LINKING COLLOID DEPOSIT MORPHOLOGY AND CLOGGING

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

ii

This thesis for the Master of Science degree by

Eric James Roth

has been approved for the

Civil Engineering Program

by

David C. Mays, Chair

James C.Y. Guo

Tim C. Lei

November 12, 2013

iii

Roth, Eric James (M.S., Civil Engineering)

Linking Colloid Deposit Morphology and Clogging: Insights through Categorization by Fractal

Dimension

Thesis directed by Assistant Professor David C. Mays

ABSTRACT

Clogging is an important limitation to essentially any technology or environmental process

involving flow in porous media. Examples include (1) groundwater remediation, (2) managed or

natural aquifer recharge, (3) hydrocarbon reservoir damage, (4) head loss in water treatment filters,

(5) fouling in porous media reactors, and (6) nutrient flow for plants or bacteria. Clogging, that is, a

detrimental reduction in permeability, is a common theme in each of these examples. Clogging

results from a number of mechanisms, including deposition of colloidal particles (such as clay

minerals), which is the focus of this research.

Colloid deposits reduce porosity, which is recognized to play an important role in clogging, as

expressed in the Kozeny-Carman equation. However, recent research has demonstrated that colloid

deposit morphology is also a crucial variable in the clogging process. Accordingly, this thesis reports

a series of laboratory experiments with the goal of quantifying deposit morphology as a fractal

dimension, using an innovative technique based on static light scattering (SLS) in refractive index

matched (RIM) porous media. For experiments conducted at constant flow, with constant influent

suspension concentration, and initially clean porous media, results indicate that increased clogging is

associated with colloid deposits having smaller fractal dimensions, that is, more dendritic and space-

filling deposits. This result is consistent with previous research that quantified colloid deposit

morphology using an empirical parameter.

Clogging by colloid deposits also provides insight into the more complex clogging

mechanisms of bio clogging, mineralization, and bio mineralization. Although this line of work was

originally motivated by problems of clogging in groundwater remediation, the methods used and the

insight gained by correlating clogging with fractal dimension are expected to have relevance to other

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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

x

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

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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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velocity, 0.024 M ionic strength……………………………………………………..…41







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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

3

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,

is the unit weight divided by the viscosity of water, is

porosity, and is the median grain size of the media.

Hydraulic conductivity can also be calculated using the permeability (Fitts, 2002):

where and are the unit weight and dynamic viscosity of water.

Finally, hydraulic conductivity is used to determine flow rate using Darcy’s Law:

5

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 cross-

sectional area, A, multiplied by flow velocity, V.

Pore flow velocity is similar to V, but describes the velocity for the fluid passing through

porous media.

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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.

8

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

9

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

10

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

12

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’.

13

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

14

Figure 3.2 Experimental summary

3.2 Apparatus Components

3.2.1 Fluid Flow System

Flow begins with two peristaltic pumps with adjustable flow rate. One pump supplies flow

from a reservoir containing stable colloids, the other pump supplies flow from a reservoir containing a

salt solution. The two flows join at a confluence point downstream from the pumps at which point

mixing begins. Next, the flow enters the flow cell and flows through the porous media. Fluid exits

the flow cell and then continues into a graduated cylinder as waste.

Figure 3.3 and 3.4 Flow cell during operation and flow cell schematic (schematic by Ben Gilbert).

3.2.2 Static Light Scattering Bench

The static light 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.

15

Figure 3.5 Static light scattering setup (Mays et al. 2011)

3.2.3 Head Data System

Head loss is measured across the pressure ports on the flow cell. Tubing 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

(Pang et al.

2007).

16

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.

17

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 pre-

calibrated transducers, flow was initiated at the target flow rate with no colloids, and equilibrium was

checked. Equilibrium was assumed when the hydraulic conductivity was stable, this ensured that the

Nafion was not swelling or compressing. Next the SLS bench is calibrated by aligning the laser and

flow column. The flow cell undergoes a blank scan, with no colloids present, to be used in later

18

calculations. Deposition flow (flow with colloids) is then started, along with a stopwatch and data

logging. Scans are performed at different flow cell positions through the duration of deposition flow.

Flow is then stopped, and all regions of the flow cell are once again scanned. A clear flow (flow with

no colloids) is started and more scans are performed.

3.7 Data Analysis

3.7.1 Fractal Dimension

For fractal dimension measurements, the scattering intensity verses scattering wave vector

values are plotted on a log-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.

Figure 3.6 IQ plot for determination of fractal dimension (modified from Sorensen 2001)

1/Rg 1/r

19

Later in the data analysis, it was found that radius of gyration might be a key parameter for

consideration. Unfortunately, the radius of gyration for aggregates in the experiment were found at a

very low scattering angle, which could not be measured using our apparatus. Instead, radius of

gyration was calculated by 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.

20

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

(mM)

Ionic Strength

(mM)

Porosity

1 3 0.05

2 6 0.11

4 12 0.22

8 24 0.26

16 48 0.26

4.2 Individual Samples

A total of 23 flow cell samples were successfully analysed, with a total of 169 SLS scans.

While carrying out the experiment on individual samples, it became evident that certain reoccurring

behaviours were exhibited during each run. As an example, results from scans on 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

21

was collected for each scan and then analysed using the IQ plot. Notice that different flow types are

contained in the IQ plot. The first two scans are during colloid deposition, then one scan was

performed while flow was stopped, and finally one scan after a colloid free (clear) solution flow.

Figure 4.1 IQ plot for middle region

Figure 4.2 Linear region of IQ plot with slope equal to fractal dimension

Head loss and specific deposit data were collected simultaneously with the SLS scans. Notice

that head loss increases during colloid deposition flow, indicating clogging. Furthermore, specific

1.00E-09

1.00E-08

1.00E-07

1.00E-06

1.00E-05

0.0001 0.001 0.01 0.1

Inte

nsi

ty I

" (

mV

)

Q (nm^-1)

I" vs Q, Middle Region

155.1 ml Eluded

315.4 ml Eluded

377.41 ml Eluded, No Flow

782.4 ml Clear Soln. Eluded

y = 1E-12x-2.044

R² = 0.9952

y = 1E-10x-1.62

R² = 0.9841

y = 2E-09x-1.261

R² = 0.9608

y = 1E-10x-1.587

R² = 0.9854 1.00E-10

1.00E-09

1.00E-08

1.00E-07

1.00E-06

1.00E-05

0.001 0.01 0.1

Inte

nsi

ty I

" (

mV

)

Q (nm^-1)

I" vs Q, Mid Region

155.1 ml Eluted

315.4 ml Eluted

377.41 ml Eluted,

No Flow

782.4 ml Clear

Soln. Eluted

22

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

23

One of the more interesting results of the individual scans was the evolution of fractal

dimension with time. For all samples, fractal dimension would decrease as deposition flow

commenced, then increase as clear flow was eluted.

Figure 4.5 Fractal dimension during deposition and clear flow

After performing analysis on all of the samples, the data could be compiled. 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.

24

Figure 4.6 Fractal dimension versus normalized hydraulic conductivity

Figure 4.7 Fractal dimension versus pore flow velocity

y = 1.4832x + 0.4316

R² = 0.2268

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

0 0.2 0.4 0.6 0.8 1 1.2

Fra

cta

l D

imen

sio

n

K/Ko

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

0 500 1000 1500 2000 2500 3000 3500

Fra

cta

l D

imen

sio

n

Pore Flow Velocity (m/day)

25

Figure 4.8 Fractal dimension versus ionic strength

Figure 4.9 Fractal dimension versus pore volumes eluted

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

0 0.01 0.02 0.03 0.04 0.05 0.06

Fra

cta

l D

imen

sio

n

Ionic Strength (M)

y = -0.0067x + 1.9077

R² = 0.083

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

0 20 40 60 80 100 120

Fra

cta

l D

imen

sio

n

Pore Volumes Eluted

26

Figure 4.10 Fractal dimension versus specific deposit

Figure 4.11 Reynolds number versus fractal dimension

y = -0.004x + 2.1147

R² = 0.6035

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

0 50 100 150 200 250 300 350 400 450 500

Fra

cta

l D

imen

sio

n

Specific Deposit (ppm)

0.01

0.1

1

10

0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5

Rey

no

ld's

Nu

mb

er

Fractal Dimension

27

Figure 4.12 Normalized hydraulic conductivity versus specific deposit

The preceding shotgun plots of data show some overall trends, but many correlations were

weak since 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.

y = -0.001x + 0.9219

R² = 0.4052

0

0.2

0.4

0.6

0.8

1

1.2

0 50 100 150 200 250 300 350 400 450 500

K/K

o


28

Figure 4.13 Fractal dimension versus flow rate, Rifle samples

Figure 4.14 Fractal dimension versus ionic strength, Rifle samples

Figure 4.15 Fractal dimension versus pore fluid colloid concentration

1.4

1.6

1.8

2

2.2

2.4

2.6

0 200 400 600 800 1000

Fra

cta

l D

imen

sio

n

Flowrate (ml/min)

Injection Well CD03

Injection Well G51

Monitor Well LR01

Monitor Well FP101

1.4

1.6

1.8

2

2.2

2.4

2.6

0.02 0.03 0.04 0.05 0.06

Fra

cta

l D

imen

sio

n

Ionic Strength (M)

Injection Well CD03

Injection Well G51

Monitor Well LR01

Monitor Well FP101

1.4

1.6

1.8

2

2.2

2.4

2.6

0 5 10 15 20

Fra

cta

l D

imen

sio

n

Concentration (ppm)

Injection Well CD03

Injection Well G51

Monitor Well LR01

Monitor Well FP101

29

4.3 Sample Sets

Sample sets consist of data that have been grouped or removed in order to eliminate ancillary

variables. First, for quality assurance, individual scans in which the straight transmission factor was

less than or equal to 0.1% were removed since this was the maximum colloid deposition for which the

SLS apparatus could take dependable readings. Next, sample runs in which the Nafion did not hit

equilibrium were removed since this would produce inaccurate head data, probably due to changing

porosity. The remaining data was grouped by flow cell position, pore flow velocity, and flow type

(colloid deposition, no flow, or clear flow). The clear flow groups seemed to exhibit different

characteristics which made sense due to the different flow regime. However, deposit flow and no

flow data were in agreement and thus were combined. The plots were usually left with three or fewer

points. However the data appear very linear, with trend line R2 values around 0.9 and significant

correlation with consideration of the 95% confidence interval. Importantly, all the data groups show

the same trends with similar accuracy. The plots shown in figures 16 through 21 are for the outlet

region, pore velocity of 1197 m/day, ionic strength of 0.006 M, and exclude the clear flow regime.

Figure 4.16 Fractal dimension versus specific deposit

y = -0.0099x + 2.3187

R² = 0.9931

1.0

1.2

1.4

1.6

1.8

2.0

2.2

2.4

0 10 20 30 40 50 60 70

Fra

cta

l D

imen

sio

n

Concentration (ppm)

30

Figure 4.17 Fractal dimension versus normalized hydraulic conductivity

Figure 4.18 Normalized hydraulic conductivity versus specific deposit

Figure 4.19 Normalized hydraulic conductivity versus pore volumes eluted

y = 4.0061x - 1.7471

R² = 0.9909

1.0

1.2

1.4

1.6

1.8

2.0

2.2

2.4

0.86 0.88 0.9 0.92 0.94 0.96 0.98 1 1.02

Fra

cta

l D

imen

sio

n

K/Ko

y = -0.0025x + 1.0148

R² = 0.9998

0.86

0.88

0.9

0.92

0.94

0.96

0.98

1

1.02

0 10 20 30 40 50 60 70

K/K

o

Concentration (ppm)

y = -0.001x + 1.066

R² = 0.982

0.85

0.9

0.95

1

1.05

0 50 100 150 200 250 300

K/K

o

Pore Volumes Eluted

31

Figure 4.20 Fractal dimension versus pore volumes eluted

Figure 4.21 Specific deposit versus pore volumes eluted

The preceding data is representative of most pore velocity/cell position combinations. The

plots clearly indicate a dependence on specific deposit and fractal dimension for hydraulic

conductivity. Importantly, there is also a clear connection between fractal dimension and specific

deposit.

A summary for all the groups was necessary in order to see reoccurring trends. Plots grouped

by the previous criteria were then combined by pore flow velocity. Only data sets with at least three

points were considered. Note that the 3000 m/day pore flow velocity data included in the following

plots is for a salt concentration below the critical coagulation concentration, so the colloids did not

aggregate.

y = -0.0027x + 2.5151

R² = 0.9486

1.0

1.2

1.4

1.6

1.8

2.0

2.2

2.4

0 50 100 150 200 250 300

Fra

cta

l D

imen

sio

n

Pore Volumes Eluted

y = 0.2741x - 20.44

R² = 0.979

0

20

40

60

80

0 50 100 150 200 250 300 Sp

ecif

ic D

epo

sit

(pp

m)

Pore Volumes Eluted

32

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.

0.5

1

1.5

2

2.5

0 200 400 600 800

Fra

cta

l D

imen

sio

n

Pore Volumes Eluted

74 m/day

569 m/day

588 m/day

1439 m/day

3000 m/day

0.5

1

1.5

2

2.5

0 200 400 600 800

Fra

cta

l D

imen

sio

n

Pore Volumes Eluted

74 m/day

569 m/day

1197 m/day

1439 m/day

3000 m/day

0.5

1

1.5

2

2.5

0 200 400 600 800

Fra

cta

l D

imen

sio

n

Pore Volumes Eluted

74 m/day

138 m/day

569 m/day

1197 m/day

1439 m/day

(a) Inlet Region

(b) Middle Region

Region

(c) Outlet Region

33

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.

0

50

100

150

200

250

300

0 200 400 600 800

Spe

cifi

c D

ep

osi

t (p

pm

)

Pore Volumes Eluted

74 m/day

569 m/day

588 m/day

1439 m/day

3000 m/day

0

50

100

150

200

250

300

0 200 400 600 800

Sp

ecif

ic D

epo

sit

(pp

m)

Pore Volumes Eluted

74 m/day

569 m/day

1197 m/day

1439 m/day

3000 m/day

0

50

100

150

200

250

300

0 200 400 600 800

Sp

ecif

ic D

epo

sit

(pp

m)

Pore Volumes Eluted

74 m/day

138 m/day

569 m/day

1197 m/day

1439 m/day

(a) Inlet Region

(b) Middle Region

Region

(c) Outlet Region

34

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.

0.5

1

1.5

2

2.5

0 50 100 150 200 250 300

Fra

cta

l D

imen

sio

n


74 m/day

569 m/day

588 m/day

1439 m/day

3000 m/day

0.5

1

1.5

2

2.5

0 50 100 150 200 250 300

Fra

cta

l D

imen

sio

n


74 m/day

569 m/day

1197 m/day

1439 m/day

3000 m/day

0.5

1

1.5

2

2.5

0 50 100 150 200 250 300

Fra

cta

l D

imen

sio

n


74 m/day

138 m/day

569 m/day

1197 m/day

1439 m/day

(a) Inlet Region

(b) Middle Region

Region

(c) Outlet Region

35

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.

0.4

0.5

0.6

0.7

0.8

0.9

1

1.1

0.5 1 1.5 2 2.5

K/K

o

Fractal Dimension

74 m/day

569 m/day

588 m/day

1439 m/day

3000 m/day

0.4

0.5

0.6

0.7

0.8

0.9

1

1.1

0.5 1 1.5 2 2.5

K/K

o

Fractal Dimension

74 m/day

569 m/day

1197 m/day

1439 m/day

3000 m/day

0.4

0.5

0.6

0.7

0.8

0.9

1

1.1

0.5 1 1.5 2 2.5

K/K

o

Fractal Dimension

74 m/day

138 m/day

569 m/day

1197 m/day

1439 m/day

(a) Inlet Region

(b) Middle Region

Region

(c) Outlet Region

36

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.

0.4

0.5

0.6

0.7

0.8

0.9

1

1.1

0 50 100 150 200 250 300

K/K

o


74 m/day

569 m/day

588 m/day

1439 m/day

3000 m/day

0.4

0.5

0.6

0.7

0.8

0.9

1

1.1

0 50 100 150 200 250 300

K/K

o


74 m/day

569 m/day

1197 m/day

1439 m/day

3000 m/day

0.4

0.5

0.6

0.7

0.8

0.9

1

1.1

0 50 100 150 200 250 300

K/K

o


74 m/day

138 m/day

569 m/day

1197 m/day

1439 m/day

(a) Inlet Region

(b) Middle Region

Region

(c) Outlet Region

37

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.

0.4

0.5

0.6

0.7

0.8

0.9

1

1.1

1.E-05 1.E-04 1.E-03 1.E-02 1.E-01 1.E+00 1.E+01 1.E+02 1.E+03

K/K

o

Radius of Gyration (m)

74 m/day

569 m/day

588 m/day

1439 m/day

3000 m/day

0.4

0.5

0.6

0.7

0.8

0.9

1

1.1

1.E-05 1.E-04 1.E-03 1.E-02 1.E-01 1.E+00 1.E+01 1.E+02 1.E+03

K/K

o


74 m/day

569 m/day

1197 m/day

1439 m/day

3000 m/day

0.4

0.5

0.6

0.7

0.8

0.9

1

1.1

1.E-05 1.E-04 1.E-03 1.E-02 1.E-01 1.E+00 1.E+01 1.E+02 1.E+03

K/K

o


74 m/day

138 m/day

569 m/day

1197 m/day

1439 m/day

(a) Inlet Region

(b) Middle Region

Region

(c) Outlet Region

38

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.

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.

0

0.5

1

1.5

2

2.5

3

0 50 100 150 200 250 300 350

Fra

cta

l D

imen

sio

n


Fractal Dimension vs Specific Deposit

74 m/day 0.049 M

138 m/day 0.049 M

292 m/day 0.048 M

569 m/day 0.048 M

588 m/day 0.024 M

691 m/day 0.012 M

1197 m/day 0.006 M

1439 m/day 0.006 M

3000 m/day 0.003 M

39

Figure 4.29 Normalized hydraulic conductivity versus radius of gyration, 74 m/day pore flow

velocity, 0.049M ionic strength.



y = -0.046ln(x) + 0.488

R² = 0.845

0.4

0.5

0.6

0.7

0.8

0.9

1

1.1

1.E-05 1.E-04 1.E-03 1.E-02 1.E-01 1.E+00 1.E+01

K/K

o


K/Ko vs Radius of Gyration

74 m/day 0.049 M

y = -0.040ln(x) + 0.574

R² = 0.953

0.4

0.5

0.6

0.7

0.8

0.9

1

1.1

1.E-05 1.E-04 1.E-03 1.E-02 1.E-01 1.E+00 1.E+01

K/K

o



138 m/day 0.049 M

40


velocity, 0.048 M ionic strength.



y = -0.023ln(x) + 0.789

R² = 0.922

0.4

0.5

0.6

0.7

0.8

0.9

1

1.1

1.E-05 1.E-04 1.E-03 1.E-02 1.E-01 1.E+00 1.E+01

K/K

o



292 m/day 0.048 M

0.4

0.5

0.6

0.7

0.8

0.9

1

1.1

1.E-05 1.E-04 1.E-03 1.E-02 1.E-01 1.E+00 1.E+01

K/K

o



569 m/day 0.048 M

41





y = -0.029ln(x) + 0.772

R² = 0.977

0.4

0.5

0.6

0.7

0.8

0.9

1

1.1

1.E-05 1.E-04 1.E-03 1.E-02 1.E-01 1.E+00 1.E+01

K/K

o



588 m/day 0.024 M

0.4

0.5

0.6

0.7

0.8

0.9

1

1.1

1.E-05 1.E-04 1.E-03 1.E-02 1.E-01 1.E+00 1.E+01

K/K

o



691 m/day 0.012 M

42





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.

y = -0.046ln(x) + 0.576

R² = 0.908

0.4

0.5

0.6

0.7

0.8

0.9

1

1.1

1.E-05 1.E-04 1.E-03 1.E-02 1.E-01 1.E+00 1.E+01

K/K

o



1197 m/day 0.006M

0.4

0.5

0.6

0.7

0.8

0.9

1

1.1

1.E-05 1.E-04 1.E-03 1.E-02 1.E-01 1.E+00 1.E+01

K/K

o



1439 m/day 0.006 M

43

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

44

between fractal dimension and specific deposit and the resulting effect on clogging. Specifically by

the use of an SLS setup that can measure radius of gyration.

As seen in figure 4.29, there seems to be a non-linear relationship between fractal dimension

and specific deposit. This finding supplies an interesting insight into the formation of aggregate

deposits. The next step here would be to further calibrate the in-situ concentration measurement

technique developed during this research, specifically at higher concentrations.

5.4 Discussion

This experiment has yielded compelling results. Fractal dimension does seem to have

a significant impact on clogging. When specific deposit is also considered, the effects on

permeability are 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.

45

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.

46

Appendix A

Experimental Data and Results

y = -0.0011x + 0.0013

R² = 0.2134 -0.0002

0

0.0002

0.0004

0.0006

0.0008

0.001

0.0012

0.0014

0.0016

0.0018

0 0.2 0.4 0.6 0.8 1 1.2

Mo

rph

olo

gy

Pa

ram

eter

(p

pm

^-1

)

K/Ko

Morphology Parameter vs K/Ko

y = -1E-06x + 0.0005

R² = 0.0652 -0.0002

0

0.0002

0.0004

0.0006

0.0008

0.001

0.0012

0.0014

0.0016

0.0018

0 50 100 150 200 250 300 350

Mo

rph

olo

gy

Pa

ram

eter

(p

pm

^-1

)


Morphology Parameter vs Specific Deposit

47

-0.0002

0

0.0002

0.0004

0.0006

0.0008

0.001

0.0012

0.0014

0.0016

0.0018

0 0.5 1 1.5 2 2.5 3

Mo

rph

olo

gy

Pa

ram

eter

(p

pm

^-1

)

Fractal Dimension

Morphology Parameter vs Fractal

Dimension

0.4

0.5

0.6

0.7

0.8

0.9

1

1.1

0 0.001 0.002 0.003 0.004 0.005

K/K

o

Morphology Parameter

K/Ko vs Morphology Parameter

74 m/day 0.049 M

138 m/day 0.049 M

292 m/day 0.048 M

569 m/day 0.048 M

588 m/day 0.024 M

691 m/day 0.012 M

1197 m/day 0.006M

1439 m/day 0.006 M

3000 m/day 0.003 M

48

Sample ID Flowrate (ml/min)

Flow Velocity (m/day)

Average Pore

Velocity (m/day)

Ionic Conc (mM)

Ionic Strength

(M) Salt Type

Nafion Size

(mesh)

2012_03_001_A_6 0.71 9.0 0 60-100

2012_03_001_A_7 0.65 8.3 0 60-100

2012_03_001_A_11 0.63 8.0 0 60-100

2012_04_002_A_15 6.9 87.9 100 Ca(NO3)2 16-35

2012_05_001_A_12 7 89.1 100 Ca(NO3)2 16-35

2012_05_001_A_15 7 89.1 100 Ca(NO3)2 16-35

2012_05_001_A_21 7 89.1 100 Ca(NO3)2 16-35

2012_05_001_A_27 7 89.1 100 Ca(NO3)2 16-35

2012_06_001_A_12 3.45 43.9 100 Ca(NO3)2 16-35

2012_06_001_A_18 3.5 44.6 100 Ca(NO3)2 16-35

2012_06_001_A_24 3.5 44.6 100 Ca(NO3)2 16-35

2012_06_001_A_30 3.45 43.9 100 Ca(NO3)2 16-35

2012_06_002_A_24 1.83 23.3 100 Ca(NO3)2 16-35

2012_06_002_A_27 1.84 23.4 100 Ca(NO3)2 16-35

2012_06_002_A_30 1.7 21.6 100 Ca(NO3)2 16-35

2012_06_003_A_15 1.95 24.8 100 Ca(NO3)2 16-35

2012_06_003_A_21 1.95 24.8 100 Ca(NO3)2 16-35

2013_01_002_A_42 10.34 131.7 1197 2 0.006 MgCl2 16-35

2013_01_002_A_48 10.34 131.7 1197 2 0.006 MgCl2 16-35

2013_01_002_A_54 10.34 131.7 1197 2 0.006 MgCl2 16-35

2013_01_002_A_88 10.34 131.7 1197 2 0.006 MgCl2 16-35

2013_01_002_A_41 10.34 131.7 1197 2 0.006 MgCl2 16-35

2013_01_002_A_47 10.34 131.7 1197 2 0.006 MgCl2 16-35

2013_01_002_A_53 10.34 131.7 1197 2 0.006 MgCl2 16-35

2013_01_002_A_82 10.34 131.7 1197 2 0.006 MgCl2 16-35

2013_01_002_A_40 10.34 131.7 1197 2 0.006 MgCl2 16-35

2013_01_002_A_46 10.34 131.7 1197 2 0.006 MgCl2 16-35

2013_01_002_A_52 10.34 131.7 1197 2 0.006 MgCl2 16-35

2013_01_002_A_75 10.34 131.7 1197 2 0.006 MgCl2 16-35

2013_02_001_A_47 5.21 66.3 603 2 0.006 MgCl2 16-35

2013_02_001_A_56 5.21 66.3 603 2 0.006 MgCl2 16-35

2013_02_001_A_62 5.21 66.3 603 2 0.006 MgCl2 16-35

2013_02_002_A_20 5.4 68.8 659 1.81 0.00543 MgCl2 16-35

2013_02_002_A_26 5.4 68.8 659 1.81 0.00543 MgCl2 16-35

2013_02_002_A_47 5.4 68.8 659 1.81 0.00543 MgCl2 16-35

2013_02_002_A_62 5.3 67.5 647 1.81 0.00543 MgCl2 16-35

2013_02_002_A_22 5.4 68.8 659 1.81 0.00543 MgCl2 16-35

2013_02_002_A_28 5.4 68.8 659 1.81 0.00543 MgCl2 16-35

49

2013_02_002_A_50 5.4 68.8 659 1.81 0.00543 MgCl2 16-35



Average Pore

Velocity (m/day)

Ionic Conc (mM)

Ionic Strength

(M) Salt Type

Nafion Size

(mesh)

2013_02_002_A_64 5.3 67.5 647 1.81 0.00543 MgCl2 16-35

2013_02_002_A_24 5.4 68.8 659 1.81 0.00543 MgCl2 16-35

2013_02_002_A_30 5.4 68.8 659 1.81 0.00543 MgCl2 16-35

2013_02_002_A_53 5.4 68.8 659 1.81 0.00543 MgCl2 16-35

2013_02_002_A_66 5.3 67.5 647 1.81 0.00543 MgCl2 16-35

2013_03_001_A_26 5.72 72.8 671 1.95 0.00585 MgCl2 16-35

2013_03_001_A_32 5.72 72.8 671 1.95 0.00585 MgCl2 16-35

2013_03_001_A_47 5.72 72.8 671 1.95 0.00585 MgCl2 16-35

2013_03_001_A_62 5.67 72.2 665 1.95 0.00585 MgCl2 16-35

2013_03_001_A_28 5.72 72.8 671 1.95 0.00585 MgCl2 16-35

2013_03_001_A_34 5.72 72.8 671 1.95 0.00585 MgCl2 16-35

2013_03_001_A_50 5.72 72.8 671 1.95 0.00585 MgCl2 16-35

2013_03_001_A_64 5.67 72.2 665 1.95 0.00585 MgCl2 16-35

2013_03_001_A_36 5.72 72.8 671 1.95 0.00585 MgCl2 16-35

2013_03_001_A_53 5.72 72.8 671 1.95 0.00585 MgCl2 16-35

2013_03_001_A_66 5.67 72.2 665 1.95 0.00585 MgCl2 16-35

2013_03_008_A_20 11.62 148.0 569 16.03 0.04809 MgCl2 16-35

2013_03_008_A_26 11.62 148.0 569 16.03 0.04809 MgCl2 16-35

2013_03_008_A_47 11.62 148.0 569 16.03 0.04809 MgCl2 16-35

2013_03_008_A_62 11.76 149.7 576 16.03 0.04809 MgCl2 16-35

2013_03_008_A_22 11.62 148.0 569 16.03 0.04809 MgCl2 16-35

2013_03_008_A_28 11.62 148.0 569 16.03 0.04809 MgCl2 16-35

2013_03_008_A_50 11.62 148.0 569 16.03 0.04809 MgCl2 16-35

2013_03_008_A_64 11.76 149.7 576 16.03 0.04809 MgCl2 16-35

2013_03_008_A_24 11.62 148.0 569 16.03 0.04809 MgCl2 16-35

2013_03_008_A_30 11.62 148.0 569 16.03 0.04809 MgCl2 16-35

2013_03_008_A_53 11.62 148.0 569 16.03 0.04809 MgCl2 16-35

2013_03_008_A_66 11.76 149.7 576 16.03 0.04809 MgCl2 16-35

2013_04_001_A_20 5.97 76.0 292 16.01 0.04803 MgCl2 16-35

2013_04_001_A_26 5.97 76.0 292 16.01 0.04803 MgCl2 16-35

2013_04_001_A_22 5.97 76.0 292 16.01 0.04803 MgCl2 16-35

2013_04_001_A_24 5.97 76.0 292 16.01 0.04803 MgCl2 16-35

2013_04_001_A_30 5.97 76.0 292 16.01 0.04803 MgCl2 16-35

2013_04_018_A_20 2.82 35.9 138 16.23 0.04869 MgCl2 16-35

2013_04_018_A_26 2.82 35.9 138 16.23 0.04869 MgCl2 16-35

2013_04_018_A_32 2.82 35.9 138 16.23 0.04869 MgCl2 16-35

2013_04_018_A_22 2.82 35.9 138 16.23 0.04869 MgCl2 16-35

50

2013_04_018_A_28 2.82 35.9 138 16.23 0.04869 MgCl2 16-35

2013_04_018_A_50 2.82 35.9 138 16.23 0.04869 MgCl2 16-35

2013_04_018_A_64 2.82 35.9 138 16.23 0.04869 MgCl2 16-35

2013_04_018_A_24 2.82 35.9 138 16.23 0.04869 MgCl2 16-35



Average Pore

Velocity (m/day)

Ionic Conc (mM)

Ionic Strength

(M) Salt Type

Nafion Size

(mesh)

2013_04_018_A_30 2.82 35.9 138 16.23 0.04869 MgCl2 16-35

2013_04_018_A_53 2.82 35.9 138 16.23 0.04869 MgCl2 16-35

2013_04_018_A_66 2.82 35.9 138 16.23 0.04869 MgCl2 16-35

2013_06_002_A_20 12 152.8 588 8.027 0.024081 MgCl2 16-35

2013_06_002_A_26 12 152.8 588 8.027 0.024081 MgCl2 16-35

2013_06_002_A_32 12 152.8 588 8.027 0.024081 MgCl2 16-35

2013_06_002_A_22 12 152.8 588 8.027 0.024081 MgCl2 16-35

2013_06_002_A_28 12 152.8 588 8.027 0.024081 MgCl2 16-35

2013_06_002_A_50 12 152.8 588 8.027 0.024081 MgCl2 16-35

2013_06_002_A_64 12 152.8 588 8.027 0.024081 MgCl2 16-35

2013_06_002_A_24 12 152.8 588 8.027 0.024081 MgCl2 16-35

2013_06_002_A_30 12 152.8 588 8.027 0.024081 MgCl2 16-35

2013_06_002_A_53 12 152.8 588 8.027 0.024081 MgCl2 16-35

2013_06_002_A_66 12 152.8 588 8.027 0.024081 MgCl2 16-35

2013_08_001_A_20 11.86 151.0 690 3.953 0.011859 MgCl2 16-35

2013_08_001_A_26 11.86 151.0 690 3.953 0.011859 MgCl2 16-35

2013_08_001_A_47 11.86 151.0 690 3.953 0.011859 MgCl2 16-35

2013_08_001_A_62 11.86 151.0 690 3.953 0.011859 MgCl2 16-35

2013_08_001_A_22 11.86 151.0 690 3.953 0.011859 MgCl2 16-35

2013_08_001_A_28 11.86 151.0 690 3.953 0.011859 MgCl2 16-35

2013_08_001_A_50 11.86 151.0 690 3.953 0.011859 MgCl2 16-35

2013_08_001_A_64 11.86 151.0 690 3.953 0.011859 MgCl2 16-35

2013_08_001_A_24 11.86 151.0 690 3.953 0.011859 MgCl2 16-35

2013_08_001_A_30 11.86 151.0 690 3.953 0.011859 MgCl2 16-35

2013_08_001_A_53 11.86 151.0 690 3.953 0.011859 MgCl2 16-35

2013_08_001_A_66 11.86 151.0 690 3.953 0.011859 MgCl2 16-35

2013_08_002_A_20 12.53 159.5 1439 2.016 0.006048 MgCl2 16-35

2013_08_002_A_26 12.53 159.5 1439 2.016 0.006048 MgCl2 16-35

2013_08_002_A_47 12.53 159.5 1439 2.016 0.006048 MgCl2 16-35

2013_08_002_A_62 12.53 159.5 1439 2.016 0.006048 MgCl2 16-35

2013_08_002_A_22 12.53 159.5 1439 2.016 0.006048 MgCl2 16-35

2013_08_002_A_28 12.53 159.5 1439 2.016 0.006048 MgCl2 16-35

2013_08_002_A_50 12.53 159.5 1439 2.016 0.006048 MgCl2 16-35

2013_08_002_A_64 12.53 159.5 1439 2.016 0.006048 MgCl2 16-35

51

2013_08_002_A_24 12.53 159.5 1439 2.016 0.006048 MgCl2 16-35

2013_08_002_A_30 12.53 159.5 1439 2.016 0.006048 MgCl2 16-35

2013_08_002_A_53 12.53 159.5 1439 2.016 0.006048 MgCl2 16-35

2013_08_002_A_66 12.53 159.5 1439 2.016 0.006048 MgCl2 16-35

2013_08_003_A_20 11.63 148.1 1.011 0.003033 MgCl2 16-35

2013_08_003_A_26 11.63 148.1 1.011 0.003033 MgCl2 16-35

2013_08_003_A_47 11.63 148.1 1.011 0.003033 MgCl2 16-35



Average Pore

Velocity (m/day)

Ionic Conc (mM)

Ionic Strength

(M) Salt Type

Nafion Size

(mesh)

2013_08_003_A_62 11.63 148.1 1.011 0.003033 MgCl2 16-35

2013_08_003_A_22 11.63 148.1 1.011 0.003033 MgCl2 16-35

2013_08_003_A_28 11.63 148.1 1.011 0.003033 MgCl2 16-35

2013_08_003_A_50 11.63 148.1 1.011 0.003033 MgCl2 16-35

2013_08_003_A_64 11.63 148.1 1.011 0.003033 MgCl2 16-35

2013_08_003_A_24 11.63 148.1 1.011 0.003033 MgCl2 16-35

2013_08_003_A_30 11.63 148.1 1.011 0.003033 MgCl2 16-35

2013_08_003_A_53 11.63 148.1 1.011 0.003033 MgCl2 16-35

2013_08_003_A_66 11.63 148.1 1.011 0.003033 MgCl2 16-35

2013_09_001_A_20 11.78 150.0 3000 0.983 0.002949 MgCl2 16-35

2013_09_001_A_26 11.78 150.0 3000 0.983 0.002949 MgCl2 16-35

2013_09_001_A_47 11.78 150.0 3000 0.983 0.002949 MgCl2 16-35

2013_09_001_A_62 11.78 150.0 3000 0.983 0.002949 MgCl2 16-35

2013_09_001_A_22 11.78 150.0 3000 0.983 0.002949 MgCl2 16-35

2013_09_001_A_28 11.78 150.0 3000 0.983 0.002949 MgCl2 16-35

2013_09_001_A_50 11.78 150.0 3000 0.983 0.002949 MgCl2 16-35

2013_09_001_A_64 11.78 150.0 3000 0.983 0.002949 MgCl2 16-35

2013_09_001_A_24 11.78 150.0 3000 0.983 0.002949 MgCl2 16-35

2013_09_001_A_30 11.78 150.0 3000 0.983 0.002949 MgCl2 16-35

2013_09_001_A_53 11.78 150.0 3000 0.983 0.002949 MgCl2 16-35

2013_09_001_A_66 11.78 150.0 3000 0.983 0.002949 MgCl2 16-35

2013_09_002_A_20 1.512 19.3 74 16.254 0.048762 MgCl2 16-35

2013_09_002_A_26 1.512 19.3 74 16.254 0.048762 MgCl2 16-35

2013_09_002_A_47 1.512 19.3 74 16.254 0.048762 MgCl2 16-35

2013_09_002_A_62 1.528 19.5 75 16.254 0.048762 MgCl2 16-35

2013_09_002_A_22 1.512 19.3 74 16.254 0.048762 MgCl2 16-35

2013_09_002_A_28 1.512 19.3 74 16.254 0.048762 MgCl2 16-35

2013_09_002_A_50 1.512 19.3 74 16.254 0.048762 MgCl2 16-35

2013_09_002_A_64 1.528 19.5 75 16.254 0.048762 MgCl2 16-35

2013_09_002_A_24 1.512 19.3 74 16.254 0.048762 MgCl2 16-35

2013_09_002_A_30 1.512 19.3 74 16.254 0.048762 MgCl2 16-35

2013_09_002_A_53 1.512 19.3 74 16.254 0.048762 MgCl2 16-35

52

2013_09_002_A_66 1.528 19.5 75 16.254 0.048762 MgCl2 16-35

Sample ID Nafion

Amount (g)

Porosity

Inlet Colloid Conc

(ppm)

Colloid Size (nm)

Pore Fluid Colloid

Conc. (ppm)


Flow Cell

Position

2012_03_001_A_6 5.5 125 99 255

2012_03_001_A_7 5.5 125 99 255

2012_03_001_A_11 5.5 125 99 255

2012_04_002_A_15 7 12 99 255

2012_05_001_A_12 7 125 99 255

2012_05_001_A_15 7 125 99 255

2012_05_001_A_21 7 125 99 255

2012_05_001_A_27 7 125 99 255

2012_06_001_A_12 7 125 99 255

2012_06_001_A_18 7 125 99 255

2012_06_001_A_24 7 125 99 255

2012_06_001_A_30 7 125 99 255

2012_06_002_A_24 7 125 99 255

2012_06_002_A_27 7 125 99 255

2012_06_002_A_30 7 125 99 255

2012_06_003_A_15 7 125 99 255

2012_06_003_A_21 7 125 99 255

2013_01_002_A_42 6.5 0.11 125 106 451 50 790

2013_01_002_A_48 6.5 0.11 125 106 1629 179 790

2013_01_002_A_54 6.5 0.11 125 106 1649 181 790

2013_01_002_A_88 6.5 0.11 125 106 1010 111 790

2013_01_002_A_41 6.5 0.11 125 106 117 13 580

2013_01_002_A_47 6.5 0.11 125 106 611 67 580

2013_01_002_A_53 6.5 0.11 125 106 1035 114 580

2013_01_002_A_82 6.5 0.11 125 106 543 60 580

2013_01_002_A_40 6.5 0.11 125 106 52 6 255

2013_01_002_A_46 6.5 0.11 125 106 301 33 255

2013_01_002_A_52 6.5 0.11 125 106 523 58 255

2013_01_002_A_75 6.5 0.11 125 106 403 44 255

2013_02_001_A_47 6.5 0.11 125 106 95 11 790

2013_02_001_A_56 6.5 0.11 125 106 108 12 790

2013_02_001_A_62 6.5 0.11 125 106 181 20 790

2013_02_002_A_20 6.5 0.10 136 106 60 6 790

2013_02_002_A_26 6.5 0.10 136 106 403 42 790

2013_02_002_A_47 6.5 0.10 136 106 1447 151 790

53

2013_02_002_A_62 6.5 0.10 136 106 1438 150 790

2013_02_002_A_22 6.5 0.10 136 106 152 16 580

2013_02_002_A_28 6.5 0.10 136 106 630 66 580

2013_02_002_A_50 6.5 0.10 136 106 1629 170 580

Sample ID Nafion

Amount (g)

Porosity

Inlet Colloid Conc

(ppm)

Colloid Size (nm)

Pore Fluid Colloid

Conc. (ppm)


Flow Cell

Position

2013_02_002_A_64 6.5 0.1043 136.4 106.0 1669.4 174.1 580

2013_02_002_A_24 6.5 0.1043 136.4 106.0 130.2 13.6 255

2013_02_002_A_30 6.5 0.1 136.4 106.0 445.022706 46.415868 255

2013_02_002_A_53 6.5 0.1 136.4 106.0 1157.50777 120.72806 255

2013_02_002_A_66 6.5 0.1 136.4 106.0 1193.99509 124.53369 255

2013_03_001_A_26 6.5 0.1 127.9 106.0 117.895408 12.791652 790

2013_03_001_A_32 6.5 0.1 127.9 106.0 340.773621 36.973938 790

2013_03_001_A_47 6.5 0.1 127.9 106.0 817.642166 88.714175 790

2013_03_001_A_62 6.5 0.1 127.9 106.0 843.416141 91.510651 790

2013_03_001_A_28 6.5 0.1 127.9 106.0 107.414029 11.654422 580

2013_03_001_A_34 6.5 0.1 127.9 106.0 320.264434 34.748691 580

2013_03_001_A_50 6.5 0.1 127.9 106.0 618.380274 67.09426 580

2013_03_001_A_64 6.5 0.1 127.9 106.0 614.553791 66.679086 580

2013_03_001_A_36 6.5 0.1 127.9 106.0 130.205251 14.12727 255

2013_03_001_A_53 6.5 0.1 127.9 106.0 224.829012 24.393948 255

2013_03_001_A_66 6.5 0.1085 127.9 106 227.637498 24.698669 255

2013_03_008_A_20 6.5 0.26 124.3 106 115.421252 30.009525 790

2013_03_008_A_26 6.5 0.26 124.3 106 493.106914 128.2078 790

2013_03_008_A_47 6.5 0.26 124.3 106 1104.15305 287.07979 790

2013_03_008_A_62 6.5 0.26 124.3 106 863.504878 224.51127 790

2013_03_008_A_22 6.5 0.26 124.3 106 99.478794 25.864486 580

2013_03_008_A_28 6.5 0.26 124.3 106 360.065798 93.617108 580

2013_03_008_A_50 6.5 0.26 124.3 106 748.501064 194.61028 580

2013_03_008_A_64 6.5 0.26 124.3 106 616.274211 160.23129 580

2013_03_008_A_24 6.5 0.26 124.3 106 159.88613 41.570394 255

2013_03_008_A_30 6.5 0.26 124.3 106 455.177266 118.34609 255

2013_03_008_A_53 6.5 0.26 124.3 106 706.908938 183.79632 255

2013_03_008_A_66 6.5 0.26 124.3 106 516.183659 134.20775 255

2013_04_001_A_20 6.5 0.26 124.5 106 91.3034289 23.738892 790

2013_04_001_A_26 6.5 0.26 124.5 106 834.386801 216.94057 790

2013_04_001_A_22 6.5 0.26 124.5 106 233.174931 60.625482 580

2013_04_001_A_24 6.5 0.26 124.5 106 246.894153 64.19248 255

2013_04_001_A_30 6.5 0.26 124.5 106 1110.48366 288.72575 255

2013_04_018_A_20 6.5 0.26 61.4 106 56.1618 14.602068 790

54

2013_04_018_A_26 6.5 0.26 61.4 106 605.794477 157.50656 790

2013_04_018_A_32 6.5 0.26 61.4 106 1142.68532 297.09818 790

2013_04_018_A_22 6.5 0.26 61.4 106 130.144726 33.837629 580

2013_04_018_A_28 6.5 0.26 61.4 106 609.26777 158.40962 580

2013_04_018_A_50 6.5 0.26 61.4 106 1245.00206 323.70054 580

2013_04_018_A_64 6.5 0.26 61.4 106 1129.69409 293.72046 580

2013_04_018_A_24 6.5 0.26 61.4 106 72.2251405 18.778537 255

Sample ID Nafion

Amount (g)

Porosity

Inlet Colloid Conc

(ppm)

Colloid Size (nm)

Pore Fluid Colloid

Conc. (ppm)


Flow Cell

Position

2013_04_018_A_30 6.5 0.26 61.4 106 291.416916 75.768398 255

2013_04_018_A_53 6.5 0.26 61.4 106 671.455783 174.5785 255

2013_04_018_A_66 6.5 0.26 61.4 106 447.436983 116.33362 255

2013_06_002_A_20 6.5 0.26 124.19 106 77.3540639 20.112057 790

2013_06_002_A_26 6.5 0.26 124.19 106 432.34905 112.41075 790

2013_06_002_A_32 6.5 0.26 124.19 106 919.552733 239.08371 790

2013_06_002_A_22 6.5 0.26 124.19 106 126.477158 32.884061 580

2013_06_002_A_28 6.5 0.26 124.19 106 424.99696 110.49921 580

2013_06_002_A_50 6.5 0.26 124.19 106 1196.16146 311.00198 580

2013_06_002_A_64 6.5 0.26 124.19 106 914.310578 237.72075 580

2013_06_002_A_24 6.5 0.26 124.19 106 198.683041 51.657591 255

2013_06_002_A_30 6.5 0.26 124.19 106 493.106914 128.2078 255

2013_06_002_A_53 6.5 0.26 124.19 106 863.504878 224.51127 255

2013_06_002_A_66 6.5 0.26 124.19 106 723.261008 188.04786 255

2013_08_001_A_20 6.5 0.2187075 126.07 106 124.326416 27.19112 790

2013_08_001_A_26 6.5 0.2187075 126.07 106 1073.03726 234.6813 790

2013_08_001_A_47 6.5 0.2187075 126.07 106 2059.04019 450.32753 790

2013_08_001_A_62 6.5 0.2187075 126.07 106 1889.82418 413.31872 790

2013_08_001_A_22 6.5 0.2187075 126.07 106 214.012151 46.806063 580

2013_08_001_A_28 6.5 0.2187075 126.07 106 853.687663 186.70789 580

2013_08_001_A_50 6.5 0.2187075 126.07 106 1573.86966 344.2171 580

2013_08_001_A_64 6.5 0.2187075 126.07 106 1162.45281 254.23715 580

2013_08_001_A_24 6.5 0.2187075 126.07 106 251.165214 54.931716 255

2013_08_001_A_30 6.5 0.2187075 126.07 106 616.274211 134.78379 255

2013_08_001_A_53 6.5 0.2187075 126.07 106 1110.48366 242.8711 255

2013_08_001_A_66 6.5 0.2187075 126.07 106 546.554156 119.53549 255

2013_08_002_A_20 6.5 0.11088 61.821 106 29.8 3.304224 790

2013_08_002_A_26 6.5 0.11088 61.821 106 105 11.6424 790

2013_08_002_A_47 6.5 0.11088 61.821 106 570 63.2016 790

2013_08_002_A_62 6.5 0.11088 61.821 106 455 50.4504 790

2013_08_002_A_22 6.5 0.11088 61.821 106 28.7 3.182256 580

55

2013_08_002_A_28 6.5 0.11088 61.821 106 111 12.30768 580

2013_08_002_A_50 6.5 0.11088 61.821 106 498 55.21824 580

2013_08_002_A_64 6.5 0.11088 61.821 106 337 37.36656 580

2013_08_002_A_24 6.5 0.11088 61.821 106 30.4 3.370752 255

2013_08_002_A_30 6.5 0.11088 61.821 106 97.8 10.844064 255

2013_08_002_A_53 6.5 0.11088 61.821 106 318 35.25984 255

2013_08_002_A_66 6.5 0.11088 61.821 106 130 14.4144 255

2013_08_003_A_20 6 61.604 106 8.3 790

2013_08_003_A_26 6 61.604 106 12.5 790

2013_08_003_A_47 6 61.604 106 30.5 790

Sample ID Nafion

Amount (g)

Porosity

Inlet Colloid Conc

(ppm)

Colloid Size (nm)

Pore Fluid Colloid

Conc. (ppm)


Flow Cell

Position

2013_08_003_A_62 6 61.604 106 42.4 790

2013_08_003_A_22 6 61.604 106 10.8 580

2013_08_003_A_28 6 61.604 106 11.2 580

2013_08_003_A_50 6 61.604 106 18.5 580

2013_08_003_A_64 6 61.604 106 6.1 580

2013_08_003_A_24 6 61.604 106 14.7 255

2013_08_003_A_30 6 61.604 106 11.7 255

2013_08_003_A_53 6 61.604 106 0 255

2013_08_003_A_66 6 61.604 106 0 255

2013_09_001_A_20 6.5 0.05 126.715 106 26.3 1.315 790

2013_09_001_A_26 6.5 0.05 126.715 106 28.5 1.425 790

2013_09_001_A_47 6.5 0.05 126.715 106 13.2 0.66 790

2013_09_001_A_62 6.5 0.05 126.715 106 21.9 1.095 790

2013_09_001_A_22 6.5 0.05 126.715 106 16.6 0.83 580

2013_09_001_A_28 6.5 0.05 126.715 106 15.1 0.755 580

2013_09_001_A_50 6.5 0.05 126.715 106 19.7 0.985 580

2013_09_001_A_64 6.5 0.05 126.715 106 2.7 0.135 580

2013_09_001_A_24 6.5 0.05 126.715 106 0 0 255

2013_09_001_A_30 6.5 0.05 126.715 106 5.2 0.26 255

2013_09_001_A_53 6.5 0.05 126.715 106 11.7 0.585 255

2013_09_001_A_66 6.5 0.05 126.715 106 0 0 255

2013_09_002_A_20 6.5 0.26 30.66 106 62 16.12 790

2013_09_002_A_26 6.5 0.26 30.66 106 324 84.24 790

2013_09_002_A_47 6.5 0.26 30.66 106 858 223.08 790

2013_09_002_A_62 6.5 0.26 30.66 106 680 176.8 790

2013_09_002_A_22 6.5 0.26 30.66 106 60 15.6 580

2013_09_002_A_28 6.5 0.26 30.66 106 196 50.96 580

2013_09_002_A_50 6.5 0.26 30.66 106 446 115.96 580

56

2013_09_002_A_64 6.5 0.26 30.66 106 387 100.62 580

2013_09_002_A_24 6.5 0.26 30.66 106 46.3 12.038 255

2013_09_002_A_30 6.5 0.26 30.66 106 122 31.72 255

2013_09_002_A_53 6.5 0.26 30.66 106 278 72.28 255

2013_09_002_A_66 6.5 0.26 30.66 106 244 63.44 255

Sample ID Volume

Eluted (ml)

Pore Volumes

Eluted

Clean Bed

Head Loss (cm

H2O)

Clean Bed K (cm/min)

dH/dHo Hyd Cond (cm/min)

2012_03_001_A_6 33.166667

2012_03_001_A_7 59.7

2012_03_001_A_11 159.2

2012_04_002_A_15 193.2 1.02

2012_05_001_A_12 35

2012_05_001_A_15 87.5

2012_05_001_A_21 196

2012_05_001_A_27 297.5

2012_06_001_A_12 25.875

2012_06_001_A_18 94.5

2012_06_001_A_24 182

2012_06_001_A_30 268.25 1.73

2012_06_002_A_24 111.63

2012_06_002_A_27 186.76

2012_06_002_A_30 272.15

2012_06_003_A_15 23.4

2012_06_003_A_21 86.775

2013_01_002_A_42 181 131.636364 6.5 1.75970048 1.07 1.649

2013_01_002_A_48 341 248 6.5 1.75970048 1.46 1.21

2013_01_002_A_54 377 274.181818 6.5 1.75970048 1.61 1.09

2013_01_002_A_88 1320 960 6.5 1.75970048 0.908 1.94

2013_01_002_A_41 155 112.727273 10 2.28761062 1.027 2.227

2013_01_002_A_47 315 229.090909 10 2.28761062 1.359 1.683

2013_01_002_A_53 377 274.181818 10 2.28761062 1.53 1.5

2013_01_002_A_82 1160 843.636364 10 2.28761062 1.16 1.967

2013_01_002_A_40 124 90.1818182 45.4 0.75581849 0.999 0.757

2013_01_002_A_46 290 210.909091 45.4 0.75581849 1.072 0.7049

2013_01_002_A_52 377 274.181818 45.4 0.75581849 1.15 0.66

2013_01_002_A_75 984 715.636364 45.4 0.75581849 1.054 0.717

2013_02_001_A_47 356 258.909091

2013_02_001_A_56 437 317.818182

57

2013_02_001_A_62 617 448.727273

2013_02_002_A_20 22 16.8744008 3.8 1.57196088 1.04 1.516

2013_02_002_A_26 113 86.6730585 3.8 1.57196088 1.28 1.22

2013_02_002_A_47 332 254.650048 3.8 1.57196088 1.88 0.835

2013_02_002_A_62 578 443.336529 3.8 1.54285049 1.99 0.775

2013_02_002_A_22 49 37.5838926 11 1.08608206 1.101 0.98

2013_02_002_A_28 138 105.848514 11 1.08608206 1.32 0.825

2013_02_002_A_50 332 254.650048 11 1.08608206 1.95 0.557

Sample ID Volume

Eluted (ml)

Pore Volumes

Eluted

Clean Bed

Head Loss (cm

H2O)



2013_02_002_A_64 605 464.046021 11 1.06596943 1.964 0.543

2013_02_002_A_24 73 55.9923298 15 1.19469027 1.13 1.055

2013_02_002_A_30 165 126.558006 15 1.19469027 1.245 0.959

2013_02_002_A_53 332 254.650048 15 1.19469027 1.52 0.787

2013_02_002_A_66 629 482.454458 15 1.17256637 1.5 0.782

2013_03_001_A_26 129 95.1152074

2013_03_001_A_32 235 173.271889

2013_03_001_A_47 343 252.903226

2013_03_001_A_62 593 437.235023

2013_03_001_A_28 157 115.760369

2013_03_001_A_34 260 191.705069

2013_03_001_A_50 343 252.903226

2013_03_001_A_64 621 457.880184

2013_03_001_A_36 292 215.299539

2013_03_001_A_53 343 252.903226

2013_03_001_A_66 649 478.525346

2013_03_008_A_20 58 17.8461538 1.1 11.6854385 1.015 11.515

2013_03_008_A_26 267 82.1538462 1.1 11.6854385 1.105 10.57

2013_03_008_A_47 485 149.230769 1.1 11.6854385 1.17 9.99

2013_03_008_A_62 809 248.923077 1.1 11.8262269 1.22 9.7

2013_03_008_A_22 110 33.8461538 7.4 3.47404927 1.03 2.6

2013_03_008_A_28 320 98.4615385 7.4 3.47404927 1.11 2.4

2013_03_008_A_50 485 149.230769 7.4 3.47404927 1.18 2.27

2013_03_008_A_64 861 264.923077 7.4 3.51590529 1.248 2.189

2013_03_008_A_24 163 50.1538462 9.6 4.01686947 1.05 3.81

2013_03_008_A_30 372 114.461538 9.6 4.01686947 1.135 3.54

2013_03_008_A_53 485 149.230769 9.6 4.01686947 1.26 3.42

2013_03_008_A_66 914 281.230769 9.6 4.06526549 1.21 3.35

2013_04_001_A_20 24 7.38461538 1.99 3.31858407 0.996 3.32

2013_04_001_A_26 194 59.6923077 1.99 3.31858407 1.22 2.71

58

2013_04_001_A_22 54 16.6153846 5.16 2.55968306 1.06 2.42

2013_04_001_A_24 81 24.9230769 6.45 3.07161967 1.1 2.79

2013_04_001_A_30 254 78.1538462 6.45 3.07161967 1.36 2.26

2013_04_018_A_20 17 5.23076923 1.14 2.73637634 1.1 2.5

2013_04_018_A_26 148 45.5384615 1.14 2.73637634 1.418 1.93

2013_04_018_A_32 250 76.9230769 1.14 2.73637634 1.77 1.54

2013_04_018_A_22 30 9.23076923 2.56 2.43708518 1.14 2.12

2013_04_018_A_28 161 49.5384615 2.56 2.43708518 1.5 1.62

2013_04_018_A_50 307 94.4615385 2.56 2.43708518 2.02 1.21

2013_04_018_A_64 512 157.538462 2.56 2.43708518 1.83 1.33

2013_04_018_A_24 42 12.9230769 3.3 2.83588093 1.144 2.48

Sample ID Volume

Eluted (ml)

Pore Volumes

Eluted

Clean Bed

Head Loss (cm

H2O)



2013_04_018_A_30 175 53.8461538 3.3 2.83588093 1.367 2.07

2013_04_018_A_53 307 94.4615385 3.3 2.83588093 1.71 1.66

2013_04_018_A_66 527 162.153846 3.3 2.83588093 1.517 1.87

2013_06_002_A_20 54 16.6153846 2.8 4.74083439 1 4.73

2013_06_002_A_26 216 66.4615385 2.8 4.74083439 1.068 4.437

2013_06_002_A_32 372 114.461538 2.8 4.74083439 1.27 3.733

2013_06_002_A_22 114 35.0769231 14.1 1.88288458 1.002 1.88

2013_06_002_A_28 264 81.2307692 14.1 1.88288458 1.095 1.719

2013_06_002_A_50 492 151.384615 14.1 1.88288458 1.245 1.514

2013_06_002_A_64 780 240 14.1 1.88288458 1.233 1.527

2013_06_002_A_24 162 49.8461538

2013_06_002_A_30 318 97.8461538

2013_06_002_A_53 492 151.384615

2013_06_002_A_66 834 256.615385

2013_08_001_A_20 47.4 17.3382257 6.4 2.04991704 1.2 1.7

2013_08_001_A_26 214 78.2780655 6.4 2.04991704 1.12 1.83

2013_08_001_A_47 513 187.647886 6.4 2.04991704 1.49 1.38

2013_08_001_A_62 810 296.286136 6.4 2.04991704 1.54 1.34

2013_08_001_A_22 113 41.3337448 18.9 1.3883036 1.03 1.34

2013_08_001_A_28 267 97.6646891 18.9 1.3883036 1.19 1.16

2013_08_001_A_50 513 187.647886 18.9 1.3883036 1.43 0.97

2013_08_001_A_64 863 315.672759 18.9 1.3883036 1.3 1.07

2013_08_001_A_24 160 58.5256564 28.6 1.37616808 1.07 1.28

2013_08_001_A_30 320 117.051313 28.6 1.37616808 1.21 1.14

2013_08_001_A_53 513 187.647886 28.6 1.37616808 1.33 1.04

2013_08_001_A_66 916 335.059383 28.6 1.37616808 1.202 1.145

2013_08_002_A_20 43.9 31.6738817 5.5 2.52011263 1.012 2.49

59

2013_08_002_A_26 213 153.679654 5.5 2.52011263 1.086 2.321

2013_08_002_A_47 520 375.180375 5.5 2.52011263 1.21 2.08

2013_08_002_A_62 807 582.251082 5.5 2.52011263 0.97 2.7

2013_08_002_A_22 119 85.8585859 26.2 1.05806255 1.04 1.015

2013_08_002_A_28 269 194.083694 26.2 1.05806255 1.135 0.932

2013_08_002_A_50 520 375.180375 26.2 1.05806255 1.276 0.829

2013_08_002_A_64 859 619.76912 26.2 1.05806255 1.09 1.008

2013_08_002_A_24 157 113.275613 43.2 0.96254302 1.03 0.932

2013_08_002_A_30 326 235.209235 43.2 0.96254302 1.093 0.881

2013_08_002_A_53 520 375.180375 43.2 0.96254302 1.168 0.824

2013_08_002_A_66 918 662.337662 43.2 0.96254302 1.1 0.913

2013_08_003_A_20 46.5

2013_08_003_A_26 209

2013_08_003_A_47 521

Sample ID Volume

Eluted (ml)

Pore Volumes

Eluted

Clean Bed

Head Loss (cm

H2O)



2013_08_003_A_62 825

2013_08_003_A_22 98.9

2013_08_003_A_28 273

2013_08_003_A_50 521

2013_08_003_A_64 877

2013_08_003_A_24 157

2013_08_003_A_30 331

2013_08_003_A_53 521

2013_08_003_A_66 930

2013_09_001_A_20 47.1 75.36 7 1.86156764 1.01 1.844

2013_09_001_A_26 212 339.2 7 1.86156764 0.99 1.88

2013_09_001_A_47 527 843.2 7 1.86156764 0.986 1.889

2013_09_001_A_62 786 1257.6 7 1.86156764 0.929 2.007

2013_09_001_A_22 100 160 30.5 0.85449006 0.998 0.856

2013_09_001_A_28 265 424 30.5 0.85449006 0.991 0.863

2013_09_001_A_50 527 843.2 30.5 0.85449006 0.985 0.868

2013_09_001_A_64 834 1334.4 30.5 0.85449006 0.955 0.896

2013_09_001_A_24 153 244.8 44.5 0.87849259 1 0.878

2013_09_001_A_30 324 518.4 44.5 0.87849259 0.998 0.88

2013_09_001_A_53 527 843.2 44.5 0.87849259 0.988 0.889

2013_09_001_A_66 940 1504 44.5 0.87849259 0.97 0.906

2013_09_002_A_20 28 8.61538462 0.9 1.85840708 1.13 1.645

2013_09_002_A_26 116 35.6923077 0.9 1.85840708 1.38 1.34

2013_09_002_A_47 248 76.3076923 0.9 1.85840708 2.13 0.873

60

2013_09_002_A_62 389 119.692308 0.9 1.87807276 1.85 1.01

2013_09_002_A_22 36.3 11.1692308 1.7 1.96772514 1.12 1.75

2013_09_002_A_28 124 38.1538462 1.7 1.96772514 1.44 1.35

2013_09_002_A_50 248 76.3076923 1.7 1.96772514 1.96 1.01

2013_09_002_A_64 395 121.538462 1.7 1.98854763 1.82 1.09

2013_09_002_A_24 43.1 13.2615385 1.8 2.78761062 1.03 2.7

2013_09_002_A_30 131 40.3076923 1.8 2.78761062 1.25 2.23

2013_09_002_A_53 248 76.3076923 1.8 2.78761062 1.43 1.96

2013_09_002_A_66 402 123.692308 1.8 2.81710914 1.39 2.02

Sample ID K/Ko Morph.

Parameter (1/ppm)

Fractal Dimension

95% Confidence

Interval (+/-)

Df - CI

Df + CI

Fractal Fit Range (Q^-1)

2012_03_001_A_6 2.957 0.086 2.87 3.04 0.002-0.01

2012_03_001_A_7 3.01 0.076 2.93 3.09 0.002-0.01

2012_03_001_A_11 3.076 0.061 3.02 3.14 0.002-0.01

2012_04_002_A_15 2.906 0.159 2.75 3.07 0.002-0.006

2012_05_001_A_12 2.466 0.065 2.4 2.53 0.005-0.02

2012_05_001_A_15 2.187 0.053 2.13 2.24 0.005-0.02

2012_05_001_A_21 1.815 0.041 1.77 1.86 0.005-0.02

2012_05_001_A_27 1.984 0.057 1.93 2.04 0.005-0.02

2012_06_001_A_12 2.96 0.131 2.83 3.09 0.005-0.02

2012_06_001_A_18 2.297 0.051 2.25 2.35 0.005-0.02

2012_06_001_A_24 1.964 0.035 1.93 2 0.005-0.02

2012_06_001_A_30 2.118 0.046 2.07 2.16 0.005-0.02

2012_06_002_A_24 2.081 0.14 1.94 2.22 0.005-0.02

2012_06_002_A_27 2.524 0.123 2.4 2.65 0.005-0.02

2012_06_002_A_30 2.928 0.114 2.81 3.04 0.005-0.02

2012_06_003_A_15 2.36 0.031 2.33 2.39 0.002-0.02

2012_06_003_A_21 1.825 0.048 1.78 1.87 0.002-0.02

2013_01_002_A_42 0.937 7.33964E-05 1.853 0.04 1.81 1.89 0.002-0.02

2013_01_002_A_48 0.685 0.000127875 1.009 0.082 0.93 1.09 0.002-0.02

2013_01_002_A_54 0.621 0.000163131 0.91 0.074 0.84 0.98 0.002-0.02

2013_01_002_A_88 1.102 -4.69449E-

05 1.375 0.057 1.32 1.43 0.002-0.02

2013_01_002_A_41 0.973 0.000117608 2.044 0.034 2.01 2.08 0.002-0.02

2013_01_002_A_47 0.736 0.000271192 1.62 0.05 1.57 1.67 0.002-0.02

2013_01_002_A_53 0.655 0.000227605 1.261 0.061 1.2 1.32 0.002-0.02

2013_01_002_A_82 0.86 0.000144301 1.588 0.047 1.54 1.64 0.002-0.02

2013_01_002_A_40 1.001 -9.55625E-

06 2.25 0.036 2.21 2.29 0.002-0.02

61

2013_01_002_A_46 0.932 0.000119069 2.015 0.061 1.95 2.08 0.002-0.02

2013_01_002_A_52 0.873 0.000134367 1.735 0.074 1.66 1.81 0.002-0.02

2013_01_002_A_75 0.949 6.58116E-05 1.829 0.054 1.78 1.88 0.002-0.02

2013_02_001_A_47 2.442 0.063 2.38 2.51 0.002-0.02

2013_02_001_A_56 2.259 0.052 2.21 2.31 0.002-0.02

2013_02_001_A_62 2.072 0.07 2 2.14 0.002-0.02

2013_02_002_A_20 0.96 0.000341936 2.722 0.048 2.67 2.77 0.005-0.02

2013_02_002_A_26 0.778 0.000331882 2.367 0.06 2.31 2.43 0.005-0.02

2013_02_002_A_47 0.531 0.000257239 1.352 0.095 1.26 1.45 0.005-0.02

2013_02_002_A_62 0.502 0.000286011 1.205 0.085 1.12 1.29 0.005-0.02

2013_02_002_A_22 0.908 0.000325121 2.235 0.041 2.19 2.28 0.005-0.02

2013_02_002_A_28 0.76 0.000233457 2.156 0.052 2.1 2.21 0.005-0.02

2013_02_002_A_50 0.512 0.000244115 1.705 0.065 1.64 1.77 0.005-0.02


Parameter (1/ppm)

Fractal Dimension

95% Confidence

Interval (+/-)

Df - CI

Df + CI


2013_02_002_A_64 0.509 0.000240592 1.472 0.062 1.41 1.53 0.005-0.02

2013_02_002_A_24 0.883 0.000493 2.891 0.048 2.84 2.94 0.005-0.02

2013_02_002_A_30 0.803 0.000260534 2.547 0.042 2.51 2.59 0.005-0.02

2013_02_002_A_53 0.658 0.000201108 1.871 0.049 1.82 1.92 0.005-0.02

2013_02_002_A_66 0.667 0.000187973 1.901 0.042 1.86 1.94 0.005-0.02

2013_03_001_A_26 2.443 0.078 2.37 2.52 0.005-0.02

2013_03_001_A_32 2.378 0.046 2.33 2.42 0.005-0.02

2013_03_001_A_47 2.149 0.035 2.11 2.18 0.005-0.02

2013_03_001_A_62 2.038 0.05 1.99 2.09 0.005-0.02

2013_03_001_A_28 2.45 0.087 2.36 2.54 0.005-0.02

2013_03_001_A_34 2.559 0.044 2.52 2.6 0.005-0.02

2013_03_001_A_50 2.341 0.048 2.29 2.39 0.005-0.02

2013_03_001_A_64 2.35 0.041 2.31 2.39 0.005-0.02

2013_03_001_A_36 2.445 0.065 2.38 2.51 0.005-0.02

2013_03_001_A_53 2.475 0.048 2.43 2.52 0.005-0.02

2013_03_001_A_66 2.429 0.051 2.38 2.48 0.005-0.02

2013_03_008_A_20 0.986 6.12917E-05 1.812 0.035 1.78 1.85 0.002-0.02

2013_03_008_A_26 0.905 0.000103784 1.385 0.044 1.34 1.43 0.002-0.02

2013_03_008_A_47 0.855 7.37906E-05 0.94 0.065 0.88 1.01 0.002-0.02

2013_03_008_A_62 0.82 0.000120804 1.113 0.043 1.07 1.16 0.002-0.02

2013_03_008_A_22 0.748 0.001570618 2.048 0.02 2.03 2.07 0.002-0.02

2013_03_008_A_28 0.691 0.00056375 1.692 0.019 1.67 1.71 0.002-0.02

2013_03_008_A_50 0.654 0.00031603 1.377 0.026 1.35 1.4 0.002-0.02

2013_03_008_A_64 0.622 0.000434803 1.302 0.045 1.26 1.35 0.002-0.02

2013_03_008_A_24 0.948 0.000169246 1.879 0.031 1.85 1.91 0.002-0.02

62

2013_03_008_A_30 0.881 0.000143677 1.548 0.03 1.52 1.58 0.002-0.02

2013_03_008_A_53 0.852 0.000117948 1.382 0.04 1.34 1.42 0.002-0.02

2013_03_008_A_66 0.824 0.00019689 1.539 0.04 1.5 1.58 0.002-0.02

2013_04_001_A_20 1.004 -2.18395E-

05 2.373 0.028 2.35 2.4 0.002-0.02

2013_04_001_A_26 0.82 0.00012502 1.162 0.054 1.11 1.22 0.002-0.02

2013_04_001_A_22 0.945 0.000123036 1.857 0.046 1.81 1.9 0.002-0.02

2013_04_001_A_24 0.909 0.000197904 1.77 0.052 1.72 1.82 0.002-0.02

2013_04_001_A_30 0.735 0.000149866 1.16 0.025 1.14 1.19 0.002-0.02

2013_04_018_A_20 0.9 0.000963156 2.208 0.049 2.16 2.26 0.002-0.02

2013_04_018_A_26 0.704 0.000316656 1.448 0.048 1.4 1.5 0.002-0.02

2013_04_018_A_32 0.565 0.000289126 1.013 0.062 0.95 1.08 0.002-0.02

2013_04_018_A_22 0.87 0.000554095 1.794 0.023 1.77 1.82 0.002-0.02

2013_04_018_A_28 0.665 0.000371394 1.454 0.035 1.42 1.49 0.002-0.02

2013_04_018_A_50 0.495 0.000338424 1.065 0.033 1.03 1.1 0.002-0.02

2013_04_018_A_64 0.545 0.000313865 1.113 0.039 1.07 1.15 0.002-0.02

2013_04_018_A_24 0.874 0.000964434 1.755 0.034 1.72 1.79 0.002-0.02


Parameter (1/ppm)

Fractal Dimension

95% Confidence

Interval (+/-)

Df - CI

Df + CI


2013_04_018_A_30 0.73 0.000584769 1.477 0.043 1.43 1.52 0.002-0.02

2013_04_018_A_53 0.58 0.000466247 1.184 0.045 1.14 1.23 0.002-0.02

2013_04_018_A_66 0.66 0.000516084 1.193 0.051 1.14 1.24 0.002-0.02

2013_06_002_A_20 1 0 2 0.023 1.98 2.02 0.002-0.02

2013_06_002_A_26 0.936 7.77677E-05 1.65 0.032 1.62 1.68 0.002-0.02

2013_06_002_A_32 0.787 0.000138361 1.25 0.048 1.2 1.3 0.002-0.02

2013_06_002_A_22 0.998 7.91845E-06 2.06 0.017 2.04 2.08 0.002-0.02

2013_06_002_A_28 0.913 0.000109556 1.72 0.02 1.7 1.74 0.002-0.02

2013_06_002_A_50 0.804 9.63493E-05 1.17 0.034 1.14 1.2 0.002-0.02

2013_06_002_A_64 0.811 0.000120775 1.38 0.025 1.36 1.41 0.002-0.02

2013_06_002_A_24 1.92 0.035 1.89 1.96 0.002-0.02

2013_06_002_A_30 1.58 0.039 1.54 1.62 0.002-0.02

2013_06_002_A_53 1.29 0.045 1.25 1.34 0.002-0.02

2013_06_002_A_66 1.34 0.053 1.29 1.39 0.002-0.02

2013_08_001_A_20 0.8 0.000949388 1.93 0.036 1.89 1.97 0.002-0.02

2013_08_001_A_26 0.89 5.59141E-05 1.3 0.046 1.25 1.35 0.002-0.02

2013_08_001_A_47 0.64 0.000121416 0.319 0.07 0.25 0.39 0.002-0.02

2013_08_001_A_62 0.651 0.000126675 0.511 0.055 0.46 0.57 0.002-0.02

2013_08_001_A_22 0.97 7.1707E-05 2.05 0.032 2.02 2.08 0.002-0.02

2013_08_001_A_28 0.84 0.000106701 1.42 0.036 1.38 1.46 0.002-0.02

2013_08_001_A_50 0.67 0.000140859 0.529 0.053 0.48 0.58 0.002-0.02

2013_08_001_A_64 0.77 0.000120096 1.01 0.047 0.96 1.06 0.002-0.02

63

2013_08_001_A_24 0.93 0.000147121 1.81 0.03 1.78 1.84 0.002-0.02

2013_08_001_A_30 0.83 0.00015844 1.48 0.03 1.45 1.51 0.002-0.02

2013_08_001_A_53 0.735 0.000149866 1.13 0.026 1.1 1.16 0.002-0.02

2013_08_001_A_66 0.83 0.000178651 1.46 0.04 1.42 1.5 0.002-0.02

2013_08_002_A_20 0.988 1.72 0.047 1.67 1.77 0.002-0.02

2013_08_002_A_26 0.92 0.000405448 2 0.074 1.93 2.07 0.002-0.02

2013_08_002_A_47 0.827 0.000174792 1.64 0.1 1.54 1.74 0.002-0.02

2013_08_002_A_62 1.03 -3.22433E-

05 1.79 0.093 1.7 1.88 0.002-0.02

2013_08_002_A_22 0.96 2.25 0.039 2.21 2.29 0.002-0.02

2013_08_002_A_28 0.881 0.000589175 2.43 0.051 2.38 2.48 0.002-0.02

2013_08_002_A_50 0.782 0.000262707 1.95 0.079 1.87 2.03 0.002-0.02

2013_08_002_A_64 0.915 0.000134768 2.11 0.077 2.03 2.19 0.002-0.02

2013_08_002_A_24 0.97 2.3 0.039 2.26 2.34 0.002-0.02

2013_08_002_A_30 0.914 0.00047023 2.27 0.048 2.22 2.32 0.002-0.02

2013_08_002_A_53 0.856 0.000254227 2.12 0.073 2.05 2.19 0.002-0.02

2013_08_002_A_66 0.91 0.000371422 2.33 0.052 2.28 2.38 0.002-0.02

2013_08_003_A_20 0 0

2013_08_003_A_26 1.89 0.151 1.74 2.04 0.002-0.02

2013_08_003_A_47 2.34 0.049 2.29 2.39 0.002-0.02


Parameter (1/ppm)

Fractal Dimension

95% Confidence

Interval (+/-)

Df - CI

Df + CI


2013_08_003_A_62 2.04 0.057 1.98 2.1 0.002-0.02

2013_08_003_A_22 0 0

2013_08_003_A_28 0 0

2013_08_003_A_50 2.08 0.127 1.95 2.21 0.005-0.015

2013_08_003_A_64 3.1 0.163 2.94 3.26 0.005-0.015

2013_08_003_A_24 1.32 0.242 1.08 1.56 0.005-0.012

2013_08_003_A_30 0 0

2013_08_003_A_53 2.7 0.464 2.24 3.16 0.005-0.012

2013_08_003_A_66 0 0

2013_09_001_A_20 0.99 0.889 0.1574 0.73 1.05 0.003-0.02

2013_09_001_A_26 1.01 1.136 0.1448 0.99 1.28 0.003-0.02

2013_09_001_A_47 1.014 2.265 0.2435 2.02 2.51 0.003-0.02

2013_09_001_A_62 1.077 1.595 0.1288 1.47 1.72 0.003-0.02

2013_09_001_A_22 1.002 1.138 0.2205 0.92 1.36 0.008-0.02

2013_09_001_A_28 1.01 1.352 0.2146 1.14 1.57 0.008-0.02

2013_09_001_A_50 1.015 1.574 0.174 1.4 1.75 0.008-0.02

2013_09_001_A_64 1.048 0 0

2013_09_001_A_24 0.999 0 0

2013_09_001_A_30 1.002 0 0

64

2013_09_001_A_53 1.011 0 0

2013_09_001_A_66 1.033 0 0

2013_09_002_A_20 0.885 0.001015936 2.044 0.0382 2.01 2.08 0.002-0.02

2013_09_002_A_26 0.72 0.000550961 1.554 0.0218 1.53 1.58 0.002-0.02

2013_09_002_A_47 0.47 0.000534557 1.092 0.0255 1.07 1.12 0.002-0.02

2013_09_002_A_62 0.54 0.000530629 1.142 0.0265 1.12 1.17 0.002-0.02

2013_09_002_A_22 0.89 0.000999965 1.721 0.0497 1.67 1.77 0.002-0.02

2013_09_002_A_28 0.69 0.001040095 1.584 0.0351 1.55 1.62 0.002-0.02

2013_09_002_A_50 0.512 0.000891351 1.363 0.0291 1.33 1.39 0.002-0.02

2013_09_002_A_64 0.55 0.000900258 1.423 0.0338 1.39 1.46 0.002-0.02

2013_09_002_A_24 0.96 0.000445372 2.297 0.0436 2.25 2.34 0.002-0.02

2013_09_002_A_30 0.8 0.000967492 2.1 0.0278 2.07 2.13 0.002-0.02

2013_09_002_A_53 0.69 0.000733304 1.785 0.0351 1.75 1.82 0.002-0.02

2013_09_002_A_66 0.72 0.000731604 1.864 0.0331 1.83 1.9 0.002-0.02

Sample ID Straight

Transmission (%)

Dyn. Viscosity

Fluid, From Pang

(kg/(m*s))

Clean Bed d50 calc

with Kozeny Carmen

(m)

Reynolds Number,

Clean Bed d50

Aggregate Radius of

Gyration (m)

2012_03_001_A_6 0.0027478

2012_03_001_A_7 0.0027478

2012_03_001_A_11 0.0027478

2012_04_002_A_15 0.0027478

2012_05_001_A_12 0.0027478

2012_05_001_A_15 0.0027478

2012_05_001_A_21 0.0027478

2012_05_001_A_27 0.0027478

2012_06_001_A_12 0.0027478

2012_06_001_A_18 0.0027478

2012_06_001_A_24 0.0027478

2012_06_001_A_30 0.0027478

2012_06_002_A_24 0.0027478

2012_06_002_A_27 0.0027478

2012_06_002_A_30 0.0027478

2012_06_003_A_15 0.0027478

2012_06_003_A_21 0.0027478

2013_01_002_A_42 0.7 0.0027478 0.00306899 1.590061815 0.00120099

2013_01_002_A_48 0.1 0.0027478 0.00306899 1.590061815 18.9

2013_01_002_A_54 0.1 0.0027478 0.00306899 1.590061815 162.9

2013_01_002_A_88 0.2 0.0027478 0.00306899 1.590061815 0.070543303

2013_01_002_A_41 5.6 0.0027478 0.00349919 1.812949406 0.00024343

65

2013_01_002_A_47 0.4 0.0027478 0.00349919 1.812949406 0.006130301

2013_01_002_A_53 0.2 0.0027478 0.00349919 1.812949406 0.257430453

2013_01_002_A_82 0.6 0.0027478 0.00349919 1.812949406 0.007198757

2013_01_002_A_40 16 0.0027478 0.00201134 1.042085583 7.85844E-05

2013_01_002_A_46 1.2 0.0027478 0.00201134 1.042085583 0.000438965

2013_01_002_A_52 0.5 0.0027478 0.00201134 1.042085583 0.002588433

2013_01_002_A_75 0.8 0.0027478 0.00201134 1.042085583 0.001288721

2013_02_001_A_47 4.2 0.0027478 0.0

2013_02_001_A_56 3.7 0.0027478 0.0

2013_02_001_A_62 2.6 0.0027478 0.0

2013_02_002_A_20 7.6 0.0027478 0.00316179 0.855507561 2.28959E-05

2013_02_002_A_26 0.6 0.0027478 0.00316179 0.855507561 0.000126917

2013_02_002_A_47 0.1 0.0027478 0.00316179 0.855507561 0.1

2013_02_002_A_62 0.1 0.0027478 0.00313237 0.831853823 0.7

2013_02_002_A_22 5.2 0.0027478 0.00262811 0.711105939 0.000129938

2013_02_002_A_28 0.5 0.0027478 0.00262811 0.711105939 0.000334394

2013_02_002_A_50 0.1 0.0027478 0.00262811 0.711105939 0.0

Sample ID Straight

Transmission (%)

Dyn. Viscosity

Fluid, From Pang

(kg/(m*s))

Clean Bed d50 calc

with Kozeny Carmen

(m)

Reynolds Number,

Clean Bed d50

Aggregate Radius of

Gyration (m)

2013_02_002_A_64 0.1 0.0027478 0.00260366 0.69144473 0.037803485

2013_02_002_A_24 3.1 0.0027478 0.00275638 0.745814201 2.09565E-05

2013_02_002_A_30 0.5 0.0027478 0.00275638 0.745814201 0.0

2013_02_002_A_53 0.1 0.0027478 0.00275638 0.745814201 0.0

2013_02_002_A_66 0.1 0.0027478 0.00273074 0.72519335 0.0

2013_03_001_A_26 5.5 0.0027478 0.0

2013_03_001_A_32 1 0.0027478 0.0

2013_03_001_A_47 0.2 0.0027478 0.0

2013_03_001_A_62 0.2 0.0027478 0.0

2013_03_001_A_28 4.7 0.0027478 0.0

2013_03_001_A_34 0.9 0.0027478 0.0

2013_03_001_A_50 0.3 0.0027478 0.0

2013_03_001_A_64 0.3 0.0027478 0.000163405

2013_03_001_A_36 5.5 0.0027478 6.33965E-05

2013_03_001_A_53 2 0.0027478 7.25449E-05

2013_03_001_A_66 2.2 0.0027478 8.3603E-05

2013_03_008_A_20 7.4 0.0027478 0.00180955 1.053594383 0.001142425

2013_03_008_A_26 0.8 0.0027478 0.00180955 1.053594383 0.070667964

2013_03_008_A_47 0.2 0.0027478 0.00180955 1.053594383 132.2003646

2013_03_008_A_62 0.3 0.0027478 0.00182041 1.072692483 3.670156468

66

2013_03_008_A_22 6.5 0.0027478 0.00098665 0.574472081 0.000336459

2013_03_008_A_28 1 0.0027478 0.00098665 0.574472081 0.00454141

2013_03_008_A_50 0.3 0.0027478 0.00098665 0.574472081 0.103856711

2013_03_008_A_64 0.4 0.0027478 0.00099258 0.584885315 0.206086052

2013_03_008_A_24 4.1 0.0027478 0.00106094 0.617724462 0.000951972

2013_03_008_A_30 0.8 0.0027478 0.00106094 0.617724462 0.015199454

2013_03_008_A_53 0.4 0.0027478 0.00106094 0.617724462 0.094559229

2013_03_008_A_66 0.7 0.0027478 0.00106731 0.628921716 0.017751557

2013_04_001_A_20 6.3 0.0027478 0.00096433 0.288466613 9.78218E-05

2013_04_001_A_26 0.2 0.0027478 0.00096433 0.288466613 1.664349307

2013_04_001_A_22 2.4 0.0027478 0.00084692 0.253344944 0.001309999

2013_04_001_A_24 2.1 0.0027478 0.00092775 0.277525481 0.002224465

2013_04_001_A_30 0.2 0.0027478 0.00092775 0.277525481 2.193772665

2013_04_018_A_20 11.1 0.0027478 0.00087566 0.123731943 0.000137698

2013_04_018_A_26 0.5 0.0027478 0.00087566 0.123731943 0.04410279

2013_04_018_A_32 0.1 0.0027478 0.00087566 0.123731943 28.75836996

2013_04_018_A_22 9 0.0027478 0.00082639 0.116769461 0.001350119

2013_04_018_A_28 0.6 0.0027478 0.00082639 0.116769461 0.041854654

2013_04_018_A_50 0.1 0.0027478 0.00082639 0.116769461 11.6751359

2013_04_018_A_64 0.2 0.0027478 0.00082639 0.116769461 4.672322302

2013_04_018_A_24 14.5 0.0027478 0.00089144 0.125961527 0.001209388

Sample ID Straight

Transmission (%)

Dyn. Viscosity

Fluid, From Pang

(kg/(m*s))

Clean Bed d50 calc

with Kozeny Carmen

(m)

Reynolds Number,

Clean Bed d50

Aggregate Radius of

Gyration (m)

2013_04_018_A_30 2 0.0027478 0.00089144 0.125961527 0.020561448

2013_04_018_A_53 0.5 0.0027478 0.00089144 0.125961527 1.005206277

2013_04_018_A_66 1.1 0.0027478 0.00089144 0.125961527 0.630352498

2013_06_002_A_20 12.4 0.0027478 0.00115259 0.693032259 0.000366077

2013_06_002_A_26 1 0.0027478 0.00115259 0.693032259 0.006774995

2013_06_002_A_32 0.3 0.0027478 0.00115259 0.693032259 0.533611598

2013_06_002_A_22 5.4 0.0027478 0.00072637 0.436755022 0.000359255

2013_06_002_A_28 0.8 0.0027478 0.00072637 0.436755022 0.004156715

2013_06_002_A_50 0.1 0.0027478 0.00072637 0.436755022 2.012229437

2013_06_002_A_64 0.2 0.0027478 0.00072637 0.436755022 0.116339697

2013_06_002_A_24 2.7 0.0027478 0.000864803

2013_06_002_A_30 0.7 0.0027478 0.012396401

2013_06_002_A_53 0.3 0.0027478 0.308253184

2013_06_002_A_66 0.3 0.0027478 0.15102743

2013_08_001_A_20 5.2 0.0027478 0.0010372 0.616373682 0.000589769

2013_08_001_A_26 0.2 0.0027478 0.0010372 0.616373682 0.282925571

67

2013_08_001_A_47 0.1 0.0027478 0.0010372 0.616373682 1.06488E+21

2013_08_001_A_62 0.1 0.0027478 0.0010372 0.616373682 20893601259

2013_08_001_A_22 1.7 0.0027478 0.00085356 0.507245461 0.000445533

2013_08_001_A_28 0.2 0.0027478 0.00085356 0.507245461 0.065045781

2013_08_001_A_50 0.1 0.0027478 0.00085356 0.507245461 3724762065

2013_08_001_A_64 0.1 0.0027478 0.00085356 0.507245461 26.1647877

2013_08_001_A_24 2.2 0.0027478 0.00084982 0.505023613 0.001613166

2013_08_001_A_30 0.4 0.0027478 0.00084982 0.505023613 0.029562767

2013_08_001_A_53 0.1 0.0027478 0.00084982 0.505023613 2.998761227

2013_08_001_A_66 0.6 0.0027478 0.00084982 0.505023613 0.032640061

2013_08_002_A_20 31.8 0.0027478 0.00362548 2.276222514 0.000540176

2013_08_002_A_26 6.3 0.0027478 0.00362548 2.276222514 0.000278526

2013_08_002_A_47 0.4 0.0027478 0.00362548 2.276222514 0.005123412

2013_08_002_A_62 0.5 0.0027478 0.00362548 2.276222514 0.001726338

2013_08_002_A_22 28.5 0.0027478 0.00234916 1.474892651 6.04099E-05

2013_08_002_A_28 4.4 0.0027478 0.00234916 1.474892651 6.25779E-05

2013_08_002_A_50 0.4 0.0027478 0.00234916 1.474892651 0.000770819

2013_08_002_A_64 0.8 0.0027478 0.00234916 1.474892651 0.000309685

2013_08_002_A_24 31.2 0.0027478 0.00224061 1.406743164 5.31522E-05

2013_08_002_A_30 7.7 0.0027478 0.00224061 1.406743164 9.74401E-05

2013_08_002_A_53 1.1 0.0027478 0.00224061 1.406743164 0.000289244

2013_08_002_A_66 4.4 0.0027478 0.00224061 1.406743164 9.07243E-05

2013_08_003_A_20 44.9 0.0027478

2013_08_003_A_26 42.5 0.0027478

2013_08_003_A_47 27.8 0.0027478

Sample ID Straight

Transmission (%)

Dyn. Viscosity

Fluid, From Pang

(kg/(m*s))

Clean Bed d50 calc

with Kozeny Carmen

(m)

Reynolds Number,

Clean Bed d50

Aggregate Radius of

Gyration (m)

2013_08_003_A_62 24 0.0027478

2013_08_003_A_22 53.9 0.0027478

2013_08_003_A_28 50.2 0.0027478

2013_08_003_A_50 42.4 0.0027478

2013_08_003_A_64 37.8 0.0027478

2013_08_003_A_24 60.2 0.0027478

2013_08_003_A_30 59.8 0.0027478

2013_08_003_A_53 62.5 0.0027478

2013_08_003_A_66 54 0.0027478

2013_09_001_A_20 31.7 0.0027478 0.0109947 6.48972679 1.069505625

2013_09_001_A_26 31.4 0.0027478 0.0109947 6.48972679 0.029620503

2013_09_001_A_47 30.7 0.0027478 0.0109947 6.48972679 2.87895E-05

2013_09_001_A_62 31.7 0.0027478 0.0109947 6.48972679 0.000557106

68

2013_09_001_A_22 36.5 0.0027478 0.00744899 4.396838481 0.017997839

2013_09_001_A_28 36.2 0.0027478 0.00744899 4.396838481 0.00223531

2013_09_001_A_50 34.8 0.0027478 0.00744899 4.396838481 0.000589363

2013_09_001_A_64 36.9 0.0027478 0.00744899 4.396838481

2013_09_001_A_24 39 0.0027478 0.00755289 4.458164156

2013_09_001_A_30 38.8 0.0027478 0.00755289 4.458164156

2013_09_001_A_53 36.4 0.0027478 0.00755289 4.458164156

2013_09_001_A_66 40.5 0.0027478 0.00755289 4.458164156

2013_09_002_A_20 9.6 0.0027478 0.00072164 0.05467226 0.000271591

2013_09_002_A_26 1.2 0.0027478 0.00072164 0.05467226 0.011634635

2013_09_002_A_47 0.3 0.0027478 0.00072164 0.05467226 5.163190695

2013_09_002_A_62 0.4 0.0027478 0.00072544 0.055542366 1.882479892

2013_09_002_A_22 14 0.0027478 0.00074256 0.056257292 0.001323948

2013_09_002_A_28 3 0.0027478 0.00074256 0.056257292 0.006710885

2013_09_002_A_50 0.8 0.0027478 0.00074256 0.056257292 0.082431212

2013_09_002_A_64 1 0.0027478 0.00074647 0.057152623 0.040898899

2013_09_002_A_24 14.4 0.0027478 0.00088382 0.06695957 9.335E-05

2013_09_002_A_30 4.6 0.0027478 0.00088382 0.06695957 0.000298522

2013_09_002_A_53 1.4 0.0027478 0.00088382 0.06695957 0.002173941

2013_09_002_A_66 1.8 0.0027478 0.00088848 0.068025228 0.00129225

Sample ID Comments

2012_03_001_A_6 No Salt

2012_03_001_A_7 No Salt

2012_03_001_A_11 No Salt

2012_04_002_A_15 Questionable head data, due to changes in salt conc effect on Nafion



2012_05_001_A_21 Questionable head data, due to changes in salt conc effect on Nafion, Clear started at 196 ml eluted

2012_05_001_A_27 Volume clear eluded after deposition,

2012_06_001_A_12 Head data taken before and after scan only

2012_06_001_A_18 Head data taken before and after scan only

2012_06_001_A_24 Head data taken before and after scan only, Clear started at 182 ml eluted

2012_06_001_A_30 Volume clear eluded after deposition, same head data

2012_06_002_A_24

2012_06_002_A_27 Clear started at 188 ml eluted

2012_06_002_A_30 Volume clear eluded after deposition, same head data

2012_06_003_A_15 Later scans look bad

69

2012_06_003_A_21 Later scans look bad

2013_01_002_A_42 deposition


2013_01_002_A_54 No Flow, after deposition, Clear started at 377 ml eluted

2013_01_002_A_88 clear flow with partial recycle









2013_02_001_A_47 No Flow, after deposition, Nafion/salt problems, No Pressure Equilibrium, Clear Flow started at 356 ml eluted

2013_02_001_A_56 clear flow, nafion problems, No Pressure Equilibrium

2013_02_001_A_62 clear flow, nafion problems, No Pressure Equilibrium

2013_02_002_A_20 deposition, Nafion Equil Not Great


2013_02_002_A_47 deposition, no flow, Nafion Equil Not Great, Clear flow started at 332 ml eluted

2013_02_002_A_62 Clear Flow, Nafion Equil Not Great




Sample ID Comments






2013_03_001_A_26 deposition, bad head data


2013_03_001_A_47 deposition, no flow, bad head data, Clear flow started at 343 ml eluted

2013_03_001_A_62 Clear Flow, bad head data







70




2013_03_008_A_47 deposition, no flow, Clear flow started at 485 ml eluted

2013_03_008_A_62 Clear Flow




2013_03_008_A_64 Clear Flow




2013_03_008_A_66 Clear Flow

2013_04_001_A_20 deposition, scan maxed out at later times





2013_04_018_A_20 deposition, scan maxed out at later times


2013_04_018_A_32 deposition, no flow




2013_04_018_A_64 Clear Flow


Sample ID Comments



2013_04_018_A_66 Clear Flow

2013_06_002_A_20 Deposittion flow, bad later data






2013_06_002_A_64 Clear Flow

2013_06_002_A_24 No Transducer DATA Dep Flow

2013_06_002_A_30 No Transducer DATA Dep Flow

71

2013_06_002_A_53 No Transducer DATA Dep Flow, No Flow, Clear flow started at 492 ml eluted

2013_06_002_A_66 No Transducer DATA Clear Flow




2013_08_001_A_62 Clear Flow.



2013_08_001_A_50 deposition, no flow, , Clear flow started at 513 ml eluted

2013_08_001_A_64 Clear Flow




2013_08_001_A_66 Clear Flow




2013_08_002_A_62 Clear Flow.




2013_08_002_A_64 Clear Flow




2013_08_002_A_66 Clear Flow

2013_08_003_A_20 deposition, No Nafion Equilibrium


2013_08_003_A_47 deposition, no flow, No Nafion Equilibrium , Clear flow started at 521 ml eluted

Sample ID Comments

2013_08_003_A_62 Clear Flow. , No Nafion Equilibrium



2013_08_003_A_50 deposition, no flow, , No Nafion Equilibrium , Clear flow started at 521 ml eluted

2013_08_003_A_64 Clear Flow, No Nafion Equilibrium



2013_08_003_A_53 deposition, no flow, No Nafion Equilibrium , Clear flow started at 521 ml eluted

2013_08_003_A_66 Clear Flow, No Nafion Equilibrium

72




2013_09_001_A_62 Clear Flow.




2013_09_001_A_64 Clear Flow, No Clear Linear Region for Df

2013_09_001_A_24 deposition, No Clear Linear Region for Df

2013_09_001_A_30 deposition, No Clear Linear Region for Df

2013_09_001_A_53 deposition, no flow, No Clear Linear Region for Df, Clear flow started at 527 ml eluted

2013_09_001_A_66 Clear Flow, No Clear Linear Region for Df




2013_09_002_A_62 Clear Flow.




2013_09_002_A_64 Clear Flow




2013_09_002_A_66 Clear Flow

73

Results From Rifle Samples

Collected 4-15-13

Well ID Sample

# Scan ID

Settled /

Agitated Sample

SLS Amplification

Flow rate

(ml/min)

Colloid Concentration

(g/ml)

Colloid Concentration

(ppm)

LR01 2 2013_04_003_A_2 Settled 0.65 650 1.86047E-05 18.60465116

LR01 2 2013_04_003_B_1 Agitated 0.65 650 1.86047E-05 18.60465116

LR01 3 2013_04_004_A_2 Settled 0.65 0 1.86047E-05 18.60465116

LR01 3 2013_04_004_B_2 Agitated 0.65 0 1.86047E-05 18.60465116

FP101 6 2013_04_006_A_2 Settled 0.65 640 6.74419E-06 6.744186047

FP101 6 2013_04_006_B_1 Agitated 0.65 640 6.74419E-06 6.744186047

FP101 7 2013_04_007_B_2 Agitated 0.65 0 6.74419E-06 6.744186047

CD03 10 2013_04_009_A_2 Settled 0.45 880 1.51163E-05 15.11627907

CD03 10 2013_04_009_B_2 Agitated 0.45 880 1.51163E-05 15.11627907

CD03 11 2013_04_010_A_2 Settled 0.45 0 1.51163E-05 15.11627907

CD03 11 2013_04_010_B_2 Agitated 0.45 0 1.51163E-05 15.11627907

G51 14 2013_04_012_A_2 Settled 0.45 450 1.81395E-05 18.13953488

G51 14 2013_04_012_B_2 Agitated 0.45 450 1.81395E-05 18.13953488

G51 15 2013_04_013_A_2 Settled 0.45 0 1.81395E-05 18.13953488

G51 15 2013_04_013_B_2 Agitated 0.45 0 1.81395E-05 18.13953488

Well ID pH Temperature

(deg C) Conductivity

(uS/cm)

Ionic Strength

(M)

Fractal Dimension

R^2 95% Conf

Interv

LR01 7.44 10.8 1634 0.026144 2.21 0.958 0.111

LR01 7.44 10.8 1634 0.026144 1.71 0.898 0.139

LR01 7.44 10.8 1634 0.026144 2.45 0.974 0.096

LR01 7.44 10.8 1634 0.026144 1.52 0.939 0.093

FP101 7.26 9.4 3300 0.0528 1.69 0.943 0.1

FP101 7.26 9.4 3300 0.0528 1.81 0.958 0.092

FP101 7.26 9.4 3300 0.0528 2.27 0.916 0.166

CD03 7.3 9 3100 0.0496 1.74 0.984 0.054

CD03 7.3 9 3100 0.0496 1.82 0.984 0.056

CD03 7.3 9 3100 0.0496 1.96 0.979 0.07

CD03 7.3 9 3100 0.0496 2.09 0.972 0.086

G51 7.51 8.2 2785 0.04456 1.85 0.994 0.034

G51 7.51 8.2 2785 0.04456 1.82 0.993 0.036

G51 7.51 8.2 2785 0.04456 1.78 0.987 0.05

G51 7.51 8.2 2785 0.04456 1.71 0.979 0.06

74

Well ID Comments

LR01 Unknown Colloids, Monitor Well




FP101 Clay Colloids, Monitor Well



CD03 Ferric Oxide Colloids, Acetate and Dissolved O2 Injections




G51 Bio-colloids, Well Clogged Due to 3 Successive Acetate Injections




75

Appendix B

Additional Method Information

Specific Deposit Calibration Curve

Motivation

In order to quantify the effect of deposit fractal dimension on permeability, it is crucial that

we also know the specific deposit of colloidal aggregates in the precise area of the flow cell that is

being scanned. Prior to this technique, we had planned to employ a mass balance approach using a

spectrometer at the 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.

76

Data Analysis

Average the intensity data throughout the cell for each concentration, leaving out any data

scanned in a region with bubbles or contaminants. Analyze the data as if it were a normal SLS scan.

For the Concentration Curve, plot intensity values at Q = 1/r versus the concentration for that scan.

Results

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).

Table 1: I’ vs concentration.

Colloid

Concentration

(ppm)

I' at 1/r

1st Set

(mV)

I' at 1/r

2nd Set

(mV)

I' at 1/r

3rd Set

(mV)

I' at 1/r

Average

(mV)

Standard

Deviation

(mV)

0 7.96E-11 7.01E-11 5.26E-11 6.74E-11 1.37E-11

0.802568218 8.18E-11 5.17E-11 6.54E-11 6.63E-11 1.51E-11

2.407704655 9.90E-11 7.17E-11 6.84E-11 7.97E-11 1.68E-11

8.025682183 5.52E-10 4.07E-10 4.02E-10 4.54E-10 8.53E-11

24.07704655 5.89E-10 3.60E-10 5.47E-10 4.99E-10 1.22E-10

80.25682183 1.12E-09 1.09E-09 1.59E-09 1.27E-09 2.80E-10

240.7704655 2.23E-08 2.87E-08 3.07E-08 2.72E-08 4.40E-09

1E-11

1E-10

1E-09

1E-08

1E-07

1E-06

1E-05

0.0001 0.001 0.01

I' (

mV

)

q^-1 (nm^-1)

I' vs q^-1

0.45 Amp All Sets

0ppm 2012_10_001_A

1ppm 2012_10_002_A

3ppm 2012_10_003_A

10ppm 2012_10_004_A

30ppm 2012_10_005_A

100ppm 2012_11_001_A

300ppm 2012_11_002_A

0 ppm 2012_11_004_A Duplicate







0 ppm 2012_12_001_A Triplicate







77

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.

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)

I" at 1/r

Average

(mV)

Standard

Deviation

(mV)

0.802568218 2.22E-12 -1.84E-11 1.28E-11

-1.12E-

12 1.59E-11

2.407704655 1.95E-11 1.65E-12 1.58E-11

1.23E-

11 9.41E-12

8.025682183 4.73E-10 3.37E-10 3.49E-10

3.86E-

10 7.50E-11

24.07704655 5.10E-10 2.90E-10 4.94E-10

4.31E-

10 1.23E-10

80.25682183 1.04E-09 1.02E-09 1.54E-09

1.20E-

09 2.92E-10

240.7704655 2.22E-08 2.86E-08 3.07E-08

2.72E-

08 4.41E-09

1.00E-11

1.00E-10

1.00E-09

1.00E-08

1.00E-07

0.1 1 10 100 1000

I' (

mV

)

Concentration (ppm)

I' vs Concentration

1st Set

2nd Set

3rd Set

Average

78

Figure 3: I” vs concentration

Figure 4: I” vs concentration average, with exponential trend-line and standard deviation error bars.

Later scans at different ionic strength and colloid concentrations are summarized in figure 5.

Note that triplicate scans were not made for higher concentrations.

1.00E-11

1.00E-10

1.00E-09

1.00E-08

1.00E-07

0.1 1 10 100 1000

I' (

mV

)

Concentration (ppm)

I" vs Concentration

1st Set

2nd Set

3rd Set

Average

y = 3E-10e0.0187x

R² = 0.9976

1.00E-11

1.00E-10

1.00E-09

1.00E-08

1.00E-07

1 10 100 1000

I' (

mV

)

Concentration (ppm)

I" vs Concentration

Average

Expon. (Average)

79

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.

y = 3E+06x0.515

R² = 0.9304

0

200

400

600

800

1000

1200

1400

0 5E-08 0.0000001 1.5E-07 0.0000002 2.5E-07 0.0000003

Co

nce

ntr

ati

on

(p

pm

)

I" (mV)

Concentration vs I" 2 mM, 8mM, and

16 mM

2 mM

16 mM

All

8 mM

Power (All)

80

Working with Nafion

Nafion is, as far as we have found, the most suitable index matched porous media material for

use in our colloidal clogging experiments. Most importantly, Nafion is nicely index matched with a

fairly benign solution of isopropanol and water. The pore scale properties of the Nafion grains

effectively retain enough colloidal aggregate to cause 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.

81

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, bio-

films will be grown on water jewels then sent to our lab for analysis. One assemblage of water jewels

will be used for bio-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 non-

representative of the sample containing bio-films.

Methods

A column will be loosely packed with hydrated water jewels, and then filled with deionized water.

SLS scans will be performed on the column at three amplification levels: 0.25, 0.45, and 0.65 amp.

The column will then be removed from the apparatus, inverted several times to redistribute the water

jewels, and then rescanned at the same amplifications. The data will 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

1E-13

1E-12

1E-11

0.0001 0.001 0.01

Inte

nsi

ty, I'

(m

V)

Q (nm^-1)

Water Jewel Blank Test, 0.25 Amp

Scan 1

Scan 2, Agitated

1E-12

1E-11

1E-10

1E-09

1E-08

0.0001 0.001 0.01

Inte

nsi

ty, I'

(m

V)

Q (nm^-1)


Scan 1

Scan 2, Agitated

82

Interpretation

It appears that water jewel packing has little effect on SLS measurement. Any differences between

the two scan sets appear to be noise since they are not repeated at different amplifications. For

comparison, a plot of a Nafion blank has been included, showing that the Nafion scatters substantially

more light than the water jewels. Also, the water jewels have a transmission factor of about 86%,

which is very good, especially when compared with the Nafion which is closer to 10%. The

conclusion is that water jewels should work very well for the bio-film scans.

Further Information

Prior to this experiment, Ben Gilbert asked if the water jewels could be sterilized. So dehydrated

water jewels were placed in an autoclave. After sterilization the water jewels were hydrated with

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.

1E-12

1E-11

1E-10

1E-09

1E-08

0.0000001

0.0001 0.001 0.01

Inte

nsi

ty, I'

(m

V)

Q (nm^-1)


Scan 1

Scan 2, Agitated

1E-11

1E-10

1E-09

1E-08

0.0000001

0.0001 0.001 0.01

Inte

nsi

ty, I'

(m

V)

Q (nm^-1)

Nafion Blank at 0.3 Amp

Nafion Blank

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LINKING COLLOID DEPOSIT MORPHOLOGY AND CLOGGING