.4615385
149.230769
264.923077
50.1538462
114.461538
149.230769
281.230769
7.38461538
59.6923077
57
3.8
3.8
3.8
3.8
11
11
11
1.57196088
1.57196088
1.57196088
1.54285049
1.08608206
1.08608206
1.08608206
1.04
1.28
1.88
1.99
1.101
1.32
1.95
1.516
1.22
0.835
0.775
0.98
0.825
0.557
Clean
Bed
Head
Loss (cm
H2O)
Clean Bed K
(cm/min)
dH/dHo
Hyd Cond
(cm/min)
11
15
15
15
15
1.06596943
1.19469027
1.19469027
1.19469027
1.17256637
1.964
1.13
1.245
1.52
1.5
0.543
1.055
0.959
0.787
0.782
1.1
1.1
1.1
1.1
7.4
7.4
7.4
7.4
9.6
9.6
9.6
9.6
1.99
1.99
11.6854385
11.6854385
11.6854385
11.8262269
3.47404927
3.47404927
3.47404927
3.51590529
4.01686947
4.01686947
4.01686947
4.06526549
3.31858407
3.31858407
1.015
1.105
1.17
1.22
1.03
1.11
1.18
1.248
1.05
1.135
1.26
1.21
0.996
1.22
11.515
10.57
9.99
9.7
2.6
2.4
2.27
2.189
3.81
3.54
3.42
3.35
3.32
2.71
2013_04_001_A_22
2013_04_001_A_24
2013_04_001_A_30
2013_04_018_A_20
2013_04_018_A_26
2013_04_018_A_32
2013_04_018_A_22
2013_04_018_A_28
2013_04_018_A_50
2013_04_018_A_64
2013_04_018_A_24
54
81
254
17
148
250
30
161
307
512
42
16.6153846
24.9230769
78.1538462
5.23076923
45.5384615
76.9230769
9.23076923
49.5384615
94.4615385
157.538462
12.9230769
5.16
6.45
6.45
1.14
1.14
1.14
2.56
2.56
2.56
2.56
3.3
2.55968306
3.07161967
3.07161967
2.73637634
2.73637634
2.73637634
2.43708518
2.43708518
2.43708518
2.43708518
2.83588093
1.06
1.1
1.36
1.1
1.418
1.77
1.14
1.5
2.02
1.83
1.144
2.42
2.79
2.26
2.5
1.93
1.54
2.12
1.62
1.21
1.33
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
2013_04_018_A_53
2013_04_018_A_66
2013_06_002_A_20
2013_06_002_A_26
2013_06_002_A_32
2013_06_002_A_22
2013_06_002_A_28
2013_06_002_A_50
2013_06_002_A_64
2013_06_002_A_24
2013_06_002_A_30
2013_06_002_A_53
2013_06_002_A_66
2013_08_001_A_20
2013_08_001_A_26
2013_08_001_A_47
2013_08_001_A_62
2013_08_001_A_22
2013_08_001_A_28
2013_08_001_A_50
2013_08_001_A_64
2013_08_001_A_24
2013_08_001_A_30
2013_08_001_A_53
2013_08_001_A_66
2013_08_002_A_20
175
307
527
54
216
372
114
264
492
780
162
318
492
834
47.4
214
513
810
113
267
513
863
160
320
513
916
43.9
53.8461538
94.4615385
162.153846
16.6153846
66.4615385
114.461538
35.0769231
81.2307692
151.384615
240
49.8461538
97.8461538
151.384615
256.615385
17.3382257
78.2780655
187.647886
296.286136
41.3337448
97.6646891
187.647886
315.672759
58.5256564
117.051313
187.647886
335.059383
31.6738817
3.3
3.3
3.3
2.8
2.8
2.8
14.1
14.1
14.1
14.1
2.83588093
2.83588093
2.83588093
4.74083439
4.74083439
4.74083439
1.88288458
1.88288458
1.88288458
1.88288458
1.367
1.71
1.517
1
1.068
1.27
1.002
1.095
1.245
1.233
2.07
1.66
1.87
4.73
4.437
3.733
1.88
1.719
1.514
1.527
6.4
6.4
6.4
6.4
18.9
18.9
18.9
18.9
28.6
28.6
28.6
28.6
5.5
2.04991704
2.04991704
2.04991704
2.04991704
1.3883036
1.3883036
1.3883036
1.3883036
1.37616808
1.37616808
1.37616808
1.37616808
2.52011263
1.2
1.12
1.49
1.54
1.03
1.19
1.43
1.3
1.07
1.21
1.33
1.202
1.012
1.7
1.83
1.38
1.34
1.34
1.16
0.97
1.07
1.28
1.14
1.04
1.145
2.49
58
2013_08_002_A_26
2013_08_002_A_47
2013_08_002_A_62
2013_08_002_A_22
2013_08_002_A_28
2013_08_002_A_50
2013_08_002_A_64
2013_08_002_A_24
2013_08_002_A_30
2013_08_002_A_53
2013_08_002_A_66
2013_08_003_A_20
2013_08_003_A_26
2013_08_003_A_47
213
520
807
119
269
520
859
157
326
520
918
46.5
209
521
Sample ID
Volume
Eluted (ml)
2013_08_003_A_62
2013_08_003_A_22
2013_08_003_A_28
2013_08_003_A_50
2013_08_003_A_64
2013_08_003_A_24
2013_08_003_A_30
2013_08_003_A_53
2013_08_003_A_66
2013_09_001_A_20
2013_09_001_A_26
2013_09_001_A_47
2013_09_001_A_62
2013_09_001_A_22
2013_09_001_A_28
2013_09_001_A_50
2013_09_001_A_64
2013_09_001_A_24
2013_09_001_A_30
2013_09_001_A_53
2013_09_001_A_66
2013_09_002_A_20
2013_09_002_A_26
2013_09_002_A_47
825
98.9
273
521
877
157
331
521
930
47.1
212
527
786
100
265
527
834
153
324
527
940
28
116
248
153.679654
375.180375
582.251082
85.8585859
194.083694
375.180375
619.76912
113.275613
235.209235
375.180375
662.337662
5.5
5.5
5.5
26.2
26.2
26.2
26.2
43.2
43.2
43.2
43.2
2.52011263
2.52011263
2.52011263
1.05806255
1.05806255
1.05806255
1.05806255
0.96254302
0.96254302
0.96254302
0.96254302
1.086
1.21
0.97
1.04
1.135
1.276
1.09
1.03
1.093
1.168
1.1
2.321
2.08
2.7
1.015
0.932
0.829
1.008
0.932
0.881
0.824
0.913
Pore
Volumes
Eluted
Clean
Bed
Head
Loss (cm
H2O)
Clean Bed K
(cm/min)
dH/dHo
Hyd Cond
(cm/min)
75.36
339.2
843.2
1257.6
160
424
843.2
1334.4
244.8
518.4
843.2
1504
8.61538462
35.6923077
76.3076923
7
7
7
7
30.5
30.5
30.5
30.5
44.5
44.5
44.5
44.5
0.9
0.9
0.9
1.86156764
1.86156764
1.86156764
1.86156764
0.85449006
0.85449006
0.85449006
0.85449006
0.87849259
0.87849259
0.87849259
0.87849259
1.85840708
1.85840708
1.85840708
1.01
0.99
0.986
0.929
0.998
0.991
0.985
0.955
1
0.998
0.988
0.97
1.13
1.38
2.13
1.844
1.88
1.889
2.007
0.856
0.863
0.868
0.896
0.878
0.88
0.889
0.906
1.645
1.34
0.873
59
2013_09_002_A_62
2013_09_002_A_22
2013_09_002_A_28
2013_09_002_A_50
2013_09_002_A_64
2013_09_002_A_24
2013_09_002_A_30
2013_09_002_A_53
2013_09_002_A_66
Sample ID
389
36.3
124
248
395
43.1
131
248
402
K/Ko
2012_03_001_A_6
2012_03_001_A_7
2012_03_001_A_11
2012_04_002_A_15
2012_05_001_A_12
2012_05_001_A_15
2012_05_001_A_21
2012_05_001_A_27
2012_06_001_A_12
2012_06_001_A_18
2012_06_001_A_24
2012_06_001_A_30
2012_06_002_A_24
2012_06_002_A_27
2012_06_002_A_30
2012_06_003_A_15
2012_06_003_A_21
2013_01_002_A_42
2013_01_002_A_48
2013_01_002_A_54
0.937
0.685
0.621
2013_01_002_A_88
2013_01_002_A_41
2013_01_002_A_47
2013_01_002_A_53
2013_01_002_A_82
1.102
0.973
0.736
0.655
0.86
2013_01_002_A_40
1.001
119.692308
11.1692308
38.1538462
76.3076923
121.538462
13.2615385
40.3076923
76.3076923
123.692308
Morph.
Parameter
(1/ppm)
7.33964E-05
0.000127875
0.000163131
-4.69449E05
0.000117608
0.000271192
0.000227605
0.000144301
-9.55625E06
60
0.9
1.7
1.7
1.7
1.7
1.8
1.8
1.8
1.8
1.87807276
1.96772514
1.96772514
1.96772514
1.98854763
2.78761062
2.78761062
2.78761062
2.81710914
1.85
1.12
1.44
1.96
1.82
1.03
1.25
1.43
1.39
1.01
1.75
1.35
1.01
1.09
2.7
2.23
1.96
2.02
Fractal
Dimension
95%
Confidence
Interval
(+/-)
Df CI
Df +
CI
Fractal Fit
Range (Q^-1)
2.957
3.01
3.076
2.906
2.466
2.187
1.815
1.984
2.96
2.297
1.964
2.118
2.081
2.524
2.928
2.36
1.825
1.853
1.009
0.91
0.086
0.076
0.061
0.159
0.065
0.053
0.041
0.057
0.131
0.051
0.035
0.046
0.14
0.123
0.114
0.031
0.048
0.04
0.082
0.074
2.87
2.93
3.02
2.75
2.4
2.13
1.77
1.93
2.83
2.25
1.93
2.07
1.94
2.4
2.81
2.33
1.78
1.81
0.93
0.84
3.04
3.09
3.14
3.07
2.53
2.24
1.86
2.04
3.09
2.35
2
2.16
2.22
2.65
3.04
2.39
1.87
1.89
1.09
0.98
0.002-0.01
0.002-0.01
0.002-0.01
0.002-0.006
0.005-0.02
0.005-0.02
0.005-0.02
0.005-0.02
0.005-0.02
0.005-0.02
0.005-0.02
0.005-0.02
0.005-0.02
0.005-0.02
0.005-0.02
0.002-0.02
0.002-0.02
0.002-0.02
0.002-0.02
0.002-0.02
1.375
2.044
1.62
1.261
1.588
0.057
0.034
0.05
0.061
0.047
1.32
2.01
1.57
1.2
1.54
1.43
2.08
1.67
1.32
1.64
0.002-0.02
0.002-0.02
0.002-0.02
0.002-0.02
0.002-0.02
2.25
0.036
2.21 2.29
0.002-0.02
2013_01_002_A_46
2013_01_002_A_52
2013_01_002_A_75
2013_02_001_A_47
2013_02_001_A_56
2013_02_001_A_62
2013_02_002_A_20
2013_02_002_A_26
2013_02_002_A_47
2013_02_002_A_62
2013_02_002_A_22
2013_02_002_A_28
2013_02_002_A_50
0.932
0.873
0.949
0.000119069
0.000134367
6.58116E-05
0.96
0.778
0.531
0.502
0.908
0.76
0.512
0.000341936
0.000331882
0.000257239
0.000286011
0.000325121
0.000233457
0.000244115
Sample ID
K/Ko
Morph.
Parameter
(1/ppm)
2013_02_002_A_64
2013_02_002_A_24
2013_02_002_A_30
2013_02_002_A_53
2013_02_002_A_66
2013_03_001_A_26
2013_03_001_A_32
2013_03_001_A_47
2013_03_001_A_62
2013_03_001_A_28
2013_03_001_A_34
2013_03_001_A_50
2013_03_001_A_64
2013_03_001_A_36
2013_03_001_A_53
2013_03_001_A_66
2013_03_008_A_20
2013_03_008_A_26
2013_03_008_A_47
2013_03_008_A_62
2013_03_008_A_22
2013_03_008_A_28
2013_03_008_A_50
2013_03_008_A_64
2013_03_008_A_24
0.509
0.883
0.803
0.658
0.667
0.000240592
0.000493
0.000260534
0.000201108
0.000187973
0.986
0.905
0.855
0.82
0.748
0.691
0.654
0.622
0.948
6.12917E-05
0.000103784
7.37906E-05
0.000120804
0.001570618
0.00056375
0.00031603
0.000434803
0.000169246
61
2.015
1.735
1.829
2.442
2.259
2.072
2.722
2.367
1.352
1.205
2.235
2.156
1.705
0.061
0.074
0.054
0.063
0.052
0.07
0.048
0.06
0.095
0.085
0.041
0.052
0.065
1.95
1.66
1.78
2.38
2.21
2
2.67
2.31
1.26
1.12
2.19
2.1
1.64
2.08
1.81
1.88
2.51
2.31
2.14
2.77
2.43
1.45
1.29
2.28
2.21
1.77
0.002-0.02
0.002-0.02
0.002-0.02
0.002-0.02
0.002-0.02
0.002-0.02
0.005-0.02
0.005-0.02
0.005-0.02
0.005-0.02
0.005-0.02
0.005-0.02
0.005-0.02
Fractal
Dimension
95%
Confidence
Interval
(+/-)
Df CI
Df +
CI
Fractal Fit
Range (Q^-1)
1.472
2.891
2.547
1.871
1.901
2.443
2.378
2.149
2.038
2.45
2.559
2.341
2.35
2.445
2.475
2.429
1.812
1.385
0.94
1.113
2.048
1.692
1.377
1.302
1.879
0.062
0.048
0.042
0.049
0.042
0.078
0.046
0.035
0.05
0.087
0.044
0.048
0.041
0.065
0.048
0.051
0.035
0.044
0.065
0.043
0.02
0.019
0.026
0.045
0.031
1.41
2.84
2.51
1.82
1.86
2.37
2.33
2.11
1.99
2.36
2.52
2.29
2.31
2.38
2.43
2.38
1.78
1.34
0.88
1.07
2.03
1.67
1.35
1.26
1.85
1.53
2.94
2.59
1.92
1.94
2.52
2.42
2.18
2.09
2.54
2.6
2.39
2.39
2.51
2.52
2.48
1.85
1.43
1.01
1.16
2.07
1.71
1.4
1.35
1.91
0.005-0.02
0.005-0.02
0.005-0.02
0.005-0.02
0.005-0.02
0.005-0.02
0.005-0.02
0.005-0.02
0.005-0.02
0.005-0.02
0.005-0.02
0.005-0.02
0.005-0.02
0.005-0.02
0.005-0.02
0.005-0.02
0.002-0.02
0.002-0.02
0.002-0.02
0.002-0.02
0.002-0.02
0.002-0.02
0.002-0.02
0.002-0.02
0.002-0.02
2013_03_008_A_30
2013_03_008_A_53
2013_03_008_A_66
0.881
0.852
0.824
2013_04_001_A_20
2013_04_001_A_26
2013_04_001_A_22
2013_04_001_A_24
2013_04_001_A_30
2013_04_018_A_20
2013_04_018_A_26
2013_04_018_A_32
2013_04_018_A_22
2013_04_018_A_28
2013_04_018_A_50
2013_04_018_A_64
2013_04_018_A_24
1.004
0.82
0.945
0.909
0.735
0.9
0.704
0.565
0.87
0.665
0.495
0.545
0.874
0.000143677
0.000117948
0.00019689
-2.18395E05
0.00012502
0.000123036
0.000197904
0.000149866
0.000963156
0.000316656
0.000289126
0.000554095
0.000371394
0.000338424
0.000313865
0.000964434
Sample ID
K/Ko
Morph.
Parameter
(1/ppm)
2013_04_018_A_30
2013_04_018_A_53
2013_04_018_A_66
2013_06_002_A_20
2013_06_002_A_26
2013_06_002_A_32
2013_06_002_A_22
2013_06_002_A_28
2013_06_002_A_50
2013_06_002_A_64
2013_06_002_A_24
2013_06_002_A_30
2013_06_002_A_53
2013_06_002_A_66
2013_08_001_A_20
2013_08_001_A_26
2013_08_001_A_47
2013_08_001_A_62
2013_08_001_A_22
2013_08_001_A_28
2013_08_001_A_50
2013_08_001_A_64
0.73
0.58
0.66
1
0.936
0.787
0.998
0.913
0.804
0.811
0.000584769
0.000466247
0.000516084
0
7.77677E-05
0.000138361
7.91845E-06
0.000109556
9.63493E-05
0.000120775
0.8
0.89
0.64
0.651
0.97
0.84
0.67
0.77
0.000949388
5.59141E-05
0.000121416
0.000126675
7.1707E-05
0.000106701
0.000140859
0.000120096
62
1.548
1.382
1.539
0.03
0.04
0.04
1.52 1.58
1.34 1.42
1.5 1.58
0.002-0.02
0.002-0.02
0.002-0.02
2.373
1.162
1.857
1.77
1.16
2.208
1.448
1.013
1.794
1.454
1.065
1.113
1.755
0.028
0.054
0.046
0.052
0.025
0.049
0.048
0.062
0.023
0.035
0.033
0.039
0.034
2.35
1.11
1.81
1.72
1.14
2.16
1.4
0.95
1.77
1.42
1.03
1.07
1.72
2.4
1.22
1.9
1.82
1.19
2.26
1.5
1.08
1.82
1.49
1.1
1.15
1.79
0.002-0.02
0.002-0.02
0.002-0.02
0.002-0.02
0.002-0.02
0.002-0.02
0.002-0.02
0.002-0.02
0.002-0.02
0.002-0.02
0.002-0.02
0.002-0.02
0.002-0.02
Fractal
Dimension
95%
Confidence
Interval
(+/-)
Df CI
Df +
CI
Fractal Fit
Range (Q^-1)
1.477
1.184
1.193
2
1.65
1.25
2.06
1.72
1.17
1.38
1.92
1.58
1.29
1.34
1.93
1.3
0.319
0.511
2.05
1.42
0.529
1.01
0.043
0.045
0.051
0.023
0.032
0.048
0.017
0.02
0.034
0.025
0.035
0.039
0.045
0.053
0.036
0.046
0.07
0.055
0.032
0.036
0.053
0.047
1.43
1.14
1.14
1.98
1.62
1.2
2.04
1.7
1.14
1.36
1.89
1.54
1.25
1.29
1.89
1.25
0.25
0.46
2.02
1.38
0.48
0.96
1.52
1.23
1.24
2.02
1.68
1.3
2.08
1.74
1.2
1.41
1.96
1.62
1.34
1.39
1.97
1.35
0.39
0.57
2.08
1.46
0.58
1.06
0.002-0.02
0.002-0.02
0.002-0.02
0.002-0.02
0.002-0.02
0.002-0.02
0.002-0.02
0.002-0.02
0.002-0.02
0.002-0.02
0.002-0.02
0.002-0.02
0.002-0.02
0.002-0.02
0.002-0.02
0.002-0.02
0.002-0.02
0.002-0.02
0.002-0.02
0.002-0.02
0.002-0.02
0.002-0.02
2013_08_001_A_24
2013_08_001_A_30
2013_08_001_A_53
2013_08_001_A_66
2013_08_002_A_20
2013_08_002_A_26
2013_08_002_A_47
0.93
0.83
0.735
0.83
0.988
0.92
0.827
2013_08_002_A_62
2013_08_002_A_22
2013_08_002_A_28
2013_08_002_A_50
2013_08_002_A_64
2013_08_002_A_24
2013_08_002_A_30
2013_08_002_A_53
2013_08_002_A_66
2013_08_003_A_20
2013_08_003_A_26
2013_08_003_A_47
1.03
0.96
0.881
0.782
0.915
0.97
0.914
0.856
0.91
Sample ID
2013_08_003_A_62
2013_08_003_A_22
2013_08_003_A_28
2013_08_003_A_50
2013_08_003_A_64
2013_08_003_A_24
2013_08_003_A_30
2013_08_003_A_53
2013_08_003_A_66
2013_09_001_A_20
2013_09_001_A_26
2013_09_001_A_47
2013_09_001_A_62
2013_09_001_A_22
2013_09_001_A_28
2013_09_001_A_50
2013_09_001_A_64
2013_09_001_A_24
2013_09_001_A_30
K/Ko
0.000147121
0.00015844
0.000149866
0.000178651
0.000405448
0.000174792
-3.22433E05
0.000589175
0.000262707
0.000134768
0.00047023
0.000254227
0.000371422
Morph.
Parameter
(1/ppm)
0.99
1.01
1.014
1.077
1.002
1.01
1.015
1.048
0.999
1.002
63
1.81
1.48
1.13
1.46
1.72
2
1.64
0.03
0.03
0.026
0.04
0.047
0.074
0.1
1.78
1.45
1.1
1.42
1.67
1.93
1.54
1.84
1.51
1.16
1.5
1.77
2.07
1.74
0.002-0.02
0.002-0.02
0.002-0.02
0.002-0.02
0.002-0.02
0.002-0.02
0.002-0.02
1.79
2.25
2.43
1.95
2.11
2.3
2.27
2.12
2.33
0.093
0.039
0.051
0.079
0.077
0.039
0.048
0.073
0.052
0.151
0.049
1.88
2.29
2.48
2.03
2.19
2.34
2.32
2.19
2.38
0
2.04
2.39
0.002-0.02
0.002-0.02
0.002-0.02
0.002-0.02
0.002-0.02
0.002-0.02
0.002-0.02
0.002-0.02
0.002-0.02
1.89
2.34
1.7
2.21
2.38
1.87
2.03
2.26
2.22
2.05
2.28
0
1.74
2.29
Fractal
Dimension
95%
Confidence
Interval
(+/-)
Df CI
Df +
CI
Fractal Fit
Range (Q^-1)
2.04
0.057
0.127
0.163
0.242
2.7
0.464
0.889
1.136
2.265
1.595
1.138
1.352
1.574
0.1574
0.1448
0.2435
0.1288
0.2205
0.2146
0.174
2.1
0
0
2.21
3.26
1.56
0
3.16
0
1.05
1.28
2.51
1.72
1.36
1.57
1.75
0
0
0
0.002-0.02
2.08
3.1
1.32
1.98
0
0
1.95
2.94
1.08
0
2.24
0
0.73
0.99
2.02
1.47
0.92
1.14
1.4
0
0
0
0.002-0.02
0.002-0.02
0.005-0.015
0.005-0.015
0.005-0.012
0.005-0.012
0.003-0.02
0.003-0.02
0.003-0.02
0.003-0.02
0.008-0.02
0.008-0.02
0.008-0.02
2013_09_001_A_53
2013_09_001_A_66
2013_09_002_A_20
2013_09_002_A_26
2013_09_002_A_47
2013_09_002_A_62
2013_09_002_A_22
2013_09_002_A_28
2013_09_002_A_50
2013_09_002_A_64
2013_09_002_A_24
2013_09_002_A_30
2013_09_002_A_53
2013_09_002_A_66
Sample ID
2012_03_001_A_6
2012_03_001_A_7
2012_03_001_A_11
2012_04_002_A_15
2012_05_001_A_12
2012_05_001_A_15
2012_05_001_A_21
2012_05_001_A_27
2012_06_001_A_12
2012_06_001_A_18
2012_06_001_A_24
2012_06_001_A_30
2012_06_002_A_24
2012_06_002_A_27
2012_06_002_A_30
2012_06_003_A_15
2012_06_003_A_21
2013_01_002_A_42
2013_01_002_A_48
2013_01_002_A_54
2013_01_002_A_88
2013_01_002_A_41
1.011
1.033
0.885
0.72
0.47
0.54
0.89
0.69
0.512
0.55
0.96
0.8
0.69
0.72
0.001015936
0.000550961
0.000534557
0.000530629
0.000999965
0.001040095
0.000891351
0.000900258
0.000445372
0.000967492
0.000733304
0.000731604
Straight
Transmission
(%)
0.7
0.1
0.1
0.2
5.6
2.044
1.554
1.092
1.142
1.721
1.584
1.363
1.423
2.297
2.1
1.785
1.864
Dyn.
Viscosity
Fluid, From
Pang
(kg/(m*s))
0.0027478
0.0027478
0.0027478
0.0027478
0.0027478
0.0027478
0.0027478
0.0027478
0.0027478
0.0027478
0.0027478
0.0027478
0.0027478
0.0027478
0.0027478
0.0027478
0.0027478
0.0027478
0.0027478
0.0027478
0.0027478
0.0027478
64
0.0382
0.0218
0.0255
0.0265
0.0497
0.0351
0.0291
0.0338
0.0436
0.0278
0.0351
0.0331
0
0
2.01
1.53
1.07
1.12
1.67
1.55
1.33
1.39
2.25
2.07
1.75
1.83
0
0
2.08
1.58
1.12
1.17
1.77
1.62
1.39
1.46
2.34
2.13
1.82
1.9
0.002-0.02
0.002-0.02
0.002-0.02
0.002-0.02
0.002-0.02
0.002-0.02
0.002-0.02
0.002-0.02
0.002-0.02
0.002-0.02
0.002-0.02
0.002-0.02
Clean Bed
d50 calc
with
Kozeny
Carmen
(m)
Reynolds
Number,
Clean Bed
d50
Aggregate
Radius of
Gyration (m)
0.00306899
0.00306899
0.00306899
0.00306899
0.00349919
1.590061815
1.590061815
1.590061815
1.590061815
1.812949406
0.00120099
18.9
162.9
0.070543303
0.00024343
2013_01_002_A_47
2013_01_002_A_53
2013_01_002_A_82
2013_01_002_A_40
2013_01_002_A_46
2013_01_002_A_52
2013_01_002_A_75
2013_02_001_A_47
2013_02_001_A_56
2013_02_001_A_62
2013_02_002_A_20
2013_02_002_A_26
2013_02_002_A_47
2013_02_002_A_62
2013_02_002_A_22
2013_02_002_A_28
2013_02_002_A_50
0.4
0.2
0.6
16
1.2
0.5
0.8
4.2
3.7
2.6
7.6
0.6
0.1
0.1
5.2
0.5
0.1
0.0027478
0.0027478
0.0027478
0.0027478
0.0027478
0.0027478
0.0027478
0.0027478
0.0027478
0.0027478
0.0027478
0.0027478
0.0027478
0.0027478
0.0027478
0.0027478
0.0027478
Sample ID
Straight
Transmission
(%)
Dyn.
Viscosity
Fluid, From
Pang
(kg/(m*s))
2013_02_002_A_64
2013_02_002_A_24
2013_02_002_A_30
2013_02_002_A_53
2013_02_002_A_66
2013_03_001_A_26
2013_03_001_A_32
2013_03_001_A_47
2013_03_001_A_62
2013_03_001_A_28
2013_03_001_A_34
2013_03_001_A_50
2013_03_001_A_64
2013_03_001_A_36
2013_03_001_A_53
2013_03_001_A_66
2013_03_008_A_20
2013_03_008_A_26
2013_03_008_A_47
2013_03_008_A_62
0.1
3.1
0.5
0.1
0.1
5.5
1
0.2
0.2
4.7
0.9
0.3
0.3
5.5
2
2.2
7.4
0.8
0.2
0.3
0.0027478
0.0027478
0.0027478
0.0027478
0.0027478
0.0027478
0.0027478
0.0027478
0.0027478
0.0027478
0.0027478
0.0027478
0.0027478
0.0027478
0.0027478
0.0027478
0.0027478
0.0027478
0.0027478
0.0027478
65
0.00349919
0.00349919
0.00349919
0.00201134
0.00201134
0.00201134
0.00201134
1.812949406
1.812949406
1.812949406
1.042085583
1.042085583
1.042085583
1.042085583
0.00316179
0.00316179
0.00316179
0.00313237
0.00262811
0.00262811
0.00262811
Clean Bed
d50 calc
with
Kozeny
Carmen
(m)
0.00260366
0.00275638
0.00275638
0.00275638
0.00273074
0.855507561
0.855507561
0.855507561
0.831853823
0.711105939
0.711105939
0.711105939
0.00180955
0.00180955
0.00180955
0.00182041
1.053594383
1.053594383
1.053594383
1.072692483
Reynolds
Number,
Clean Bed
d50
0.69144473
0.745814201
0.745814201
0.745814201
0.72519335
0.006130301
0.257430453
0.007198757
7.85844E-05
0.000438965
0.002588433
0.001288721
0.0
0.0
0.0
2.28959E-05
0.000126917
0.1
0.7
0.000129938
0.000334394
0.0
Aggregate
Radius of
Gyration (m)
0.037803485
2.09565E-05
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.000163405
6.33965E-05
7.25449E-05
8.3603E-05
0.001142425
0.070667964
132.2003646
3.670156468
2013_03_008_A_22
2013_03_008_A_28
2013_03_008_A_50
2013_03_008_A_64
2013_03_008_A_24
2013_03_008_A_30
2013_03_008_A_53
2013_03_008_A_66
2013_04_001_A_20
2013_04_001_A_26
2013_04_001_A_22
2013_04_001_A_24
2013_04_001_A_30
2013_04_018_A_20
2013_04_018_A_26
2013_04_018_A_32
2013_04_018_A_22
2013_04_018_A_28
2013_04_018_A_50
2013_04_018_A_64
2013_04_018_A_24
6.5
1
0.3
0.4
4.1
0.8
0.4
0.7
6.3
0.2
2.4
2.1
0.2
11.1
0.5
0.1
9
0.6
0.1
0.2
14.5
0.0027478
0.0027478
0.0027478
0.0027478
0.0027478
0.0027478
0.0027478
0.0027478
0.0027478
0.0027478
0.0027478
0.0027478
0.0027478
0.0027478
0.0027478
0.0027478
0.0027478
0.0027478
0.0027478
0.0027478
0.0027478
Sample ID
Straight
Transmission
(%)
Dyn.
Viscosity
Fluid, From
Pang
(kg/(m*s))
2013_04_018_A_30
2013_04_018_A_53
2013_04_018_A_66
2013_06_002_A_20
2013_06_002_A_26
2013_06_002_A_32
2013_06_002_A_22
2013_06_002_A_28
2013_06_002_A_50
2013_06_002_A_64
2013_06_002_A_24
2013_06_002_A_30
2013_06_002_A_53
2013_06_002_A_66
2013_08_001_A_20
2013_08_001_A_26
2
0.5
1.1
12.4
1
0.3
5.4
0.8
0.1
0.2
2.7
0.7
0.3
0.3
5.2
0.2
0.0027478
0.0027478
0.0027478
0.0027478
0.0027478
0.0027478
0.0027478
0.0027478
0.0027478
0.0027478
0.0027478
0.0027478
0.0027478
0.0027478
0.0027478
0.0027478
66
0.00098665
0.00098665
0.00098665
0.00099258
0.00106094
0.00106094
0.00106094
0.00106731
0.00096433
0.00096433
0.00084692
0.00092775
0.00092775
0.00087566
0.00087566
0.00087566
0.00082639
0.00082639
0.00082639
0.00082639
0.00089144
Clean Bed
d50 calc
with
Kozeny
Carmen
(m)
0.00089144
0.00089144
0.00089144
0.00115259
0.00115259
0.00115259
0.00072637
0.00072637
0.00072637
0.00072637
0.574472081
0.574472081
0.574472081
0.584885315
0.617724462
0.617724462
0.617724462
0.628921716
0.288466613
0.288466613
0.253344944
0.277525481
0.277525481
0.123731943
0.123731943
0.123731943
0.116769461
0.116769461
0.116769461
0.116769461
0.125961527
0.000336459
0.00454141
0.103856711
0.206086052
0.000951972
0.015199454
0.094559229
0.017751557
9.78218E-05
1.664349307
0.001309999
0.002224465
2.193772665
0.000137698
0.04410279
28.75836996
0.001350119
0.041854654
11.6751359
4.672322302
0.001209388
Reynolds
Number,
Clean Bed
d50
Aggregate
Radius of
Gyration (m)
0.0010372
0.0010372
0.616373682
0.616373682
0.125961527
0.125961527
0.125961527
0.693032259
0.693032259
0.693032259
0.436755022
0.436755022
0.436755022
0.436755022
0.020561448
1.005206277
0.630352498
0.000366077
0.006774995
0.533611598
0.000359255
0.004156715
2.012229437
0.116339697
0.000864803
0.012396401
0.308253184
0.15102743
0.000589769
0.282925571
2013_08_001_A_47
2013_08_001_A_62
2013_08_001_A_22
2013_08_001_A_28
2013_08_001_A_50
2013_08_001_A_64
2013_08_001_A_24
2013_08_001_A_30
2013_08_001_A_53
2013_08_001_A_66
2013_08_002_A_20
2013_08_002_A_26
2013_08_002_A_47
2013_08_002_A_62
2013_08_002_A_22
2013_08_002_A_28
2013_08_002_A_50
2013_08_002_A_64
2013_08_002_A_24
2013_08_002_A_30
2013_08_002_A_53
2013_08_002_A_66
2013_08_003_A_20
2013_08_003_A_26
2013_08_003_A_47
0.1
0.1
1.7
0.2
0.1
0.1
2.2
0.4
0.1
0.6
31.8
6.3
0.4
0.5
28.5
4.4
0.4
0.8
31.2
7.7
1.1
4.4
44.9
42.5
27.8
0.0027478
0.0027478
0.0027478
0.0027478
0.0027478
0.0027478
0.0027478
0.0027478
0.0027478
0.0027478
0.0027478
0.0027478
0.0027478
0.0027478
0.0027478
0.0027478
0.0027478
0.0027478
0.0027478
0.0027478
0.0027478
0.0027478
0.0027478
0.0027478
0.0027478
Sample ID
Straight
Transmission
(%)
Dyn.
Viscosity
Fluid, From
Pang
(kg/(m*s))
2013_08_003_A_62
2013_08_003_A_22
2013_08_003_A_28
2013_08_003_A_50
2013_08_003_A_64
2013_08_003_A_24
2013_08_003_A_30
2013_08_003_A_53
2013_08_003_A_66
2013_09_001_A_20
2013_09_001_A_26
2013_09_001_A_47
2013_09_001_A_62
24
53.9
50.2
42.4
37.8
60.2
59.8
62.5
54
31.7
31.4
30.7
31.7
0.0027478
0.0027478
0.0027478
0.0027478
0.0027478
0.0027478
0.0027478
0.0027478
0.0027478
0.0027478
0.0027478
0.0027478
0.0027478
67
0.0010372
0.0010372
0.00085356
0.00085356
0.00085356
0.00085356
0.00084982
0.00084982
0.00084982
0.00084982
0.00362548
0.00362548
0.00362548
0.00362548
0.00234916
0.00234916
0.00234916
0.00234916
0.00224061
0.00224061
0.00224061
0.00224061
0.616373682
0.616373682
0.507245461
0.507245461
0.507245461
0.507245461
0.505023613
0.505023613
0.505023613
0.505023613
2.276222514
2.276222514
2.276222514
2.276222514
1.474892651
1.474892651
1.474892651
1.474892651
1.406743164
1.406743164
1.406743164
1.406743164
1.06488E+21
20893601259
0.000445533
0.065045781
3724762065
26.1647877
0.001613166
0.029562767
2.998761227
0.032640061
0.000540176
0.000278526
0.005123412
0.001726338
6.04099E-05
6.25779E-05
0.000770819
0.000309685
5.31522E-05
9.74401E-05
0.000289244
9.07243E-05
Clean Bed
d50 calc
with
Kozeny
Carmen
(m)
Reynolds
Number,
Clean Bed
d50
Aggregate
Radius of
Gyration (m)
0.0109947
0.0109947
0.0109947
0.0109947
6.48972679
6.48972679
6.48972679
6.48972679
1.069505625
0.029620503
2.87895E-05
0.000557106
2013_09_001_A_22
2013_09_001_A_28
2013_09_001_A_50
2013_09_001_A_64
2013_09_001_A_24
2013_09_001_A_30
2013_09_001_A_53
2013_09_001_A_66
2013_09_002_A_20
2013_09_002_A_26
2013_09_002_A_47
2013_09_002_A_62
2013_09_002_A_22
2013_09_002_A_28
2013_09_002_A_50
2013_09_002_A_64
2013_09_002_A_24
2013_09_002_A_30
2013_09_002_A_53
2013_09_002_A_66
36.5
36.2
34.8
36.9
39
38.8
36.4
40.5
9.6
1.2
0.3
0.4
14
3
0.8
1
14.4
4.6
1.4
1.8
0.0027478
0.0027478
0.0027478
0.0027478
0.0027478
0.0027478
0.0027478
0.0027478
0.0027478
0.0027478
0.0027478
0.0027478
0.0027478
0.0027478
0.0027478
0.0027478
0.0027478
0.0027478
0.0027478
0.0027478
0.00744899
0.00744899
0.00744899
0.00744899
0.00755289
0.00755289
0.00755289
0.00755289
0.00072164
0.00072164
0.00072164
0.00072544
0.00074256
0.00074256
0.00074256
0.00074647
0.00088382
0.00088382
0.00088382
0.00088848
Sample ID
Comments
2012_03_001_A_6
2012_03_001_A_7
2012_03_001_A_11
2012_04_002_A_15
2012_05_001_A_12
2012_05_001_A_15
2012_05_001_A_21
2012_05_001_A_27
2012_06_001_A_12
2012_06_001_A_18
2012_06_001_A_24
2012_06_001_A_30
2012_06_002_A_24
2012_06_002_A_27
2012_06_002_A_30
2012_06_003_A_15
No Salt
4.396838481
4.396838481
4.396838481
4.396838481
4.458164156
4.458164156
4.458164156
4.458164156
0.05467226
0.05467226
0.05467226
0.055542366
0.056257292
0.056257292
0.056257292
0.057152623
0.06695957
0.06695957
0.06695957
0.068025228
0.017997839
0.00223531
0.000589363
0.000271591
0.011634635
5.163190695
1.882479892
0.001323948
0.006710885
0.082431212
0.040898899
9.335E-05
0.000298522
0.002173941
0.00129225
No Salt
No Salt
Questionable head data, due to changes in salt conc effect on Nafion
Questionable head data, due to changes in salt conc effect on Nafion
Questionable head data, due to changes in salt conc effect on Nafion
Questionable head data, due to changes in salt conc effect on Nafion, Clear started at 196 ml eluted
Volume clear eluded after deposition,
Head data taken before and after scan only
Head data taken before and after scan only
Head data taken before and after scan only, Clear started at 182 ml eluted
Volume clear eluded after deposition, same head data
Clear started at 188 ml eluted
Volume clear eluded after deposition, same head data
Later scans look bad
68
2012_06_003_A_21
2013_01_002_A_42
2013_01_002_A_48
2013_01_002_A_54
2013_01_002_A_88
2013_01_002_A_41
2013_01_002_A_47
2013_01_002_A_53
2013_01_002_A_82
2013_01_002_A_40
2013_01_002_A_46
2013_01_002_A_52
2013_01_002_A_75
2013_02_001_A_47
2013_02_001_A_56
2013_02_001_A_62
2013_02_002_A_20
2013_02_002_A_26
2013_02_002_A_47
2013_02_002_A_62
2013_02_002_A_22
2013_02_002_A_28
2013_02_002_A_50
Later scans look bad
deposition
deposition
No Flow, after deposition, Clear started at 377 ml eluted
clear flow with partial recycle
deposition
deposition
No Flow, after deposition, Clear started at 377 ml eluted
clear flow with partial recycle
deposition
deposition
No Flow, after deposition, Clear started at 377 ml eluted
clear flow with partial recycle
No Flow, after deposition, Nafion/salt problems, No Pressure Equilibrium, Clear Flow started at 356 ml eluted
clear flow, nafion problems, No Pressure Equilibrium
clear flow, nafion problems, No Pressure Equilibrium
deposition, Nafion Equil Not Great
deposition, Nafion Equil Not Great
deposition, no flow, Nafion Equil Not Great, Clear flow started at 332 ml eluted
Clear Flow, Nafion Equil Not Great
deposition, Nafion Equil Not Great
deposition, Nafion Equil Not Great
deposition, no flow, Nafion Equil Not Great, Clear flow started at 332 ml eluted
Sample ID
Comments
2013_02_002_A_64
2013_02_002_A_24
2013_02_002_A_30
2013_02_002_A_53
2013_02_002_A_66
2013_03_001_A_26
2013_03_001_A_32
2013_03_001_A_47
2013_03_001_A_62
2013_03_001_A_28
2013_03_001_A_34
2013_03_001_A_50
2013_03_001_A_64
2013_03_001_A_36
2013_03_001_A_53
Clear Flow, Nafion Equil Not Great
deposition, Nafion Equil Not Great
deposition, Nafion Equil Not Great
deposition, no flow, Nafion Equil Not Great, Clear flow started at 332 ml eluted
Clear Flow, Nafion Equil Not Great
deposition, bad head data
deposition, bad head data
deposition, no flow, bad head data, Clear flow started at 343 ml eluted
Clear Flow, bad head data
deposition, bad head data
deposition, bad head data
deposition, no flow, bad head data, Clear flow started at 343 ml eluted
Clear Flow, bad head data
deposition, bad head data
deposition, no flow, bad head data, Clear flow started at 343 ml eluted
69
2013_03_001_A_66
2013_03_008_A_20
2013_03_008_A_26
2013_03_008_A_47
2013_03_008_A_62
2013_03_008_A_22
2013_03_008_A_28
2013_03_008_A_50
2013_03_008_A_64
2013_03_008_A_24
2013_03_008_A_30
2013_03_008_A_53
2013_03_008_A_66
2013_04_001_A_20
2013_04_001_A_26
2013_04_001_A_22
2013_04_001_A_24
2013_04_001_A_30
2013_04_018_A_20
2013_04_018_A_26
2013_04_018_A_32
2013_04_018_A_22
2013_04_018_A_28
2013_04_018_A_50
2013_04_018_A_64
2013_04_018_A_24
Clear Flow, bad head data
deposition
deposition
deposition, no flow, Clear flow started at 485 ml eluted
Clear Flow
deposition
deposition
deposition, no flow, Clear flow started at 485 ml eluted
Clear Flow
deposition
deposition
deposition, no flow, Clear flow started at 485 ml eluted
Clear Flow
deposition, scan maxed out at later times
deposition
deposition
deposition
deposition
deposition, scan maxed out at later times
deposition
deposition, no flow
deposition
deposition
deposition, no flow, Clear flow started at 307 ml eluted
Clear Flow
deposition
Sample ID
Comments
2013_04_018_A_30
2013_04_018_A_53
2013_04_018_A_66
2013_06_002_A_20
2013_06_002_A_26
2013_06_002_A_32
2013_06_002_A_22
2013_06_002_A_28
2013_06_002_A_50
2013_06_002_A_64
2013_06_002_A_24
2013_06_002_A_30
deposition
deposition, no flow, Clear flow started at 307 ml eluted
Clear Flow
Deposittion flow, bad later data
Deposittion flow, bad later data
Deposittion flow, bad later data
deposition
deposition
deposition, no flow, Clear flow started at 492 ml eluted
Clear Flow
No Transducer DATA Dep Flow
No Transducer DATA Dep Flow
70
2013_06_002_A_53
2013_06_002_A_66
2013_08_001_A_20
2013_08_001_A_26
2013_08_001_A_47
2013_08_001_A_62
2013_08_001_A_22
2013_08_001_A_28
2013_08_001_A_50
2013_08_001_A_64
2013_08_001_A_24
2013_08_001_A_30
2013_08_001_A_53
2013_08_001_A_66
2013_08_002_A_20
2013_08_002_A_26
2013_08_002_A_47
2013_08_002_A_62
2013_08_002_A_22
2013_08_002_A_28
2013_08_002_A_50
2013_08_002_A_64
2013_08_002_A_24
2013_08_002_A_30
2013_08_002_A_53
2013_08_002_A_66
2013_08_003_A_20
2013_08_003_A_26
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
2013_08_003_A_22
2013_08_003_A_28
2013_08_003_A_50
2013_08_003_A_64
2013_08_003_A_24
2013_08_003_A_30
2013_08_003_A_53
2013_08_003_A_66
Clear Flow. , No Nafion Equilibrium
No Transducer DATA Dep Flow, No Flow, Clear flow started at 492 ml eluted
No Transducer DATA Clear Flow
deposition
deposition
deposition, no flow, Clear flow started at 513 ml eluted
Clear Flow.
deposition
deposition
deposition, no flow, , Clear flow started at 513 ml eluted
Clear Flow
deposition
deposition
deposition, no flow, Clear flow started at 513 ml eluted
Clear Flow
deposition
deposition
deposition, no flow, Clear flow started at 520 ml eluted
Clear Flow.
deposition
deposition
deposition, no flow, , Clear flow started at 520 ml eluted
Clear Flow
deposition
deposition
deposition, no flow, Clear flow started at 520 ml eluted
Clear Flow
deposition, No Nafion Equilibrium
deposition, No Nafion Equilibrium
deposition, No Nafion Equilibrium
deposition, No Nafion Equilibrium
deposition, no flow, , No Nafion Equilibrium , Clear flow started at 521 ml eluted
Clear Flow, No Nafion Equilibrium
deposition, No Nafion Equilibrium
deposition, No Nafion Equilibrium
deposition, no flow, No Nafion Equilibrium , Clear flow started at 521 ml eluted
Clear Flow, No Nafion Equilibrium
71
2013_09_001_A_20
2013_09_001_A_26
2013_09_001_A_47
2013_09_001_A_62
2013_09_001_A_22
2013_09_001_A_28
2013_09_001_A_50
2013_09_001_A_64
2013_09_001_A_24
2013_09_001_A_30
2013_09_001_A_53
2013_09_001_A_66
2013_09_002_A_20
2013_09_002_A_26
2013_09_002_A_47
2013_09_002_A_62
2013_09_002_A_22
2013_09_002_A_28
2013_09_002_A_50
2013_09_002_A_64
2013_09_002_A_24
2013_09_002_A_30
2013_09_002_A_53
2013_09_002_A_66
deposition
deposition
deposition, no flow, Clear flow started at 527 ml eluted
Clear Flow.
deposition
deposition
deposition, no flow, , Clear flow started at 527 ml eluted
Clear Flow, No Clear Linear Region for Df
deposition, No Clear Linear Region for Df
deposition, No Clear Linear Region for Df
deposition, no flow, No Clear Linear Region for Df, Clear flow started at 527 ml eluted
Clear Flow, No Clear Linear Region for Df
deposition
deposition
deposition, no flow, Clear flow started at 248 ml eluted
Clear Flow.
deposition
deposition
deposition, no flow, , Clear flow started at 248 ml eluted
Clear Flow
deposition
deposition
deposition, no flow, Clear flow started at 248 ml eluted
Clear Flow
72
Results From Rifle Samples
Collected 4-15-13
Well ID
Sample
#
Scan ID
LR01
LR01
LR01
LR01
FP101
FP101
FP101
CD03
CD03
CD03
CD03
G51
G51
G51
G51
2
2
3
3
6
6
7
10
10
11
11
14
14
15
15
2013_04_003_A_2
2013_04_003_B_1
2013_04_004_A_2
2013_04_004_B_2
2013_04_006_A_2
2013_04_006_B_1
2013_04_007_B_2
2013_04_009_A_2
2013_04_009_B_2
2013_04_010_A_2
2013_04_010_B_2
2013_04_012_A_2
2013_04_012_B_2
2013_04_013_A_2
2013_04_013_B_2
Well ID
pH
LR01
LR01
LR01
LR01
FP101
FP101
FP101
CD03
CD03
CD03
CD03
G51
G51
G51
G51
7.44
7.44
7.44
7.44
7.26
7.26
7.26
7.3
7.3
7.3
7.3
7.51
7.51
7.51
7.51
Settled
Flow
Colloid
Colloid
/
SLS
rate
Concentration Concentration
Agitated Amplification
(ml/min)
(g/ml)
(ppm)
Sample
Settled
0.65
650
1.86047E-05
18.60465116
Agitated
0.65
650
1.86047E-05
18.60465116
Settled
0.65
0
1.86047E-05
18.60465116
Agitated
0.65
0
1.86047E-05
18.60465116
Settled
0.65
640
6.74419E-06
6.744186047
Agitated
0.65
640
6.74419E-06
6.744186047
Agitated
0.65
0
6.74419E-06
6.744186047
Settled
0.45
880
1.51163E-05
15.11627907
Agitated
0.45
880
1.51163E-05
15.11627907
Settled
0.45
0
1.51163E-05
15.11627907
Agitated
0.45
0
1.51163E-05
15.11627907
Settled
0.45
450
1.81395E-05
18.13953488
Agitated
0.45
450
1.81395E-05
18.13953488
Settled
0.45
0
1.81395E-05
18.13953488
Agitated
0.45
0
1.81395E-05
18.13953488
Temperature Conductivity
(deg C)
(uS/cm)
10.8
10.8
10.8
10.8
9.4
9.4
9.4
9
9
9
9
8.2
8.2
8.2
8.2
1634
1634
1634
1634
3300
3300
3300
3100
3100
3100
3100
2785
2785
2785
2785
73
Ionic
Strength
(M)
Fractal
Dimension
R^2
95% Conf
Interv
0.026144
0.026144
0.026144
0.026144
0.0528
0.0528
0.0528
0.0496
0.0496
0.0496
0.0496
0.04456
0.04456
0.04456
0.04456
2.21
1.71
2.45
1.52
1.69
1.81
2.27
1.74
1.82
1.96
2.09
1.85
1.82
1.78
1.71
0.958
0.898
0.974
0.939
0.943
0.958
0.916
0.984
0.984
0.979
0.972
0.994
0.993
0.987
0.979
0.111
0.139
0.096
0.093
0.1
0.092
0.166
0.054
0.056
0.07
0.086
0.034
0.036
0.05
0.06
Well ID
LR01
LR01
LR01
LR01
FP101
FP101
FP101
CD03
CD03
CD03
CD03
G51
G51
G51
G51
Comments
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 O2 Injections
Ferric Oxide Colloids, Acetate and Dissolved O2 Injections
Ferric Oxide Colloids, Acetate and Dissolved O2 Injections
Ferric Oxide Colloids, Acetate and Dissolved O2 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: I’ vs Q^-1 for all scans (includes blank) from 1ppm to 300ppm, where I’ is the raw intensity
corrected for the transmission factor and the cross-sectional area of the scattering region, per Mays et
al. (2011).
I' vs q^-1
0.45 Amp All Sets
1E-05
0ppm 2012_10_001_A
1ppm 2012_10_002_A
1E-06
3ppm 2012_10_003_A
10ppm 2012_10_004_A
30ppm 2012_10_005_A
1E-07
100ppm 2012_11_001_A
I' (mV)
300ppm 2012_11_002_A
0 ppm 2012_11_004_A Duplicate
1 ppm 2012_11_005_A Duplicate
1E-08
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
1E-09
300 ppm 2012_11_010_A Duplicate
0 ppm 2012_12_001_A Triplicate
1 ppm 2012_12_002_A Triplicate
1E-10
3 ppm 2012_12_003_A Triplicate
10 ppm 2012_12_004_A Triplicate
30 ppm 2012_12_005_A Triplicate
1E-11
0.0001
100 ppm 2012_12_006_A Triplicate
0.001
q^-1 (nm^-1)
0.01
Table 1: I’ vs concentration.
Colloid
Concentration
(ppm)
0
0.802568218
2.407704655
8.025682183
24.07704655
80.25682183
240.7704655
I' at 1/r
1st Set
(mV)
7.96E-11
8.18E-11
9.90E-11
5.52E-10
5.89E-10
1.12E-09
2.23E-08
I' at 1/r
2nd Set
(mV)
7.01E-11
5.17E-11
7.17E-11
4.07E-10
3.60E-10
1.09E-09
2.87E-08
I' at 1/r
3rd Set
(mV)
5.26E-11
6.54E-11
6.84E-11
4.02E-10
5.47E-10
1.59E-09
3.07E-08
76
I' at 1/r
Standard
Average Deviation
(mV)
(mV)
6.74E-11 1.37E-11
6.63E-11 1.51E-11
7.97E-11 1.68E-11
4.54E-10 8.53E-11
4.99E-10 1.22E-10
1.27E-09 2.80E-10
2.72E-08 4.40E-09
300 ppm 2013_01_001_A Triplicate
Figure 2: I’ 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.
I' vs Concentration
1.00E-07
I' (mV)
1.00E-08
1st Set
1.00E-09
2nd Set
3rd Set
Average
1.00E-10
1.00E-11
0.1
1
10
100
Concentration (ppm)
1000
Table 2: I” vs concentration (blank has been subtracted), where I’’ = I’ – 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)
0.802568218
2.22E-12
-1.84E-11
1.28E-11
2.407704655
1.95E-11
1.65E-12
1.58E-11
8.025682183
4.73E-10
3.37E-10
3.49E-10
24.07704655
5.10E-10
2.90E-10
4.94E-10
80.25682183
1.04E-09
1.02E-09
1.54E-09
240.7704655
2.22E-08
2.86E-08
3.07E-08
77
I" at 1/r
Average
(mV)
-1.12E12
1.23E11
3.86E10
4.31E10
1.20E09
2.72E08
Standard
Deviation
(mV)
1.59E-11
9.41E-12
7.50E-11
1.23E-10
2.92E-10
4.41E-09
Figure 3: I” vs concentration
I" vs Concentration
1.00E-07
I' (mV)
1.00E-08
1st Set
1.00E-09
2nd Set
3rd Set
1.00E-10
Average
1.00E-11
0.1
1
10
100
Concentration (ppm)
1000
Figure 4: I” vs concentration average, with exponential trend-line and standard deviation error bars.
I" vs Concentration
1.00E-07
y = 3E-10e0.0187x
R² = 0.9976
I' (mV)
1.00E-08
1.00E-09
Average
Expon. (Average)
1.00E-10
1.00E-11
1
10
100
Concentration (ppm)
1000
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
1400
Concentration (ppm)
1200
y = 3E+06x0.515
R² = 0.9304
1000
800
2 mM
16 mM
600
All
8 mM
400
Power (All)
200
0
0
5E-08 0.0000001 1.5E-070.0000002 2.5E-070.0000003
I" (mV)
Figure 5 Concentration versus I”all 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 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 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, it’s 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-films can be
cultivated, and then analyzed for fractal dimension by static light scattering. To accomplish this, biofilms will be grown on water jewels then sent to our lab for analysis. 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 differences between the two sets of water jewels could cause the blank to be nonrepresentative 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 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
Intensity, I' (mV)
Water Jewel Blank Test, 0.25 Amp
1E-11
0.0001
0.001
0.01
Scan 1
1E-12
Scan 2, Agitated
1E-13
Q (nm^-1)
1E-08
Water Jewel Blank Test, 0.45 Amp
Intensity, I' (mV)
1E-09
0.0001
0.001
0.01
1E-10
Scan 1
Scan 2, Agitated
1E-11
1E-12
Q (nm^-1)
81
Intensity, I' (mV)
0.0000001
Water Jewel Blank Test, 0.65 Amp
1E-08
0.0001
1E-09
0.001
0.01
Scan 1
1E-10
Scan 2, Agitated
1E-11
1E-12
Q (nm^-1)
Nafion Blank at 0.3 Amp
Intensity, I' (mV)
0.0000001
1E-08
1E-09
Nafion Blank
1E-10
1E-11
0.0001
0.001
Q (nm^-1)
0.01
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