OCS Study 

MMS 2006-028 

 

Degradation of Synthetic-Based 

Drilling Mud Base Fluids 

by Gulf of Mexico Sediments 

Final Report 

U.S. Department of the Interior

Minerals Management Service 

Gulf of Mexico OCS Region 
U.S. Department of the Interior

Minerals Management Service 

Gulf of Mexico OCS Region 

OCS Study 

MMS 2006-028 

Degradation of Synthetic-Based 

Drilling Mud Base Fluids 

by Gulf of Mexico Sediments 

Final Report 

Authors 

Deborah J. Roberts 

Alan H. Nguyen 

Prepared under MMS Contract 

1435-01-01-CA-31179 

by 

University of Houston 

Department of Civil and 

 Environmental Engineering 

N107 Engineering Bldg. 1 

Houston, Texas 77204-4003 

Published by 

New Orleans

May 2006 
iii

DISCLAIMER 

This report was prepared under contract between the Minerals Management Service (MMS) and 

the University of Houston. This report has been technically reviewed by the MMS, and it has 

been approved for publication. Approval does not signify that the contents necessarily reflect the 

views and policies of the MMS, nor does mention of trade names or commercial products 

constitute endorsement or recommendation for use. It is, however, exempt from review and 

compliance with MMS editorial standards. 

REPORT AVAILABILITY 

Extra copies of this report may be obtained by the Public Information Office (Mail Stop 5034) at 

the following address: 

 U.S. Department of the Interior 

 Minerals Management Service 

 Gulf of Mexico OCS Region 

 Public Information Office (MS 5034) 

 1201 Elmwood Park Boulevard 

 New Orleans, Louisiana 70123-2394 

 Telephone: (504) 736-2519 or 

 1-800-200-GULF 

CITATION 

Suggested citation: 

Roberts, D.J. and A.H. Nguyen. 2006. Degradation of synthetic-based drilling mud base 

fluids by Gulf of Mexico sediments: Final report. U.S. Dept. of the Interior, Minerals 

Management Service. Gulf of Mexico OCS Region, New Orleans, LA. OCS Study MMS 

2006-028. 122 pp. 

ABOUT THE COVER 

The cover art depicts a fluorescence photomicrograph of a culture of Desulfovibrio salexigens

visualized using fluorescence in situ hybridization (top left), a student performing fluorescence 

microscopy on sediment samples (top right), the pressure chamber designed and constructed to 

allow the incubation of sediment samples at high hydrostatic pressures (bottom left), and a 

fluorescence photomicrograph of Gulf of Mexico sediment stained with DAPI (bottom right). 

The photograph of the pressure chamber and student at the microscope were taken by Jeff Shaw, 

the Cullen College of Engineering photographer. 
v

ABSTRACT 

An important consideration in the environmental assessment of deep-sea drilling operations in 

the Gulf of Mexico is the discharge of cuttings coated with synthetic-based fluids (SBF). 

Synthetic-based fluids are one type of nonaqueous drilling fluid and are used in drilling mud to 

lubricate the drill bit, control reservoir pressure, and bring rock chips, or cuttings, to the surface. 

Synthetic-based fluids, which can be composed of linear alpha olefins, internal olefins, esters, or 

paraffins, are released into the marine environment as a residue on the cuttings as they are 

discharged. This study addressed the fate of the synthetic base fluid portion of the drilling mud 

in Gulf of Mexico sediments by determining the potential of marine sediment microbes to 

degrade representative SBF under deep-sea conditions. A model to predict how fast the 

sediment will recover under realistic conditions was developed to form a scientific basis for 

evaluating impacts from the discharge of SBF in the deep-sea. This study also examined the 

effect of the discharge on the microbial ecology of the sediments. 

Sediments collected from three locations in the Gulf of Mexico, 66 m to 1135 m depth, near field 

(NF) and far field (FF) locations (relative to drill sites) were used in a modified Closed Bottle 

Test (CBT) method to measure degradation rates of surrogate SBF tetradecene and ethyl oleate. 

The sediments were incubated at 4°C and under a hydrostatic pressure equal to that of the depth 

they were taken from, or at atmospheric pressure. The microbial population in the sediments 

was characterized by fluorescent in-situ hybridization (FISH) and most-probable number (MPN). 

A model that can be used to predict the fate of SBF deposited to the floor of the Gulf of Mexico 

was developed.

Analyses of the microbial ecology of the sediment were not as useful as had been hoped due to 

interference of natural sediment components with the methods used for analyses. The results did 

show an increase in the number of sulfate reducing bacteria (SRB) present in sediments that had 

been exposed to SBF (comparing impacted samples with unimpacted) or incubated in the 

presence of surrogate SBF tetradecene or ethyl oleate. 

The study showed that the CBT could be adapted to reflect deep-sea pressure and demonstrated 

the activities of cold tolerant, anaerobic microorganisms from the Gulf of Mexico sediments for 

degrading surrogate SBF components tetradecene and ethyl oleate. The results showed that the 

degradation of ethyl oleate and tetradecene by sediment organisms was not dependant on 

incubation pressure. Sulfate was determined to be the major electron acceptor involved in the 

degradation process in contaminated sediments. The anaerobic incubations revealed that the 

removal of ethyl oleate from a contaminated site could be described using a first order k value of 

-0.22 ± 0.02 week-1. The removal of ethyl oleate from an uncontaminated site would occur at a 

rate of -0.11 ± 0.02 week-1. A lag time for ethyl oleate removal is predicted to be between 0 and 

11 weeks. The average first order decay coefficient (k value) for the removal of tetradecene 

linked to sulfate reduction was -0.05 ± 0.01 week-1. Tetradecene degradation typically required a 

much longer lag period (4-28 weeks). 
vii

TABLE OF CONTENTS 

List of Figures............................................................................................................................... xi

List of Tables ................................................................................................................................xv

Chapter 1 Introduction..................................................................................................................1

Chapter 2 Literature Review ........................................................................................................3

2.1 Offshore Drilling..................................................................................................................3 

2.1.1 Drilling Mud..................................................................................................................3 

2.1.1.1 Drilling Mud Additives............................................................................................4 

2.1.2 Cuttings Discharge ........................................................................................................5 

2.2 Physical Processes Affecting the Fate of SBF in Sediments ...............................................6 

2.2.1 Molecular Diffusion ......................................................................................................6 

2.2.2 Advection and Compaction...........................................................................................7 

2.3 Biodegradation of SBF ........................................................................................................8 

2.3.1 Aerobic Hydrocarbon Degradation .............................................................................10 

2.3.2 Anaerobic Hydrocarbon Degradation .........................................................................11 

2.3.3 Modeling Microbial Activities ....................................................................................14 

2.3.4 Methods for Enumerating Microorganisms in Sediment ............................................15 

2.3.4.1 Growth-Based Techniques.....................................................................................16 

2.3.4.2 Molecular Based Techniques.................................................................................16 

Chapter 3 Methodology...............................................................................................................21

3.1 MPN Enumeration of Specific Nutritional Groups ...........................................................21 

3.1.1 Sample Preparation .....................................................................................................21

3.1.2 Media Preparation .......................................................................................................24 

3.1.3 Inoculation, Incubation, and Results Interpretation ....................................................25 

3.2 Enumeration Using Molecular Techniques .......................................................................25 

3.2.1 Cultures Used in Validation Activities........................................................................25 

3.2.2 Fixing the Pure Cultures..............................................................................................26 

3.2.3 Fixing the Sediments...................................................................................................26

3.2.4 Preparing the Sediment for FISH ................................................................................26 
viii

3.2.5 FISH Examination of the Sediment ............................................................................26 

3.3 Anaerobic Biodegradation Testing ....................................................................................28 

3.3.1 General Test Procedures..............................................................................................29 

3.3.2 First Pressure Vessel Experiment................................................................................30 

3.3.3 Other Anaerobic Incubations.......................................................................................30 

3.4 Aerobic Biodegradation Test .............................................................................................30 

3.5 Analytical Methods............................................................................................................31 

3.5.1 Methane Analysis........................................................................................................31 

3.5.2 Sulfate Analysis...........................................................................................................31 

3.5.3 SBF in Sediment..........................................................................................................31 

3.6 Statistical Analysis.............................................................................................................32 

Chapter 4 Initial Model Development........................................................................................33

4.1 SBF Removal.....................................................................................................................33 

4.1.1 Oxygen Consumption Zone. .......................................................................................33 

4.1.2 Sulfate Consumption Zone..........................................................................................34 

4.1.3 CO2 Consumption Zone ..............................................................................................34 

4.1.4 General Formula for All Zones ...................................................................................35 

4.2 Fate of Pore Water Species (Oxygen and Sulfate).............................................................36 

4.3 Solution for Equations .......................................................................................................37 

4.4 Spreadsheet Solution to the Model ....................................................................................39 

4.4.1 Layout..........................................................................................................................39 

4.4.2 Input Parameters..........................................................................................................39 

4.5 Boundary Conditions .........................................................................................................39 

4.6 Sensitivity Analysis ...........................................................................................................39 

4.6.1 Physical Properties ......................................................................................................41 

4.6.1.1 Porosity and Tortuosity of the Sediment ...............................................................41 

4.6.1.2 Oxygen Diffusion Coefficient................................................................................41 

4.6.1.3 Sulfate Diffusion Coefficient.................................................................................41 

4.6.1.4 Initial Concentration of Hexadecane .....................................................................45 

4.6.2 Biological Parameters .................................................................................................45 

4.6.2.1 Bioturbation Coefficient ........................................................................................45 
ix

4.6.2.2 Oxygen Consumption Zone ...................................................................................45 

4.6.2.3 Sulfate Consumption Zone ....................................................................................54 

4.6.2.4 CO2 Consumption Zone.........................................................................................59 

4.7 Conclusions from Initial Modeling....................................................................................59 

Chapter 5 Microecology Studies.................................................................................................65

5.1 Method Development.........................................................................................................65 

5.1.1 Separation of Cells and Sediment ...............................................................................65 

5.1.2 Most Probable Number (MPN) Technique .................................................................67 

5.1.3 Verification of Molecular Technique..........................................................................69 

5.1.3.1 Probe Combination Eub 338 and Clost I. ..............................................................69 

5.1.3.2 Probe Combination Eub 338 and SRB 385............................................................70 

5.1.3.3 Probe Combination Eub 338 and Arch 915. ..........................................................73 

5.2 Results from Sample Analysis...........................................................................................76 

5.2.1 Time Zero Samples .....................................................................................................77 

5.2.1.1 Results of FISH Analysis.......................................................................................77 

5.2.1.2 Results of MPN Analysis.......................................................................................77 

5.2.1.3 Discussion of the Effect of Oil Exploration Activities on Sediment 

Microbial Populations..........................................................................................78 

5.2.2 Time Final Samples.....................................................................................................80

5.2.2.1 FISH Analyses .......................................................................................................80 

5.2.2.2 MPN Analyses .......................................................................................................82 

5.2.2.3 Discussion of the Effect of Anaerobic Incubations with Surrogate SBF on 

Microbial Populations..........................................................................................82 

5.3 Conclusions from Microecology Studies...........................................................................84 

Chapter 6 Results of BioDegradation Studies...........................................................................87

6.1 Method Development.........................................................................................................87 

6.1.1 Pressure Chamber Development .................................................................................87 

6.2 Anaerobic Incubations .......................................................................................................88 

6.2.1 MP299 Site..................................................................................................................88 

6.2.2 GC112 Site ..................................................................................................................91 

6.2.3 VK916 Site..................................................................................................................94 
x

6.3 Interpretation of Anaerobic Incubation Data .....................................................................96 

6.3.1 Determination of the Decay Coefficient from Anaerobic Degradation ......................96 

6.4 Aerobic Biodegradation Results ........................................................................................99 

Chapter 7 Final Model Development .......................................................................................101

7.1 Overview of the Fate Model ............................................................................................101 

7.2 Numerical Solution for the Fate Model ...........................................................................103 

7.3 Explanation of Model Input.............................................................................................104 

7.3.1 Initial and Boundary Conditions ...............................................................................104 

7.3.1.1 Depth of the Saturated Layer ...............................................................................104 

7.3.1.2 Initial Concentration ............................................................................................105 

7.3.2 Diffusion and Decay Parameters...............................................................................106 

7.3.2.1 SBF Diffusion Coefficient ...................................................................................106 

7.3.2.2 Oxygen Diffusion Coefficient..............................................................................106 

7.3.2.3 Sulfate Diffusion Coefficient...............................................................................106 

7.3.2.4 Aerobic Decay Coefficient ..................................................................................106 

7.3.2.5 Anaerobic Decay Coefficient...............................................................................107 

7.3.2.6 NOUR Decay Coefficient....................................................................................107 

7.3.2.7 Stoichiometric Coefficient and Lag Time............................................................107 

7.3.2.8 Step Sizes.............................................................................................................107 

7.3.2.9 Porosity and Tortuosity of the Sediment .............................................................108 

7.4 Verification of Model Performance.................................................................................108 

7.4.1 Simulation of the Natural Oxygen Profile.................................................................108 

7.4.2 Simulation of Aerobic SBF Degradation ..................................................................110 

7.4.3 Simulation of Anaerobic Degradation.......................................................................110 

7.4.4 Simulation of Aerobic-Anaerobic Degradation with Diffusion of SO4 and O2 ........115 

Chapter 8 Conclusions...............................................................................................................117

Chapter 9 Literature Cited .......................................................................................................119
xi

LIST OF FIGURES 

Page 

Figure 2.1. The β-oxidation pathway. ..................................................................................9 

Figure 2.2. Monooxygenase pathway for activation of hydrocarbons...............................10 

Figure 2.3. Summary example of aerobic pathways for the degradation of aromatic 

compounds. ......................................................................................................11 

Figure 2.4. Incorporation of fumarate into saturated hydrocarbons during anaerobic 

degradation.......................................................................................................13 

Figure 3.1. Geographic locations of the offshore sediments collected. .............................22 

Figure 3.2. Pressure vessel .................................................................................................29 

Figure 4.1. Effect of porosity on O2, SO4, and hexadecane concentrations in the 

first 30 cm after two years. ..............................................................................42 

Figure 4.2. Effect of the oxygen diffusion coefficient on O2, SO4, and hexadecane 

concentrations in the first 30 cm after two years. ............................................43 

Figure 4.3. Effect of sulfate diffusion coefficient on O2, SO4, and hexadecane 

concentrations in the first 30 cm after two years. ............................................44 

Figure 4.4. Effect of the initial hexadecane concentration on O2, SO4, and 

hexadecane concentrations in the first 30 cm after two years. ........................46 

Figure 4.5. Effect of the bioturbation coefficient on O2, SO4, and hexadecane 

concentrations in the first 10 cm after two years. ............................................47 

Figure 4.6. Effect of the growth rate of aerobes on O2, SO4, and hexadecane 

concentrations in the first 10 cm after two years. ............................................48 

Figure 4.7. Effect of the initial concentration of aerobes on O2, SO4, and 

hexadecane concentrations in the first 10 cm after two years. ........................50 

Figure 4.8. Effect of the yield value for aerobic hexadecane degradation on O2, 

SO4, and hexadecane concentrations in the first 10 cm after two years...........51 

Figure 4.9. Effect of the half saturation constant for aerobes on O2, SO4, and 

hexadecane concentrations in the first 10 cm after two years. ........................52 

Figure 4.10. Effect of the oxygen limitation coefficient on O2, SO4, and hexadecane 

concentrations in the first 10 cm after two years. ............................................53 
xii

Figure 4.11. Effect of the growth rate of SRB on O2, SO4, and hexadecane 

concentrations in the first 30 cm after two years. ............................................55 

Figure 4.12. Effect of the number of SRB on O2, SO4, and hexadecane 

concentrations in the first 20 cm after two years. ............................................56 

Figure 4.13. Effect of the yield of SRB on O2, SO4, and hexadecane concentrations 

in the first 20 cm after two years. ....................................................................57 

Figure 4.14. Effect of the half saturation constant for SRB on O2, SO4, and 

hexadecane concentrations in the first 20 cm after two years. ........................58 

Figure 4.15. Effect of the sulfate limitation coefficient for SRB on O2, SO4, and 

hexadecane concentrations in the first 20 cm after two years. ........................60 

Figure 4.16. Effect of the oxygen inhibition coefficient for SRB on O2, SO4, and 

hexadecane concentrations in the first 20 cm after two years. ........................61 

Figure 4.17. Effect of the oxygen inhibition of methanogens on O2, SO4, and 

hexadecane concentrations in the first 20 cm after two years. ........................62 

Figure 4.18. Effect of the sulfate inhibition of methanogens on O2, SO4, and 

hexadecane concentrations in the first 20 cm after two years. ........................63 

Figure 5.1. Sediment viewed using the DAPI filter (100x oil objective)...........................65 

Figure 5.2. C. sordelli using Eub 338 and Clost I probes (40x objective).........................71 

Figure 5.3. S. aureus using Eub 338 and Clost I probes (100x objective).........................71 

Figure 5.4. D. multivorans using Eub 338 and SRB 385 probes (100x objective). ...........72 

Figure 5.5. C. sordelli using Eub 338 and SRB 385 probes (100x objective). ..................73 

Figure 5.6. M. mazei using Eub 338 and Arch 915 probes (100x objective).....................75 

Figure 5.7. C. sordelli using Eub 338 and Arch 915 probes (100x objective)..................75 

Figure 5.8. Microbial numbers in sediments at time zero..................................................79 

Figure 6.1. Effect of incubation vessel on concentration of surrogate SBF in sterile 

sediments..........................................................................................................87 

Figure 6.2. Sulfate removal in incubation vessel tests. ......................................................88 

Figure 6.3. Ethyl oleate and tetradecene concentrations in MP299 NF sediment 

incubated at 97 psi or atmospheric pressure. ...................................................89 
xiii

Figure 6.4. Tetradecene and sulfate concentrations in MP299 NF sediment 

incubated at 97 psi or atmospheric pressure. ...................................................90 

Figure 6.5. Concentrations of sulfate and ethyl oleate in MP299 NF sediment 

incubated at 97 psi or atmospheric pressure. ...................................................90 

Figure 6.6. Concentrations of sulfate, ethyl oleate, and tetradecene in MP299 FF 

sediment incubated at atmospheric pressure....................................................91 

Figure 6.7. Ethyl Oleate and tetradecene concentrations in GC112 NF sediment 

incubated at 790 psi or atmospheric pressure. .................................................92 

Figure 6.8. Tetradecene and sulfate concentrations in GC112 NF sediment 

incubated at 790 psi or atmospheric pressure. .................................................93 

Figure 6.9. Ethyl Oleate and sulfate concentrations in GC112 NF sediment 

incubated at 790 psi or atmospheric pressure. .................................................93 

Figure 6.10. Concentrations of sulfate, ethyl oleate, and tetradecene in GC112 FF 

sediment incubated at atmospheric pressure....................................................94 

Figure 6.11. Concentration of sulfate, ethyl oleate, and tetradecene in VK916 NF 

sediment microcosms incubated at 1700 psi....................................................95 

Figure 6.12. Concentrations of sulfate, ethyl oleate, and tetradecene in VK916 FF 

sediment microcosms incubated at 1700 psi....................................................96 

Figure 7.1. Model input table. ..........................................................................................105 

Figure 7.2. Oxygen profile with oxygen diffusion (D=0.955 cm2

/sec) with a) no 

reactive terms and b) with NOUR (0.3 wk-1).................................................109 

Figure 7.3. SBF profile when a) only aerobic decay (k=0.15) is active and b) when 

oxygen diffusion is added using a diffusion coefficient of 0.955..................111 

Figure 7.4. Oxygen profile when a) only aerobic decay (k=0.15) is active and b) 

when oxygen diffusion is added using a diffusion coefficient of 0.955. .......112 

Figure 7.5. SBF profile with anaerobic decay of SBF occurs with a) no sulfate 

diffusion, and b) sulfate diffusion using a coefficient of 0.522.....................113 

Figure 7.6. Sulfate profile with a) anaerobic decay (k=0.12) only and b) anaerobic 

decay plus sulfate diffusion (D=0.522)..........................................................114 

Figure 7.7. Predicted SBF profile with all model parameters set.....................................115 

Figure 7.8. Predicted oxygen profile with all model parameters set................................116 
xiv

Figure 7.9. Predicted sulfate profile with all model parameters set.................................116 
xv

LIST OF TABLES 

Page 

Table 2.1 EPA NPDES Allowances for SBF Adherent on Cuttings to be 

Discharged Overboard .......................................................................................5 

Table 2.2 Measured or Estimated Log Octanol/Water Partition Coefficients of 

Several SBF .......................................................................................................6 

Table 2.3 Calculated* and Experimental Yields for Organisms Grown on 

Hexadecane......................................................................................................14 

Table 2.4 Molecular Probes for Microbial Enumeration .................................................18 

Table 3.1 Sediment Samples Received for Study............................................................23 

Table 3.2 Chemical Properties of Selected Sediments ....................................................24 

Table 3.3 Expected Fluorescence of Molecular Probes...................................................28 

Table 4.1 Parameter Values Used in Initial Modeling.....................................................40 

Table 5.1 Quantitative Analysis of Cell Counts in Separation Layers ............................67 

Table 5.2 DAPI Counts on Separated Cells and Supernatants ........................................67 

Table 5.3 Method Validation for MPN Media.................................................................68 

Table 5.4 Probe Combination Eub 338 and Clost I Validation (TH = 53.5oC) ..............70 

Table 5.5 Matrix Obtained for Probe Combination Eub 338 and SRB 385 (TH = 

53.5oC).............................................................................................................72 

Table 5.6 M atrix Obtained for Probe Combination Eub 338 and Arch 915 (TH = 

53.5oC).............................................................................................................74 

Table 5.7 Probe Combination of Clost Ι and Eub 338.....................................................76 

Table 5.8 Probe Combination of SRB 385 and Eub 338 .................................................76 

Table 5.9 Results of FISH Analysis on Time Zero Sediments (cells/g dry 

sediment)..........................................................................................................77 

Table 5.10 Results of Time Zero MPN Enumerations.......................................................78 

Table 5.11 Comparison of Microbial Numbers in NF and FF Sediment (Time =0) .........80 
xvi

Table 5.12 Results of FISH Analysis of MP299 FF Time Final Sediments......................81 

Table 5.13 Results of FISH Analysis of GC112 FF Time Final Sediments ......................82 

Table 5.14 Eesults Time Final MPN Enumerations ..........................................................83 

Table 5.15 Statistical Comparison of Time Final FF MPN Results for SRB ....................83 

Table 5.16 Statistical Comparison of Time Final FF MPN Results for General 

Anaerobes ........................................................................................................84 

Table 5.17 Method Development Summation ...................................................................85 

Table 6.1 Kinetic Data for Ethyl Oleate Degradation......................................................98 

Table 6.2 Kinetic Data for Tetradecene Degradation ......................................................99 

Table 7.1 Stoichiometric Coefficients for Sulfate Usage (g SO4/g substrate) ..............102 

Table 7.2 Input Parameters Used for Full Model Run...................................................115 
xvii

LIST OF ABREVIATIONS AND SYMBOLS 

Abbreviations 

AO acridine orange 

AODC acridine orange direct counts 

API American Petroleum Institute 

ARCH915 oligonucleotide probe for Archaebacteria 

ATCC American type culture collection 

BAA broad agency announcement 

CBT closed bottle test 

CLOST I oligonucleotide probe for Clostridia 

Co-A coenzyme A 

DAPI 4’-6-diamino-2-phenylindole 

DNA deoxyribonucleic acid 

DOE U.S. Department of Energy 

EDTA ethylenediaminetetraacetic acid 

EB963 Ewing Bank Block 963 

EI346 Eugene Island Block 346 

EPA U.S. Environmental Protection Agency 

Eub 338 oligonucleotide probe for eubacteria 

EMOBF enhanced mineral oil based fluids 

FISH fluorescence in situ hybridization 

FITC fluorescein isothiocyanate fluorochrome 

FF far field (relative to drill site location) 

GA general anaerobes 

GC112 Green Canyon Block 112 

GC-FID gas chromatography with flame ionization detector 

GC-MS gas chromatography with mass spectrometry 

GOM Gulf of Mexico 

HP Hewlett Packard 

ID inner diameter 

IO internal olefin 

LA lag time adjusted 

LHS left hand side of an equation 

LAO linear alpha olefin 

MC496 Mississippi Canyon Block 496 

MMS Minerals Management Service 

MPN most probable number 

MP 288 Main Pass Block 288 

MP299 Main Pass Block 299 

na analysis not applicable 

NABF nonaqueous base fluid 

NADF nonaqueous-based drilling fluid 

NF near field (relative to drill site location) 

NL not linked 
xviii

NOUR natural oxygen uptake rate 

NPDES nonpoint discharge elimination system 

OBF oil-based fluid 

OCS Outer Continental Shelf 

OS original supernatant 

PAH polycyclic aromatic hydrocarbons 

PBS phosphate buffered saline 

PCR polymerase chain reaction 

pH negative log of the hydrogen ion concentration 

RHS right hand side of an equation 

RNA ribonucleic acid 

rRNA ribosomal ribonucleic acid 

RPD redox potential discontinuity 

SBF synthetic base fluids 

SBM drilling mud made using synthetic base fluids 

SC stoichiometric coefficient 

SD standard deviation 

SRB sulfate reducing bacteria 

SRB 385 oligonucleotide probe for sulfate reducing bacteria 

TH hybridization temperature 

TGY tryptone, glucose yeast extract (microbial medium) 

TRITC Texas red fluorochrome 

UH University of Houston 

U.S. United States 

UV Ultraviolet 

VBA visual basic computer language 

VK916 Viosca Knoll Block 916 

WBF water-based fluid 

Symbols 

∆x depth increment (cm) 

∆t time increment (week, month) 

ε porosity 

ρs density of sediment (kg/L) 

θ turtuosity (1/ε) 

a ion specific diffusion coefficient (cm2 

s

-1 °C-1) 

C general term for concentration of substrate in sediment or water (mg/kg or 

mg/L) 

coeffdb coefficient of exponential bioturbation decrease 

D general molecular diffusion coefficient 

DO general molecular diffusion coefficient at 0 degrees 

DT general molecular diffusion coefficient at temperature T 

DE general effective diffusion coefficient 

D`O diffusion coefficient of O2 in sea water (cm2

/d) 

D`SO4 diffusion coefficient of SO4 in sea water (cm2

/d) 
xix

DO diffusion coefficient of O2 in sediment pore water (cm2

/d) 

DSO4 diffusion coefficient of SO4 in sediment pore water (cm2/d) 

Db0 bioturbation coefficient in bioburbated layer (cm2/d) 

F SBF or surrogate compounds concentration (mg/kg dry sediment) 

k general first order decay coefficient (time-1) 

k F,O2 first order decay coefficient of SBF in aerobic condition (time –1) 

k F,SO4 first order decay coefficient of SBF in anaerobic condition (time –1) 

Kow octanol water partition coefficient (dimensionless concentration unit ratio) 

Ks general half saturation constant (mg/kg or mg/L) 

Ks,1 half-saturation concentration of F for aerobic degradation (mg/kg) 

Ks,2 half-saturation concentration of F for anoxic (SO4) deg. (mg/kg) 

Ks,3 half-saturation concentration of F for anoxic (CO2) deg. (mg/kg) 

Ks,o O2 limitation for oxygen consumption (mg/L) 

KS,SO4 SO4 limitation for sulfate utilization (mg/L) 

K`O,SO4 O2 inhibition of SO4 reduction (mg/L) 

K`O,CO2 O2 inhibition of methanogenesis (mg/L) 

K`SO4,CO2 SO4 inhibition of methanogenesis (mg/L) 

O oxygen concentration (mg/L or mM pore water) 

r

2

 linear correlation coefficient 

rF,O rate of base fluid degradation in the oxygen utilizing layer 

rF,SO4 rate of base fluid degradation in the sulfate utilizing layer 

rF,CO2 rate of base fluid degradation in the methanogenic layer 

rS rate of substrate utilization 

S sulfate concentration (mg/L or Mm pore water) 

SC stoichiometric coefficient 

T temperature (°C typically) 

TH hybridization temperature 

t time (week, month, year) 

μ general term for maximum specific cell growth rate 

μ1 maximum specific growth rate (O2) (d-1) 

μ2 maximum specific growth rate (SO4) (d-1) 

μ3 maximum specific growth rate (CO2) (d-1) 

xb thickness of constant bioturbation layer 

X general term for cell concentration 

X1,O initial aerobic cell concentration (mg/kg) (extra subscripts I, F indicate initial 

and final concentrations) 

X2,O initial anaerobic (SO4) cell concentration (mg/kg) (extra subscripts I, F indicate 

initial and final concentrations) 

X3,O initial anaerobic (CO2) cell concentration (mg/kg) (extra subscripts I, F indicate 

initial and final concentrations) 

X1,F final aerobic cell concentration (mg/kg) (extra subscripts I, F indicate initial 

and final concentrations) 

X2,F final anaerobic (SO4) cell concentration (mg/kg) (extra subscripts I, F indicate 

initial and final concentrations) 
xx

X3,F final anaerobic (CO2) cell concentration (mg/kg) (extra subscripts I, F indicate 

initial and final concentrations. 

Y general term for microorganism yield (g cells/g substrate) 

Y1 yield (g aerobic cells/g hexadecane) 

Y2 yield (g SRB/g hexadecane) 

Y3 yield (g methanogens/g hexadecane) 

Z depth 
1 

CHAPTER 1 INTRODUCTION 

Synthetic base fluids (SBF) are one component of the drilling mud system referred to as 

synthetic-based mud (SBM) that are important in difficult deep water drilling operations. SBF 

combine the technical advantages of oil-based fluids and the low toxicity of water-based fluids. 

When drilling mud and the cuttings it carries reach the surface they are passed through 

separation processes, the drilling mud is pumped back to the mud tank and used for the next 

drilling processes, and the cuttings that have SBF adherent to them are disposed of. The most 

economical disposal method is direct ocean discharge. The cuttings and adherent SBF settle to 

the sea floor. The concentration of SBF in the sea floor environment may decrease with time due 

to resuspension, bed transport, bioturbation, and biodegradation. Biodegradation is expected to 

be the most significant mechanism of SBF attenuation and thus environmental recovery. 

Biodegradation of SBF is the use of the organic compounds as carbon and energy sources, and is 

expected to occur with different electron acceptors. Oxygen is the most energetically favorable 

electron acceptor, but in the floor of the Gulf the average oxygen concentration is 6.8 mg/L (0.21 

mM) and the oxygen only naturally diffuses a few centimeters into the sediment. The deposition 

of SBF contaminated cuttings will cause the sediment to become anoxic and sulfate will then be 

used as the electron acceptor. The average sulfate concentration in the sea bottom is 2.77 g/L 

(28.9 mM) and the sulfate concentration in the sediment pore water will be almost the same as 

this concentration in first 30 cm. If the sulfate in the sediment is depleted, methanogens will 

then use carbon dioxide in the sediment and produce methane with the biodegradation of SBF. 

When the concentration of SBF in sediments is reduced to very low levels the oxygen and sulfate 

concentration will increase due to diffusion from the overlying water body and complete 

recovery of the sediment from the cuttings disposition will be possible. The key to predicting 

sediment recovery will be the kinetics of the biodegradation of the SBF. 

The objective of this research is to model the fate of the synthetic base drilling fluids in the Gulf 

of Mexico. This will be accomplished by: 

• developing a conceptual model; 

• conducting a sensitivity analyses to determine which modeling parameters have 

the most important effect on the fate of SBF in Gulf of Mexico sediments; 

• performing experiments to determine the specific values of the parameters 

deemed important; and 

• using the experimentally determined kinetic data to finalize a mathematical model 

to predict the fate of SBF in deep Gulf sediments. 
3 

CHAPTER 2 LITERATURE REVIEW 

2.1 OFFSHORE DRILLING

The main functions of drilling muds are to balance pressures preventing a blowout; to cool, 

lubricate, and support part of the weight of the bit and pipes; and to transport cuttings to the 

surface (Neff 1987, Darley and Gray 1988). During drilling, the drilling mud is pumped from 

the mud tanks down the hollow drill pipe and through nozzles in the drill bit. The flowing mud 

sweeps cuttings from beneath the bit and carries them back up the annular space between the 

drill pipe and the borehole or casing to the surface. The mud is then passed through solids 

control equipment to remove the drilling mud from the cuttings. The mud is then circulated back 

to the mud tanks where the cycle is repeated (Neff et al. 2000). 

2.1.1 Drilling Mud 

Drilling muds are composed of a base fluid to which various compounds such as barite (BaSO4), 

clay, caustic soda, lignite, lignosulfonates, and/or polymeric materials are added. There are two 

general types of base fluids used in drilling mud: water and nonaqueous base fluids. Fresh or salt 

water is used as the continuous phase in water-based drilling fluids (WBF) and are used during 

shallow drilling operations and to drill the shallow phase of deeper wells. All muds may also 

contain low concentrations of specialty chemicals added to solve some particular problem that is 

affecting mud properties. 

The continuous phase of nonaqueous-based drilling fluids (NADF) is a liquid hydrocarbon 

mixture or other insoluble organic chemical termed nonaqueous base fluid (NABF). NABF are 

more expensive than WBF but are used in difficult drilling situations where their technical 

advantages are required. There are three types of NADF, based on the chemical composition of 

the base fluid in the mud. These are oil-based fluids (OBF), enhanced mineral oil-based fluids 

(EMOBF), and synthetic based muds (SBM). The term SBM is used here to represent the whole 

drilling fluid or mud, and the base fluid portion is represented by the term SBF. 

The OBF contain diesel fuel or conventional mineral oil as the continuous phase. They are the 

least expensive and were the only ones in use until the late 1980s (Dicks et al. 1986/87). 

EMOBF contain an enhanced mineral oil as the continuous phase. Enhanced mineral oils are 

conventional paraffinic mineral oils that have been or purified to remove all aromatic 

hydrocarbons. Although EMOBF are less toxic than OBF, the EPA does not permit the 

discharge of EMOBF coated cuttings to U.S. territorial waters. 

The base fluid or continuous phase of an SBM is a water insoluble synthetic organic material. 

The EPA defines SBM as being different from other NADF because the SBF continuous phase is 

produced from a chemically defined feed stock. Since they are synthesized by the reaction of 

purified compounds, they should be free of polycyclic aromatic hydrocarbons (PAH) (U.S. EPA 

1996). Thus SBF are designed to be less toxic and degrade faster than OBF, and they yield mud 

systems similar to OBF in drilling performance (Friedheim and Conn 1996). With the use of 

SBF the drilling times were reduced by 50 to 60 percent, and well costs were generally cut in 
4 

half for the SBF wells. Burke and Veil (1995) also point out that when SBF are used instead of 

WBF, the total quantity of waste discharged is greatly reduced. SBF provide good carrying 

capacity for cuttings, improving cuttings transport in long, cold, deep-water risers. Because of 

their low toxicity and persistence, SBF are thought to have environmental impacts intermediate 

between those of WBF and OBF. Linear alpha olefins (LAO) and internal olefins (IO) are very 

common synthetic base fluids used in drilling muds in the Gulf of Mexico. 

The SBF can be classified into four categories: synthetic hydrocarbons, ethers, esters, and 

acetals. The synthetic hydrocarbons are typically polymerized olefins and linear paraffins. They 

are often used in blends that are designed to achieve balance among the physical properties 

important to the drilling operation (e.g. viscosity, pour point, flash point, etc). Ethers are only 

poorly degraded and acetals are not very stable so they have never been used in U.S. waters 

(Friedheim and Conn 1996). Esters and olefins are most commonly used in today’s market due 

to their low toxicity, relatively rapid biodegradation rate, low environmental impacts, and cost. 

Olefins are less costly than esters, more stable at higher temperatures, less viscous at low 

temperature, and more adaptable to deep water drilling environments. However, esters are much 

more biodegradable than olefins (Neff et al. 2000). 

2.1.1.1 Drilling Mud Additives 

The types and amounts of chemical additives included in the mud formulation vary according to 

the required characteristics of the mud. The functions and types of the major chemical additives 

used in different drilling muds are summarized as follows. 

• Weighting materials are added to increase the weight of the mud, so that adequate 

well control can be maintained. The weighting agent is normally a major 

component of the mud system. The most common weighting material is barite 

(BaSO4). 

• Viscosifiers promote viscosity through complex interactions with the emulsions. 

Bentonite clay is often used with most mud types. 

• Fluid loss control agents are compounds added to reduce the loss of fluid from the 

mud into the drilled formation. Types of agents include bentonite clay, lignite, 

and polymers (e.g. carboxymethylcellulose, polyanioniccellulose, and modified 

starch). 

• Emulsifiers are added to stabilize oil-in-water emulsions. A combination of two 

emulsifiers is often used to ensure a homogenous composition. Types of primary 

emulsifiers include fatty acids (and derivatives) and rosin acid (and derivatives). 

Types of secondary emulsifiers include amines, amides, sulfonic acids, 

lignosulfonates, alcohols, and related co-polymers. These are used to improve 

emulsion stability, especially at high temperatures, and to wet the drilled solids 

• Brines are used 1) to balance the interactions of drilling fluid with clay and 

soluble salts in the formation, 2) because they are denser than the oil/synthetic oil 
5 

phase, thereby increasing the weight considerably, and 3) because the emulsion 

formed has a higher viscosity than either of the two phases alone. 

• Alkaline chemicals are normally added to control the pH, which is beneficial to 

reduce corrosion and to activate some emulsifiers. Lime (Ca(OH)2) is normally 

used with drilling muds made with SBF. 

• Lost circulation materials are added to block pores, voids, or fractures (all mud 

types). Many types of materials are used, for example crushed nut shells, 

shredded vegetable fiber, mica flakes, graded sizes of calcium carbonate, 

shredded cellulose, and diatomaceous earth. 

2.1.2 Cuttings Discharge 

Drill cuttings are particles of crushed rock and range in size from clay-sized particles to coarse 

gravel. When SBM are used the EPA restricts the amount of base fluid remaining adherent to 

discharged cuttings. Prior to the implementation of current regulations, cuttings discharged 

offshore contained an average of 12 percent SBF. Current discharges are now in compliance 

with the limits in Table 2.1. 

Table 2.1 

EPA NPDES Allowances for SBF Adherent on Cuttings to be Discharged Overboard 

Standard of Adherence Level 

C16-C18 Internal Olefins <6.9 g SBF/100 g discharged cuttings 

C12-C14 Ester <9.4 g SBF/100 g discharged cuttings 

C8 Ester <9.4 g SBF/100 g discharged cuttings 

Discharged directly at sea floor 14 - 15%* 

 *Percentage of the base fluids retained on the cuttings. Source: Federal Register 2004. 

When NADF are discharged to the ocean, they tend to clump together in large particles that 

settle rapidly to the sea floor (Delvigne 1996, Brandsma 1996). Ester based SBF cuttings are 

more easily dispersed than olefinic SBF cuttings. Water cannot easily penetrate the oleophyllic 

mass of cuttings, so they do not disperse efficiently (Neff et al. 2000). Therefore, most SBF 

cuttings settle rapidly and accumulate at the bottom near the platform discharge sites. 

Gallaway et al. (1998) monitored SBF cuttings distribution in 565 m of water south of the 

Mississippi River in the northern Gulf of Mexico. Total cutting discharges from the rig included 

7700 bbls of WBF cuttings, 5150 bbls of SBF cuttings, and an estimated 7695 bbls of Petrofree 

LE (a SBF base material containing 90 percent LAO and 10 percent ester). Maximum cuttings 

accumulations were observed to be 20 to 25 cm thick and maximum LAO concentration was 

198,000 mg/kg in surficial sediment. The mean concentration of LAO in surficial sediments (all 

sampling stations combined) was 4,000 mg/kg in 1997 and 2,000 mg/kg in 1998. Gallaway`s 
6 

monitoring showed that SBF cuttings were distributed very heterogeneously in surface and 

subsurface sediment. 

2.2 PHYSICAL PROCESSES AFFECTING THE FATE OF SBF IN SEDIMENTS

The concentration of SBF on the sea floor after deposition can be affected by various physical 

properties. The diffusion of SBF from the cuttings and sediment and the resuspension of 

sediments containing cuttings affect the SBF directly. Other properties, such as the diffusion of 

electron acceptors such as oxygen and sulfate effect the concentrations of SBF indirectly due to 

the stimulation (or lack of it) of the microbial population responsible for SBF metabolism. 

2.2.1 Molecular Diffusion 

SBF base chemicals are hydrophobic compounds with low solubility and they do not 

significantly disperse in the water column following discharge. Table 2.2 shows measured or 

estimated values for log octanol/water partition coefficient (log Kow) of several SBF base 

chemicals. There is an inverse relationship between log Kow and aqueous solubility. The esters 

would represent the most soluble of the SBF. 

Since the SBF are so poorly soluble, the diffusion of the SBF off of the sediment or into the 

overlaying water body is minimal and can be ignored when predicting the fate of SBF in 

sediments. 

Table 2.2 

Measured or Estimated Log Octanol/Water Partition Coefficients of Several SBF 

SBF Base Chemicals Log Kow Reference 

Ester 1.69 Growcock et al. 1994 

Acetal 11.8 Vik et al. 1996a 

Linear-α-Olefin >6.43 McKee et al. 1995 

Internal Olefin 8.57 Zevallos et al. 1996, 

Poly-α-Olefin 11.2-13.7 

15.4 

11.2 

Vik et al. 1996a 

Friedheim et al. 1996 

Zevallos et al. 1996 

 Neff et al. 2000 

The diffusion of oxygen and sulfate is important because they are used as electron acceptors 

during biodegradation of SBF in sediment. The free solution diffusion coefficient (DT) (units of 

cm2 s-1) for sulfate at the ambient temperature T (°C) is calculated from the zero-degree 

coefficient D0. 

DT

 = D0 + at Equation 2.1
7 

where a = an ion specific coefficient. For sulfate D0

 is 4.88 x 10-6 cm

2

 s

-1 and a is 0.232 x 10-6

cm

2

 s

-1 °C-1 (Li and Gregory 1974). The ambient temperature of Gulf sediments is 5 °C. 

Therefore, 

DT = 4.88 x 10-6 + 0.232 x 10-6 *5 = 6.04 x 10-6 cm

2

 s

-1 (0.522 cm2

 d-1) Equation 2.2

The following formula is used to calculate DT for oxygen (Boudreau 1997) 

DT

 = (0.2604 + 0.006383 * (t / μ*0.01)) * 10-5 Equation 2.3

where T is the absolute temperature (°K) and μ is the dynamic viscosity in units of poise (g cm-1

s

-1). 

In the sediment pore water, because of the convoluted path molecules must follow to circumvent 

the sediment particles, the effective diffusion coefficient of a dissolved substance in the sediment 

(DE) is lower than its free-solution diffusion coefficient in seawater (DT

). DE is related to DT by: 

DE = DT

 / θ2 (Berner 1980) Equation 2.4

where θ is the turtuosity of the sediment. The turtuosity is related to sediment porosity (Ullman 

and Aller 1982). The effective diffusion coefficient of a dissolved substance in the sediment is 

then calculated as: 

DE = DT

 * ε

2 Equation 2.5

where ε is the porosity of the sediment. 

2.2.2 Advection and Compaction 

Advection is the process of material transport due to deposition of new material at the sediment 

surface or to the mixing of the sediment through currents or geochemical forces (Berner 1980). 

Advection of sediment due to currents or other physical mixing forces is highly unpredictable. 

These actions would cause reaeration and dispersion of the cuttings over a larger area, which 

would increase the degradation rate of the SBF and thus the recovery rate of the sediment. 

Ignoring this type of mixing results in a worst case scenario for prediction of sediment recovery. 

Bioturbation, the process of sediment mixing by the activity of organisms, is commonly modeled 

with Boudreau’s random diffusion-like process. It is assumed that bioturbation is constant in the 

upper few cm and that it decreases exponentially with sediment depth. Equation 2.6 and 

Equation 2.7 can be used to calculate bioturbation. 

If z ≤ zb Dbz = Dbo, Equation 2.6

If z > zb Dbz = Dbo * e-(z-zb)/coeffDb Equation 2.7
8 

where Dbz the rate of bioturbation at depth z (cm2

 d-1) and coeffDb is the coefficient for 

exponential bioturbation decrease. 

Deposition of new material to the sediment will also cause compaction. It can be assumed that 

the recovery process is started after deposition and sedimentation are completed and that the 

natural deposition rate is very slow. Therefore, the effects of neglecting the advection and 

compaction to the outcome of any fate model would be minimal. In summary, assuming 

constant porosity, no sedimentation, and no compaction, Equation 2.8 can be used to describe the 

SBF mass balance: 

 + ∑ 













∂

∂ = +

∂

∂ Reactions 2

2

) 2 (

z

C D b

o D

t

C

θ

Equation 2.8

The left hand side (LHS) is the change of concentration of the compounds (base chemical, 

sulfate, or oxygen) with time. The right hand side (RHS) of the equation accounts for diffusion, 

bioturbation, and biodegradation. 

2.3 BIODEGRADATION OF SBF 

Biodegradation is the breakdown of an organic substance, by the action of living organisms 

(especially bacteria) and is a key factor in reducing the long-term environmental impacts of SBF. 

The SBF are used as carbon and energy sources for microorganisms. The presence of an 

electron acceptor is required for complete biodegradation to occur. When oxygen is present 

(aerobic conditions) it will be used as the electron acceptor. When oxygen is absent (anaerobic 

conditions), the major electron acceptors are nitrate, Fe (III), sulfate, or carbon dioxide. The 

order of preference would depend mainly on the available concentrations of the compounds in 

the environment but if all were present, the electron acceptors would be used in the order listed. 

For biodegradation to occur, several basic conditions must be satisfied (Alexander 1994). The 

most important of these are: 

• the presence of organisms with the necessary enzymes to perform the reactions; 

• the chemicals must be accessible to the organisms; 

• the conditions in the environment must be favorable to the growth of the 

microorganisms (i.e. temperature, pH, salinity, and the presence of other essential 

nutrients). 

There are many reasons why some chemicals are degraded rapidly and others are not. The 

structure and concentration of the chemical are both crucial. For some compounds, low 

concentrations may result in low biodegradation rates, and there is commonly a threshold 

concentration, below which biodegradation does not occur (Alexander 1994). Higher 

concentrations of the organic compounds may result in increased degradation, because the 

increased availability of carbon and energy sources may support a larger microbial population. 
9 

Alternatively, high concentrations of the organic compound may have toxic effects that reduce 

degradation rates (Cornelissen and Sijm 1996). 

The presence of other compounds may also influence biodegradation. The presence of other 

more easily degradable organic compounds will result in a higher total microbial activity and 

thus may increase degradation rates of specific compounds. Alternatively, biodegradation of 

slowly degradable compounds could cease completely due to the availability of more 

preferentially degraded compounds (Cripps et al. 1999). In seawater, the reaction that yields the 

most energy is the aerobic oxidation of organic matter to CO2. Whenever oxygen is present, 

aerobic oxidation will be dominant. When oxygen is consumed or limited, sulfate reduction is 

expected to dominate because of the high content of sulfate in seawater. 

Another rule of thumb when estimating the biodegradability of organic compounds is that a 

compound that is structurally similar to a natural compound will more readily degrade than 

compounds that have completely foreign structures. When considering SBF compounds, the 

esters can be predicted to be the easiest to degrade since all organisms have ester bonds in the 

membranes and most organisms are capable of degrading membrane esters. 

Biodegradation of ester compounds begins with hydrolysis of the ester to its component acid and 

alcohol. The esterase enzymes necessary to hydrolyze an ester bond are very common and can 

be found in most environmental samples. The fatty acid is then degraded via the β-oxidation 

pathway (Figure 2.1) where the molecule is degraded two carbons at a time through a series of 

oxidation then reduction reactions. Most organisms are capable of performing β-oxidation since 

it is the pathway used to degrade cellular fatty acids. The alcohol can be degraded by a number 

of mechanisms depending on the alcohol, in most cases being transformed to one of the central 

metabolic pathway intermediates such as acetate, pyruvate, fumarate, or succinate. 

+

C

CH2

CH2

CH2

CH2

CH2

H C3

O

C O-CoA

CH2

CH2

CH2

CH2

CH2

H3C

O

O

C

H3C

O

CoA

C

CH

CH

CH2

CH2

CH2

H C3

O

O-CoA

CH2

CH2

CH2

CH2

H3C

CoA O

C

CH2

CH

CH2

CH2

CH2

H3C

O

O-CoA

HO

C

CH2

C

CH2

CH2

CH2

H3C

O

O-CoA

O

Figure 2.1. The β-oxidation pathway. 
10 

2.3.1 Aerobic Hydrocarbon Degradation 

Aerobic degradation of hydrocarbons has been commonly accepted as the major mechanism of 

removal of hydrocarbons from many contaminated environments. Aerobic organisms like 

Pseudomonas (Tagger et al. 1990), Flavobacterium (Okpokwasili et al. 1984), Moraxella

(Tagger et al. 1990), Marinobacter (Gauthier et al. 1992), and Vibrio (West et al. 1984) were 

found to degrade PAH under aerobic marine conditions. Pseudomonas testosterone, P. putida, 

and P. stutzeri biovars were isolated from Spanish Mediterranean sediments and were found to 

be capable of degrading naphthalene by Garcia-Valdes et al. (1988). Cycloclasticus was isolated 

from Puget Sound sediments (Dyksterhouse et al. 1995, Geiselbrecht et al. 1996) and from Gulf 

of Mexico sediments (Geiselbrecht et al. 1998). Shen et al. (1998) found that the genus 

Pseudomonas was the most prevalent among the aerobes degrading hydrocarbons. These 

organisms listed above are all classed as Eubacteria. 

The biodegradation pathways of aromatic and saturated hydrocarbons have been reasonably well 

studied. Studies to determine the aerobic pathways for the degradation of both saturated and 

aromatic compounds have shown that monooxygenase or dioxygenase enzymes are required for 

initial activation of the hydrocarbon chain. Oxygenase enzymes incorporate one or both of the 

atoms of molecular oxygen into the hydrocarbon, ultimately forming an alcohol (or catechol for 

aromatic compounds). The saturated hydrocarbon alcohol is oxidized again to form a carboxylic 

acid (Figure 2.2), making a fatty acid which is then degraded by the cell using β-oxidation 

(Figure 2.1). The catechol formed during the degradation of an aromatic compound is then 

cleaved to form a dicarboxylic acid (Figure 2.3), which is then further degraded via β-oxidation 

(Figure 2.1). 

CH3

CH2

CH2

CH2

CH2

CH2

H3C CH2

CH2

CH2

CH2

CH2

CH2

H C3

HO

O2 H2O

NADH NAD

CH

CH2

CH2

CH2

CH2

CH2

H C3

O

NAD

NADH

C

CH2

CH2

CH2

CH2

CH2

H3C

O

O

β oxidation

C

H3C

O

CoA

+

CH2

CH2

CH2

CH2

H3C

CoA O

monooxygenase

dehydrogenase

oxidase

Figure 2.2. Monooxygenase pathway for activation of hydrocarbons. 
11 

Although there is limited information in the literature concerning the degradation of alkenes, it is 

proposed by Britton (1984) that the metabolism of alkenes may be initiated using four major 

routes: 

• oxygenase attack upon a terminal methyl group to the corresponding alcohols and 

acids; 

• subterminal oxygenase attack to the corresponding alcohols and acids; 

• oxidation across the double bond to the corresponding epoxide; 

• oxidation across the double bond to the corresponding diol. 

All of the products formed are further metabolized by means of the β-oxidation pathway 

producing intermediates of the central metabolic pathway such as acetate. 

O2

Dioxygenase

meta cleavage ortho cleavage

Central Metabolic Pathway Intermediates

OH

OH

O

O

OH

OH

meta cleavage

ortho cleavage

OH

OH

O

O

HO

Figure 2.3. Summary example of aerobic pathways for 

the degradation of aromatic compounds. 

2.3.2 Anaerobic Hydrocarbon Degradation 

Only recently has reliable evidence demonstrating the degradation of aromatic hydrocarbons in 

anoxic environments been presented. The anaerobic degradation of alkanes is a rapidly 

developing field but the anaerobic degradation of alkenes is not very well studied. 
12 

The research concerning the anaerobic degradation of alkanes documents the removal of alkanes, 

linked to various anaerobic electron acceptors. The results suggest this is a very slow process. 

The information on types and numbers of organisms involved and the pathways that they use is 

limited. Aeckersberg et al. (1991; 1998) and Caldwell et al. (1998) found that sulfate-reducing 

bacteria (SRB) could metabolize straight chain saturated hydrocarbons. So et al. (1999a) 

reported the isolation and characterization of a novel sulfate-reducing bacterium (SRB) capable 

of degrading alkanes. Meckenstock et al. (2000) reported on a sulfate-reducing naphthalenedegrading freshwater culture enriched from a contaminated aquifer. So et al. (2001) enriched 

anaerobic alkane degrading microorganisms under four different reducing conditions (sulfatereducing, denitrifying, iron-reducing, and methanogenic) using estuarine sediment. They found 

that sulfate was the major electron acceptor in the estuarine environment. Koizumi et al. (2002) 

established a toluene-degrading consortium and an ethylbenzene-degrading consortium under 

sulfate-reducing conditions. Kleikemper et al. (2002) studied the activity and diversity of SRB 

in petroleum hydrocarbon contaminated aquifers and showed that SRB from the environment 

were able to use a variety of organic carbon sources. 

The major obstacle for the anaerobic biodegradation of hydrocarbons is the initial oxidation step. 

So and Young (1999b) proposed the subterminal oxidation of the hydrocarbon by an unknown 

mechanism, which was not a direct carboxylation. Studies that are more recent have shown that 

at least one mechanism for the anaerobic bacterial metabolism of alkanes is initiated by a 

fumarate addition reaction at the subterminal methyl group of the alkane (Kropp et al. 2000, 

Geig and Sulfita 2002) (Figure 2.4). Fumarate is an unsaturated 4-carbon dicarboxylic acid and 

a component of well established pathways for the oxidation of sugars. The addition of fumarate 

to a hydrocarbon results in the formation of a succinate derivative that has been identified using 

gas chromatograph-mass spectrometry (GC-MS) analysis (Geig and Sulfita 2002). The addition 

of an organic acid as an initial step in the oxidation of saturated hydrocarbons may represent a 

common theme for the anaerobic degradation of a broad range of hydrocarbon contaminants. 

The anaerobic pathway for the biodegradation of olefins (unsaturated hydrocarbons), which are 

the dominant hydrocarbon present in SBF, has received little attention. Unsaturated 

hydrocarbons, such as those found in SBF, are known to biodegrade more quickly in anaerobic 

environments compared to saturated hydrocarbons of similar length. The presence of an 

unsaturated double bond appears to raise the reactivity of olefins. It is not known if the same 

organic acid addition reactions proposed for the biodegradation of saturated hydrocarbons would 

also be applied to unsaturated hydrocarbons, or if the mechanisms involving the incorporation of 

water across the double bond of the unsaturated compound forming an epoxide or an alcohol as 

seen in aerobic degradation of unsaturated hydrocarbons would occur. 

Schink (1985) enriched methanogenic cultures on normal alkanes, branched alkanes, and 

alkenes. Only 1-hexadecene and squalene increased methanogenesis over that of controls. 

About 78-91 percent of the theoretical methane production was observed from hexadecene. 

Growth was much poorer and methanogenesis stopped after a short period when squalene was 

used as the substrate. It was proposed that hydration across the double bond to produce an 

alcohol was the most likely reaction. Later Schink (1989) noted that the initial reaction might be 

either a biological or an abiotic chemical reaction. There was no evidence for or against either of 
13 

these possibilities. It can be concluded that anaerobic degradation of alkenes appears to be 

feasible but the information concerning the types of alkenes that are degraded anaerobically and 

the mechanisms that organisms can use to degrade these compounds is limited. 

It is evident that many different organisms have the capability to degrade hydrocarbons in 

different anaerobic conditions i.e., different reducing conditions. During anaerobic degradation 

nitrate, sulfate, and carbon dioxide serve as main terminal electron acceptors. Kleikemper et al. 

(2002) concluded that sulfate reduction was responsible for 70 percent of petroleum hydrocarbon 

attenuation at 38 petroleum hydrocarbon contaminated aquifers. SRB were found to grow on 

contaminants such as benzene, toluene, ethylbenzene, xylenes, naphthalene, phenanthrene, 

alkanes, and halogenated compounds. This information plus the fact that sulfate is present in 

high concentrations in seawater suggest that SRB will be major factors contributing to the 

anaerobic degradation of SBF in marine sediments. 

β oxidation

+

+

CH3

CH2

CH2

CH2

CH2

CH2

H3C

CH3

CH

CH2

CH2

CH2

CH2

H C3

CH2

C

OH

O

CH3

CH

CH2

CH2

CH2

CH2

H3C

C

H2C

CH

C

OH

O

OH O

C H3C

O

CoA

C

CH HC

C

HO

O

HO

O

C H3

C

O

OH

Figure 2.4. Incorporation of fumarate into saturated hydrocarbons 

during anaerobic degradation. 
14 

2.3.3 Modeling Microbial Activities 

Microbial growth and degradation of compounds is typically modeled using Monod type kinetics 

as shown in equation (Equation 2.9). In cases where the substrate is not limiting (Ks <<C, the 

Monod equation reduces to zero order, while in cases where Ks >>C it reduces to a first order 

equation. 

( ) 















+ = − Y K s C

XC

r

S

μ Equation 2.9

Where; rS = rate of substrate removal (mg/L • h), μ = maximum specific growth rate (mg cell/mg 

cell ⋅ time), X = concentration of microorganisms in sediment (mg cells/L), C = concentration of 

substrate (mg/L), Y = yield (mg cell produced/mg substrate consumed) and Ks = half saturation 

coefficient (mg/L).

The Monod equation relates the rate of degradation of a substrate to the rate of microbial growth 

by the yield of cells from the degradation of the substrate. The microbial yield from any 

individual chemical can be calculated using thermodynamic principles (McCarty 1972) or it can 

be measured in laboratory studies. In many cases, it is easier to measure the rate of removal of a 

compound and then convert this to a growth rate using a yield than it is to try and directly 

measure a yield in environmental samples. 

There is very little literature concerning rates of microbial growth on hydrocarbons and the 

growth yields from this. Table 2.1 presents some information gathered for hexadecane, which is 

a 16-carbon paraffin rather than an olefin, but it is the best example available in the literature. 

There are large differences between the calculated yields and the experimental yields; each of the 

experimental yields is about 22 percent of the expected yields. 

Table 2.3 

Calculated* and Experimental Yields for Organisms Grown on Hexadecane 

Electron 

Acceptor 

Calculated Yield 

(g cell/g hexadecane) 

Yield Found in Literature 

(g cells/g hexadecane) 

Oxygen 1.3965 0.3 (Chakravarty et al. 1975) 

Sulfate 0.1446 0.0327 (So and Young 1999b) 

CO2 0.0637 No Data 

 *The calculations were performed using the thermodynamic model first 

described by McCarty (1972). 

The other factor that it is important to model to determine the fate of SBF in sediment is the lag 

phase or acclimation period. When cells are exposed to a new carbon source, they typically are 

not able to metabolize it immediately. There is typically a period (from hours to years) in which 

the organisms learn to be able to grow on and degrade a substrate. Although there are many 

theories to explain a lag phase, there are no widely accepted models to account for a lag phase. 

The theories of why microorganisms experience a lag phase can be summarized as follows. 
15 

Several theories have been proposed to explain the acclimation of microorganisms to new 

compounds. These theories include: 

• Proliferation of small populations. This theory suggests that the microorganisms capable 

of degrading the new substrate are present in the natural population, but in very small 

numbers. The acclimation period, then, would reflect the induction of the appropriate 

enzymes and the increase in numbers of the organisms capable of growing on the new 

substrate. This would be reflected in low numbers and slow rates of degradation initially, 

then an increase in numbers of organisms and a corresponding rate increase. 

• Presence of toxins. This theory suggests that the presence of toxic chemicals suppresses 

biodegradation until some organism is capable of degrading or are not inhibited by the 

toxin develop. 

• Predation by protozoa. It has been observed that when protozoa (which normally feed on 

bacteria) are inhibited the lag times seen for acclimation to new materials are decreased 

dramatically. It is presumed that the grazing of the protozoa on the bacteria keeps the 

population of the acclimating bacteria so low that noticeable degradation does not occur. 

• Appearance of new genotypes. Natural mutations occur about once every million cell 

divisions in a bacterial culture. If the mutation results in a new genotype with altered 

enzymes that are capable of degrading the new substrate it will give the culture a 

selective advantage. 

• Diauxie. This theory suggests that some substrates are degraded preferentially over other 

substrates. For example if glucose is present in a media, many organisms will degrade 

only it until it is gone then they will begin to degrade the other substrates. The lag phase 

would be due to the organisms degrading the other substrate first. 

• Enzyme induction. This theory presumes that the acclimation period is due to enzyme 

induction in a population that is already present. The enzymes are only produced when 

the substrate is present. When organisms capable of degrading a substrate, but have been 

degrading something else, are then exposed to the substrate, it usually takes them a while 

to recognize the new substrate and turn on the appropriate enzyme systems. 

In most cases, several of the theories will apply to the overall explanation of the acclimation or 

lag period. 

2.3.4 Methods for Enumerating Microorganisms in Sediment 

To model the microbial degradation of SBF in deep Gulf sediments it is necessary to study the 

population of organisms present in the sediment, especially those that respond to the presence of 

SBF. The study of environmental microbial ecology has bloomed in the last few years due to the 

advent of newer methods based on genetic profiling of organisms and analysis of specific 

cellular components such as phospholipid fatty acids. Two types of methods were selected for 

this research: growth-based methods and molecular-based methods. 
16 

2.3.4.1 Growth-Based Techniques 

Growth based techniques for environmental microbiology rely on the ability to induce the 

organisms in the environmental sample to reproduce and give some sort of positive response to 

their presence. The response may be the formation of a visible colony on an agar plate or 

causing a color change in a liquid medium. The use of solid medium to culture organisms is the 

foundation behind the majority of medical microbiological studies, but is not recommended for 

growing environmental organisms. The Most Probable Number (MPN) technique is a liquid 

based technique. An MPN enumeration is based on the observation of whether or not growth 

occurs in a series of culture containers of progressively increasing dilution. Determination of the 

dilution separating growth from no-growth can be used with a statistical technique to infer the 

concentration of organisms in the original sample. Turbidity is often used as an indicator of 

growth. The indicator could also be the measurement of a substrate consumed or end product 

produced. The tubes that show growth are scored and the distribution of positive tubes among 

the dilutions is statistically related to the number of organisms present in the original sample. 

This is done using the MPN tables that are based on the mathematical approaches of Halvorson 

and Ziegler (1933). Cochran (1950) later contributed procedures that estimate error and 

calculate confidence limits. Woomer (1994) also gave attention to the reliability of experimental 

results, including the criteria for discarding data that do not comply with the principle 

assumptions that underlie the use of this technique. The MPN data can also be interpreted by 

using the Thomas equation (Thomas 1942). 

2.3.4.2 Molecular Based Techniques 

The discovery of DNA and the development of tools for purification isolation and rapid 

sequencing of DNA have all contributed to the development of molecular methods for use in 

environmental microbiology. A variety of molecular based techniques has been described over 

the last two decades, which give direct counts of microorganisms in environmental samples. 

This involves direct microscopic observations, which yields high numbers, has less bias and 

counts both live and dead cells (if necessary). Staining procedures are developed to allow direct 

counts of living bacteria. As all the active cells are expected to have DNA or RNA, the most 

common staining procedures involve the DNA or RNA probes. The initial probes developed 

were used for determining the total counts of bacteria. Later, rRNA based probes were 

developed to identify the phylogenetic groups of bacteria. 

Total counts: Several dyes have been developed to enumerate total bacterial content of 

samples. In 1978, Rublee and Dornseif determined the number of bacteria in the sediments of 

North Carolina salt marsh by direct count epifluorescent illumination and acridine orange (AO) 

stain. Acridine orange direct counting (AODC) is based on the RNA/DNA ratio in a cell. Yu et 

al. (1995) stated that at relatively low AO concentration, the active bacteria (cells with high 

amounts of RNA) could be counted as fluorescent red-orange cells because of the predominance 

of RNA while inactive bacteria have mostly DNA and will fluoresce green. In natural and 

undefined bacterial communities, the RNA/DNA ratio in a cell and thus the AO color reaction 

could be affected by growth media. AO has also been noted to react nonspecifically with 
17 

organic material in soils and sediments thus making AODC a poor method for assessment of the 

activity of cells in environmental samples. 

Porter and Fieg (1980) reported the use of 4′-6-diamidino-2-phenylindole dihydrochloride 

(DAPI) for identifying and counting aquatic microflora. The DAPI stain binds to DNA due to 

intercalation between base pairs or by associating itself with the adenosine thymine clusters in 

the minor groove of the DNA double helix. DAPI can also bind to the RNA by somewhat 

different mechanism that is expected to involve adenosine uracil selective intercalation. 

Fluorescent enhancement is observed when DAPI binds to the DNA due to the displacement of 

water molecules from both DAPI and the minor groove (Kubista et al. 1987; Tanious et al. 1992; 

Pineda de Castro and Zacharias 2000; Molecular probes 2001). DAPI was chosen as a dye for 

total cell counts over acridine orange for this research, in the hopes of minimizing interference 

from natural organic matter in the sediment. 

Phylogenetic identification: Many methods have been developed to analyze DNA and RNA of 

cells. The focus has been on the use of the polymerase chain reaction (PCR) in the detection and 

analysis of the DNA. This method can determine whether a specific organism is present in the 

sample, but most PCR methods are not quantitative in nature. Real time or quantitative PCR 

where the detection of a signal based on how many rounds of thermal cycling of PCR reaction 

has taken place has been developed in the last two to three years, but is not widely proven in 

environmental samples. The major improvement in detection and enumeration of specific 

environmental organisms is the sequencing and comparative analysis of RNA molecules. The 

sequencing of ribosomal RNA (rRNA) has provided the first consistent taxonomic description of 

microorganisms. Stahl (1986) and Amann et al. (1995) have described in detail the various DNA 

and RNA based methods. 

The 5S, the 16S (and 16S-like), the 23S (and the 23S-like) rRNA, are common types of rRNA 

present in the ribosomes of prokaryotes and eukaryotes. The rRNA is composed of structural 

domains. With increase in phylogenetic distance, sequence variations occur in these structural 

domains. While the most variable regions in these domains help distinguish between species and 

genera, the regions that vary to small extents allow inference of relationships between members 

of three main domains: Eubacteria, Eukaryotes, and Archaebacteria. These differences in 

sequence conservation are the basis for designing nucleic acid probes. The newly designed 

oligonucleotide probes can be used to determine environmental diversity, as there are group- and 

species-specific probes. To date over 5,000 16S-like rRNA sequences have been developed and 

are available in the GenBank database, which have been used to explore natural microbial 

diversity and phylogeny. 

In order to detect that an oligonucleotide probe has bound to its complementary DNA or RNA in 

a cell the probes are usually labeled with single fluorescent dye molecule attached to the 5’ end 

via a linker molecule. There are several fluorescent dyes available typically fluorescing green or 

red. The dyes chosen for this study were Fluorescein, which was one of the first dyes used and 

fluoresces green and Texas red which fluoresces red and has the longest excitation and emission 

wavelengths, preventing cross talk between the green emission and red excitation. Table 2.4 

presents the oligonucleotide sequences of the phylogenetic probes chosen from literature for 
18 

enumerating different groups. The Texas red fluorescent dye was used for the probe directed at 

eubacteria (Eub 338). The other probes are linked to fluorescein dye. 

Table 2.4 

Molecular Probes for Microbial Enumeration 

Probe Specificity Probe Sequence (5’ to 3’) Reference 

Eub 338 Eubacteria GCTGCCTCCCGTAGGAGT Amann et al. 1990a 

Arch 915 Archaea GTGCTCCCCCGCCAATTCCT Amann et al. 1990b 

Clost I Clostridia TTCTTCCTAATCTCTACGCA Kusel et al. 1999 

SRB 385 Sulfate-reducing 

bacteria 

CGGCGTCGCTGCGTCAGG Amann et al. 1995 

Two methods have been developed for quantitative microbial analysis using phylogenetic 

probes. Quantitative dot blot hybridization involves hybridization of the probe to total rRNA, 

extracted from the environment. Fluorescent whole-cell or in situ hybridization (FISH) involves 

hybridization of the probes to the DNA or RNA of whole cells for quantitative enumeration by 

direct microscopic visualization. FISH was chosen as a molecular tool for enumerating different 

phylogenetic groupings of organisms in the sediment samples. 

FISH is a technique where rRNA is specifically detected within intact cells and can be used to 

directly identify and enumerate microorganisms belonging to a particular phylogenetic group 

(Amann et al. 1995). This method provides more information than dot blot hybridization as it 

involves analysis at the single-cell level. This method not only helps in determining the 

morphology and abundance of uncultured microorganisms but also in analyzing their spatial 

distributions in situ and estimating the in situ growth rates. 

Though the FISH technique has become a powerful tool for quantitative and phylogenetic 

analysis of microorganisms in various environments, it still has problems that need to be 

resolved. It is a direct microscopy method so sediment and detritus will interfere during 

hybridization or by autofluorescence during microscopy. Because of its potential promise of 

direct cellular quantification the FISH method was attempted in this study. 

An important step is the ability to visualize the cells from the samples using microscopy. 

Several studies have investigated the quantitative extraction of cells from sediments. Methods 

have typically involved ultrasonication, vigorous homogenization, and/ or the addition of 

detergents and dispersants. Several of the following methods were attempted in this study. 

Scheraga et al. (1979) reported that the best method for the recovery of bacteria from sediments 

would involve addition of 0.0001 percent cetyltrimethylammonium bromide to the initial dilution 

blank followed by shaking. However, they did not include the comparison of the techniques 

such as sonication and grinding. Ellery and Schleyer (1984) in their studies on sandy sediments 

found that ultrasonication (performed using an ultrasonication bath with a frequency range of 40 

- 50 kHz) was more effective than homogenization at 23000 rpm. They also stated that 

ultrasonication destroyed many bacteria in the sediment they used. 
19 

Velji and Albright (1985) examined in detail the dispersal effect of pyrophosphate and 

ultrasound on bacterial cells in marine surface sediments. They reported that samples treated 

with pyrophosphate and sonication in combination showed a decline in variation within sub 

samples. Schallenberg et al. (1989) reported that the majority of published abundance data 

underestimate the bacterial numbers to various extents due to the difficulties in removing the 

organisms from the sediments. Epstein and Rossel (1995) examined three different ways to 

dislodge bacteria: homogenization in a blender at 16000 rpm, sonication in a sonic bath, and 

sonication by sonic probe (disintegrator with 5 mm tapered microtip). They concluded that the 

use of a sonic probe for 3 times at 60 sec each with an 109 μm amplitude to be the most effective 

device for bacterial dislodgement. Tso and Taghon (1997) used glutaraldehyde to strengthen the 

bacterial cells before sonication. Their studies indicated that dispersant tetra sodium 

pyrophosphate did not allow the cells to reattach to the sediment particles or clump together after 

sonication. This helped in distributing the cells evenly for any further analysis. Sonication for 1 

minute was reported to have resulted in maximal abundances of bacteria and to be effective in 

dislodging the cells from the detritus or sediment particles. Frischer et al. (2000) evaluated a 

modified protocol for extracting cells from salt marsh sediments that involved the use of 

homogenization, detergents, and dispersants, but did not require sonication. They reported that 

their technique (which involved addition of 0.01M sodium pyrophosphate and 0.09 percent 

Tween 80, rigorous vortexing, slow centrifugation, supernatant removal, and then cell collection 

by fast centrifugation of supernatant) allowed the rapid and quantitative extraction of cells from 

sediments that had been stored in formalin, while avoiding possible cell lysis by sonication. The 

resulting cell extract were substantially reduced in sediment and detritus content and were 

therefore amenable to hybridization protocols. The last two papers contradict each other and 

exemplify the troubles associated with separating organisms from sediments. It is important to 

note that the majority of the research reported to date used relatively sandy sediments so 

separation of organisms from the sediment is possible. In all of the research, once the organisms 

were dislodged from the sediment the larger sediment particles were allowed to settle and the 

organisms are assumed to be in the aqueous phase. The separation of organisms and solids in 

sediment with relatively higher organic matter and clay particles is much more difficult than for 

sandy sediments, researchers have avoided these types of sediments. 
21 

CHAPTER 3 METHODOLOGY 

The sediments were collected by Continental Shelf Associates during the seabed survey 

sponsored by the MMS, DOE, and the Synthetic Based Muds Research Group. The VK916 

samples were collected during the MMS Deepwater Study (2000-2002). The sediments were 

collected from seven geographic locations (Figure 3.1). Two samples were collected from each 

geographic location, one within 100 m of a drilling site where synthetic based mud cuttings were 

discharged (near field (NF)) and the other at a location near that site that was not expected to be 

impacted by drilling activity to serve as a control (far field (FF)). The sediments were shipped 

immediately on ice (arriving still cold) and have been kept and worked with at 4°C at all times. 

In order to use the four jars sent as one sample, they were homogenized into one sample and then 

subdivided again into two sub samples. The two were considered equal sub samples, 

representative of the entire sample set from each site. 

Sub samples of the sediments were extracted analyzed to determine SBF exposure using gas 

chromatographic analysis (Section 3.5.3). Table 3.1 presents the results and other pertinent data 

for the sediments. This data was used to decide which sediments should be used for further 

study. MP299 was chosen because it was from the shallowest depth. GC112 was chosen 

because it was from a medium depth and the near field sample showed some contamination with 

SBF. VK916 was chosen because it was from the deepest site and the near field sample was 

contaminated with SBF. Samples of these sediments were then sent to the Texas A&M soils 

laboratory for analysis of important sediment properties. The results are presented in Table 3.2. 

These sediments all contain low percentage of sand and high amounts of silt and clay. 

3.1 MPN ENUMERATION OF SPECIFIC NUTRITIONAL GROUPS

The MPN viable count procedure was used to determine the numbers of specific nutritional 

groups i.e. sulfate-reducing bacteria (SRB), methanogens (H2 and acetate utilizing methanogens), 

general anaerobes, and hydrocarbon degrading aerobes. Each enumeration was performed using 

selective media in a five tube dilution series. One set of dilution blanks was prepared for each 

sample and used to inoculate the appropriate dilutions of each specific medium. 

3.1.1 Sample Preparation 

Approximately 10 g of wet sediment was weighed and added to 90 ml phosphate buffered saline 

adjusted to the salinity of seawater (1.236 g Na2HPO4, 0.18 g NaH2PO4•H2O, 26.3 g NaCl and 1 

ml resazurin (1 g/L stock solution) per liter type 1 water) which had been sterilized using an 

autoclave. This represented an initial 10-1 dilution. This initial dilution was shaken vigorously 

on a shaker for 10 min, then put in an ice bath and subjected to sonic disruption with a sonic 

probe at 40 percent power for three, 2 min bursts. The headspace of the dilution bottle was then 

flushed with N2 gas. The initial and remaining dilution blanks were reduced with 10 ml of 10 

mM thioglycolate stock solution and the dilutions were carried out mixing well by shaking each 

transfer. 
22 

Figure 3.1. Geographic locations of the offshore sediments collected. 
23 

Table 3.1 

Sediment Samples Received for Study 

Sediment Location Depth 

(m) 

Pressure 

at Depth 

(psi) 

Presence of SBF 

(mg/kg dry sediment) 

History** 

MP299 NF 66 97 Not detected Drilling activity 

1962-2000; 966 bbl 

of IO/LAO cuttings 

mid 1990s-2000. 

 FF 65 96 Not detected 

EI346 NF 93 137 Trace amounts Drilling activity 

1977-2000; 10,328 

bbl of IO cuttings 

mid 1990s-2000. 

 FF 95 140 Not detected 

EB963 NF 535 787 Trace amounts 598 bbl of IO 

cuttings, last 

discharge 1997. 

 FF 440 647 Not detected 

GC112 NF 535 787 1068 + 300 5,470 bbl IO cuttings 

last discharge 1997. 

 FF 454 667 Not detected 

VK916 NF 1135 1668 11717 + 636 2,510 bbl IO cuttings 

from Nov to Dec 

2001. 

 FF 1114 1638 Not detected 

MC496 NF 550 809 Not detected 1,674 bbl IO cuttings 

last discharge 1998. 

 FF 440 647 Not detected 

MP288 NF 122 179 Not detected Drilling activity 

1968-1997; 98 bbl of 

IO cuttings mid 

1990s-1997. 

 FF 151 222 Not detected 

*The SBF in the sediments were extracted and then analyzed with GC/FID as in Section 3.4.3. 

** The history data were taken from Continental Shelf Associates (2004). All samples were 

collected during the spring and summer, 2002. 
24 

Table 3.2 

Chemical Properties of Selected Sediments 

Sediment % Sand % Silt % Clay pH Nitrate-N1

(mg/L) 

Phosphorus1

(mg/L) % Organic

MP299 NF 18 8 74 8.3 3 120 2.94 

MP299 FF 28 40 32 8.1 2 114 3.24 

GC112 NF 20 58 22 8.4 3 98 3.98 

GC112 FF 18 54 28 8.5 2 96 4.13 

VK916 NF 24 64 14 8.4 2 103 5.76 

VK916 FF 30 54 16 8.2 2 104 5.36 

1

 Available form 

3.1.2 Media Preparation 

Biosea Marine Mix was mixed with type 1 reagent grade water and was used as the liquid base 

during the preparation of media for SRB, general anaerobes, and hydrocarbon degraders. The 

SRB medium was prepared using modified Butlin and Postgate’s medium B (3.5 g sodium 

acetate, 1.0 g yeast Extract, 2.0 g MgSO4.7H2O, 1.0 g NH4Cl, 0.06 g CaCl2.2H2O, 0.5 g 

KH2PO4, 0.005 g FeSO4.7H2O, 0.1 g ascorbic acid, 1.0 ml resazurin stock (1 g/L) per liter of 

type 1 water. The medium was boiled and cooled under nitrogen, before 9 mL was transferred to 

Hungate screw cap tubes using strict anaerobic technique. Nails were added to pre-reduce the 

medium and reveal SRB activity. The nails were washed in dichloromethane (twice) to remove 

rust prevention oils and dried before adding one nail to each tube. The tubes were sealed with 

Hungate screw caps and septa and autoclaved before use. 

The medium for general anaerobes was 1/4 strength TGY (Atlas, 1997), which contains 1.25 g 

Tryptone (pancreatic digest of casein), 1.25 g yeast extract, 0.25 g glucose (dextrose), 0.25 g 

K2HPO4, and 1 mL resazurin stock (1 g/L) per 100 ml of the Biosea Marine Mix. 

The medium for hydrocarbon degraders was prepared by adding 1 mL of a solution of 425 mg 

KH2PO4, 575 mg K2HPO4, and 500 mg NH4NO3, per 125 ml distilled water which had been 

adjusted to pH 7 and filter sterilized (using a syringe filter) to 8 mL of Biosea Marine Mix water 

that had been pre-sterilized in test tubes. This was the only medium not made up or incubated 

under anaerobic conditions. 

The medium for methanogens was modeled after Fedorak and Hrudey (1986) with added salt to 

produce marine conditions. The components are as follows: 10 mL macronutrient solution, 1.0 

mL micronutrient solution, 10 mL Phosphate solution (50 g/L KH2PO4), 26.3 g NaCl, 1 mL 

resazurin (1 g/L) and 5.7 g sodium bicarbonate (added after the medium has been boiled) per 

liter of type 1 water. The macronutrient solution consisted of 50 g NaCl, 50 g NH4Cl, 10 g 

MgCl2.6H2O, and 10 g CaCl2.2H2O per liter of type 1 water. The micronutrient solution 

contained 10 g (NH4)6Mo7O24.4H2O, 0.1 g ZnSO4.7H2O, 0.3 g H3BO3, 1.5 g FeCl2.4H2O, 10 g 
25 

CoCl2.6H2O, 0.03 g MnCl2.4H2O, 0.03 g NiCl2.4H2O, and 0.1 g AlK(SO4)2 .12H2O, per liter of 

type 1 water. 

3.1.3 Inoculation, Incubation, and Results Interpretation 

All inoculations and incubations were performed at 4°C. The incubations were carried out until 

indicators of growth were observed. Different indicators of growth were used for different 

classes or organisms. The detection of methane (using GC-FID), any peak at all above 

background levels, was used as an indicator of growth for methanogens. The dispersion 

(reduction of sheen from the hydrocarbon layer of the medium) after incubation at a 45° angle on 

a tube rotator was used as an indicator for hydrocarbon degraders. A blackening of the nails in 

the medium was used as an indicator of growth of SRB. Turbidity was used as an indicator of 

the growth of general anaerobes. 

The positives or negatives per dilution set were scored and the Thomas Equation or the MPN 

table was then used to determine the MPN per g wet sediment. The value was then converted to 

MPN per g dry sediment by multiplying it with the wet to dry ratio (determined by drying 

sediment in the oven at 104o

C overnight). The same sediment, which was used for the 

inoculation, was used to determine the wet to dry ratio. 

3.2 ENUMERATION USING MOLECULAR TECHNIQUES

The molecular techniques used in this study included DAPI staining for enumeration of total 

cells and FISH for determination of the numbers of organisms in different phylogenetic groups. 

This study was the first application of these techniques in our lab. As such, a number of method 

validation and development techniques were carried out. The probe selection and protocols for 

application (including the hybridization temperature (TH) and the concentration of formamide) 

were performed using pure cultures. Hybridization of the oligonucleotide probe to the sample 

only happens when the DNA is opened (unwound, melted) and the base pairs are then free to 

bind the probe. The hybridization temperature and the formamide concentration control the state 

of opening of the DNA. Each piece of DNA opens at a different TH or formamide concentration. 

The objective of this initial method development was to see if all of the probes could be used at 

the same temperature, thus allowing multiple sample processing. Adjusting the formamide 

concentration is another way to allow this. 

The protocol for separation of cells from sediment and probing these cells was worked up using 

sediments obtained from Galveston Bay. Pure cultures of known organisms were spiked into 

Galveston bay sediment samples for use as validation standards.

3.2.1 Cultures Used in Validation Activities 

The pure cultures used for the method validation were purchased from American type culture 

collection (ATCC) or donated by the biology laboratory in the University of Houston (UH). The 

organisms used were Clostridium alginoliticum (ATCC# 17916), Clostridium sordelli (ATCC# 

9714), Desulfococcus multivorans (ATCC# 33890), Desulfovibrio salexigens (ATCC# 14822),
26 

Escherichia coli (biology lab, UH), Bacillus subtilis (biology lab, UH), Halobacterium 

salinarium (ATCC# 33170), Micrococcus roseus (biology lab, UH), Methanosarcina mazei 

(ATCC# BAA-159), Pseudomonas aeruginosa (biology lab, UH), and Staphylococcus aureus 

(biology lab, UH). The cultures purchased from ATCC were grown in the media specified by 

ATCC for each culture. The others were grown in Nutrient broth (Difco). 

3.2.2 Fixing the Pure Cultures 

The pure cultures were fixed by adding 270 ml of the fixative (29.73 ml of 37 percent 

formaldehyde to 275 mL sterile filtered Biosea Marine Mix, i.e 4 percent formaldehyde solution) 

to 90 ml of mid-log grown cells. The fixative was allowed to react with the cells on ice for at 

least 2 hrs. The fixed cells were then divided into 40 ml allotments in 50 ml centrifuge tubes and 

washed twice by sequential centrifugation and resuspension with filtered sea water to remove the 

formaldehyde. The centrifugation was done at maximum speed (1000 rpm) for 5 min using a 

MSE GT-2 table centrifuge. The final resuspension was in a 1:1 solution of phosphate buffered 

saline (PBS):ethanol. The cells were then transferred into 1.7 ml centrifuge tubes (in 1 ml 

aliquots) and stored at 4o

C ready for probing. 

3.2.3 Fixing the Sediments 

Samples of 100 g of sediment were mixed with 300 ml of fixative cooled to 4°C. The slurry was 

shaken well on a rotary shaker to suspend sediment in fixative and was allowed to sit for 2 - 3 hrs 

at 4o

C. The sediment was then poured into 50 ml centrifuge tubes. The sediment suspension 

was washed twice by sequential centrifugation and resuspension with filtered PBS to remove the 

formaldehyde. The final resuspension was in a 1:1 solution of PBS:ethanol. The tubes were 

stored at –20o

C. 

3.2.4 Preparing the Sediment for FISH 

The pure cultures were ready for the application of the FISH method once fixed, but the 

sediments required further treatment to separate the cells from the solids in the sediment. Many 

methods were tried to separate the cells from the various particles in the sediment but none of 

them worked effectively (Section 5.1.1). The final procedure was as follows: The fixed 

sediment (about 15 ml was required, if not present in one tube then two tubes were combined 

together) was taken from the freezer and was allowed to warm up. The supernatant (ethanol + 

PBS) was removed by decanting after centrifugation. Five grams of the sediment pellet was 

weighed into an aluminum dish and the wet to dry ratio was then determined by drying it 

overnight at 104o

C. A second 5 g of sediment was added to a bottle containing 50 mg sodium 

pyrophosphate in 95 ml PBS. The contents were homogenized by placing the bottle horizontally 

on a rotary shaker for about 15 min. The final volume of the sediment slurry in the bottle was 

noted. This sediment slurry was then used for FISH analysis. 

3.2.5 FISH Examination of the Sediment 

The molecular probes used for the FISH analyses of the sediment were Arch 915 (Archaea),

Clost I (Clostridium), SRB 385 (sulfate-reducing bacteria) and Eub 338 (Eubacteria) (Table 2.4) 
27 

made up in 0.1 ml aliquots of (0.2 μg/mL) in TE (10 mM Tris and 1mM EDTA (pH 7.5-8)). 

DAPI was included for total cell counts and was prepared as a 100 μg/mL solution. 

The probe efficiency and specificity were tested using the pure cultures described above. Further 

method validation was performed by adding 1 ml of fixed cells of pure cultures (positive controls 

for the respective probes) to make sure that the probes were working as expected in the 

sediments. 

The procedure followed for probing the pure cultures and sediments was as follows: A sample 

of 1 mL of the fixed cell solutions or 0.1 mL of the sediment slurry was added to 5 ml 

prewarmed (to 53.5°C) hybridization buffer containing 200 ng of each probe combination. The 

hybridization occurred for 9 hrs (overnight) in a heating block at 53.5°C. The cells were then 

centrifuged, the supernatant poured off and the pellet resuspended in 5 ml prewarmed 

hybridization buffer with no probes and incubated for 1 hr at 53.5°C. The cells were then 

centrifuged again, the supernatant poured off and the pellet resuspended in 5 ml prewarmed 

hybridization buffer before 350 μl DAPI was added and allowed to incubate for 10 min at 

53.5°C. The excess DAPI was washed off by a third and fourth centrifugation and replacement 

of the buffer with clean hybridization buffer and incubation for 10 min at 53.5°C. The sample 

(100 μl) was then filtered onto a 0.2 μm black polycarbonate filter (Millipore Isopore) allowed to 

dry and placed on a microscope slide. 

Counting was done using fluorescence microscopy (Olympus BX51). The fluorescence 

microscope was equipped with specific filters to expose the specimen to the specific excitation 

and pass through the emission wavelengths as required by the fluorescent tag on the probes or 

the DAPI stain. The specificity, emission color of the probes, and the name of filter used to 

visualize the fluorescence are given in Table 3.3. The DAPI filter allowed light in the UV range 

to pass through to the sample as the excitation wavelength and the blue fluorescent light from 

DAPI-stained DNA to pass from the specimen to the observer (camera optics or optic lenses). 

The FITC filter allowed light from the blue spectrum to pass through to the specimen and green 

emission light from the fluorescein stained specimen to pass to the observer. The TRITC filter 

allowed excitation light in the green wavelengths to pass to the specimen and the red 

fluorescence from the Texas Red fluorochrome to pass to the observer. The fluorescing cells 

were counted in approximately 20 microscopic fields for each fluor. The average number of 

cells was then converted into the number of cells per g dry sediment originally used in the 

preparation of the sediment sample taking into account the area of the microscopic field, the 

geometry of the filter, the volume of probed sediment filtered and the original weight of 

sediment added to the buffer. 
28 

Table 3.3 

Expected Fluorescence of Molecular Probes 

Probe Specificity Fluorescing Color on Filter (if positively probed) 

Color Filter 

Eub 338 All Eubacteria Red TRITC

Arch 915 Archaea Green FITC

Clost I Clostridia Green FITC 

SRB 385 Sulfate-reducing bacteria Green FITC 

3.3 ANAEROBIC BIODEGRADATION TESTING

The basis for the anaerobic SBF degradation studies is the closed bottle test (CBT) approved by 

the EPA for testing SBF biodegradability (Herman and Roberts 2005) modified to allow high 

pressure incubations. The traditional incubation vessels for anaerobic testing (serum bottles) 

were changed to flexible walled heavy-duty polyethylene heat-seal bags that would allow the 

transfer of pressure from pressure chambers into the cultures. Three pressure chambers (Figure 

3.2) were constructed, one capable of holding up to 800 psi (corresponding to 503 m in water 

depth), one holding up to 1200 psi (corresponding to 750 m in depth) and one holding up to 1700 

psi (corresponding to 1000 m in depth). The pressure chambers were made from 1-in thick 

stainless steel tubes that were 10 in tall and had 10 in internal diameters. Plates made of 1-in 

stainless steel were made to fit over the top and bottom of the tubes. The end plates have an 

extended inner core, which holds two O-rings used to form an airtight seal with the inner wall of 

the stainless steel tube. The end plates are secured by 18 or 24 steel bolts, depending on the 

vessel. Once the end plates have been secured, water is pumped into the pressure vessel to raise 

the hydrostatic pressure to mimic conditions at the depth at which the sediment had been 

collected. The pressure vessels are incubated in a walk-in room at 4o

C. 

To prove that the plastic bags would be suitable vessels for the tests, near shore sediment was 

placed in plastic sample bags, pressurized to 800 psi and left for 72 hours. The bags did not leak. 

Further proof that the bags would be suitable incubation vessels was obtained by inoculating near 

shore sediment into both the plastic bags and serum bottles. The bags were incubated in the 

pressure vessel (but were not pressurized since these were near shore sediments). The serum 

bottles were incubated alongside the pressure vessel. The results showed the change of 

incubation vessel did not affect the removal of ethyl oleate or tetradecene. 
29 

10”

1”

Outlet 

valve

Inlet valve and 

pressure gauge

Figure 3.2. Pressure vessel. 

3.3.1 General Test Procedures 

Ethyl oleate (a surrogate for an ester based SBF and the positive control used in the EPA CBT) 

and tetradecene (a surrogate for olefin-based SBF) were spiked into the test sediments to a final 

concentration of 2000 mg carbon/kg dry sediment. The sediments were then mixed with 

synthetic marine water (Forty Fathoms Crystal Sea Marine Mix) and a volume of 

sediment/marine water slurry equivalent to 30 g dry sediment was transferred into the incubation 

vessel. Controls consisted of sediment mixed with artificial seawater but not spiked with test 

substrate. 

When high-pressure incubations were required, the sediment seawater slurry was placed into 150 

mL heavy-duty polyethylene heat-seal bags. The bags were heat sealed with a small straw in one 

side of the top. Any air in the bag was pushed up through the small hole left by the straw and 

then the bag was heat-sealed again. The bags were placed inside a water-filled pressure vessel. 

Hydrostatic pressure inside the vessels was applied by using a pump to force excess water into a 

sealed pressure vessel. Sediments were pressurized to a level equal to the pressure encountered 

at the depth of sampling and incubated at 4°C. 
30 

When atmospheric pressure incubations were performed synthetic seawater (Crystal Sea/Forty 

Fathoms Marine mix, Marine Enterprises International, Baltimore, MD) was added to make a 

slurry, and 75 mL of this slurry, containing 30 g/dry wgt sediment, was added to 125 mL serum 

bottles. A drop of resazurin solution (0.5 g/L) was added to indicate the redox conditions inside 

the bottles. The headspace of each vial was then flushed with a stream of nitrogen gas for 1 to 2 

minutes to remove oxygen from the headspace, and the bottles were sealed with 20 mm diameter 

rubber stoppers (Bellco Glass, Vineland NJ) and crimp cap seals (Fisher Scientific). The 

headspace within the bottles was vented to establish an internal pressure equivalent to 

atmospheric pressure. The cultures were incubated at 4°C. 

At timed intervals, the pressure vessels were opened and triplicate bags from each treatment 

were removed. Triplicate bottles were also sacrificed if set up. Microbial activity in the bags or 

bottles was monitored by 1) measuring the production of methane gas, 2) monitoring the 

utilization of sulfate by SRB, and, 3) determining the concentration of SBF surrogate by 

extraction and gas chromatography with a flame ionization detector (GC-FID) analysis. 

3.3.2 First Pressure Vessel Experiment 

The first experiment using the Gulf of Mexico sediment had the dual objectives of 1) 

investigating the anaerobic biodegradation of SBF under simulated deep-sea conditions, and 2) 

determining the necessity of placing sediment under hydrostatic pressure (matching the sampling 

depth). Sediment from two NF sites (MP299 and GC112) was prepared as described above for 

both high-pressure and atmospheric pressure incubations. The MP299 sediment was collected 

from 66 meters depth so it was incubated in bags at 97 psi. The GC112 sediment was collected 

from 535 meters so it was incubated in bags at 787 psi. Samples of both sediments were also 

incubated at atmospheric pressure in serum bottles. 

3.3.3 Other Anaerobic Incubations 

Since the first pressure vessel experiment showed that for MP299 and GC112, the pressure of 

incubation did not cause a significant difference in the degradation of ethyl oleate or tetradecene, 

samples from the far field sites were incubated only at atmospheric pressure. 

Sediment from VK916 NF site was incubated at both atmospheric pressure and 1700 psi. The 

substrates were removed faster than expected so the experiment was started again. There were 

indications that the removal of the substrates was faster at higher pressure so the incubations 

were only performed at high pressure (1700 psi) when the incubations were restarted. The 

VK916 FF sediment was also incubated at 1700 psi. 

3.4 AEROBIC BIODEGRADATION TEST

The natural oxygen uptake rate and aerobic degradation of SBF was measured using a BI-1000 

electrolytic respirometer (Biosciences Inc.). Sediment from MP299 FF was divided into two 

sub-sets and prepared at 4o

C for the aerobic study. Triplicate samples of the test sub-set (200 g 

of dry sediment each, spiked with 466 mg of tetradecene) and identical triplicate samples of the 
31 

control sub-set (200 g of dry sediment each, not spiked) were placed in reactors and incubated 

at 4o

C. Oxygen consumption data were collected at two hour intervals for 1174 hours (49 days). 

The natural oxygen uptake rate was determined from the average oxygen consumption in the 

control sub-set. The oxygen uptake rate due to the biodegradation of tetradecene was determined 

from the net difference in oxygen consumption between the spiked sub-set and the control subset. 

3.5 ANALYTICAL METHODS

3.5.1 Methane Analysis 

An aliquot of 0.1 cc was taken from the headspace of the MPN tubes or cultures and injected into 

the GC. The GC-FID analysis (HP 6890 Series GC system) was performed with a 30 m HP-5 

(0.32 mm ID, 0.25 micron film) column. Helium was the carrier gas. The oven, injector and 

detector temperatures were set at 50o

C, 50oC, and 250oC respectively. Any peak at all above 

background levels, was taken as a positive for methane production. 

3.5.2 Sulfate Analysis 

Sulfate analysis was performed using a DX-100 Ion Chromatograph (Dionex, Sunnyvale CA). 

Eluent (2.7 mM Na2CO3 + 0.3 mM NaHCO3) was pumped at a flow rate of 1.5 ml/min through 

AG12 and AS12 columns. The concentration of sulfate was determined using an external 

standard curve. 

3.5.3 SBF in Sediment 

An aliquot (20 g wet weight) of sediment from each vial was transferred into a 400 ml Pyrex 

beaker and spiked with 1 ml of an internal standard solution. Two internal standards were used, 

hexamethylbenzene and heneicosane (C21), which were prepared to 500 mg/L in 

dichloromethane. The internal standard solution was mixed into the sediment sample using a 

glass rod, and the sediment was then dried by the addition of anhydrous sodium sulfate. The 

dried sediment was extracted with approximately 100 ml of dichloromethane, and sonicated in a 

water bath (Fisher Scientific) for 20 min. The solvent was decanted through a sodium sulfate 

filter into round bottom flasks. Three dichloromethane washes of the dried sediment were 

performed. Rotary evaporation was used to reduce the solvent volume to 1.8 ml, which was 

transferred into an auto-sampler vial. GC-FID analysis (HP 6890 Series GC system) was 

performed with a 30 m HP-5 (0.32 mm ID, 0.25 micron film) column. Flow rate of helium was 

1 ml/min, and the injector and detector temperatures were set at 275o

C. A ramped temperature 

regime was used, which had an initial temperature of 100o

C for 1 min, then was increased by 2oC

per min to a final temperature of 225oC, which was held for 2 min. Total run time was 66 min. 
32 

3.6 STATISTICAL ANALYSIS

Confidence intervals (95 percent) for MPN values were calculated as described in Standard 

Methods for the Examination of Water and Wastewater (Greenberg et al. 1992). Cochran’s 

analyses (Cochran 1950) was used for comparison of MPN data. Confidence intervals (95 

percent) for the FISH values were calculated using Microsoft Excel or SigmaStat software. 

Student’s t-tests were performed using Microsoft Excel or SigmaStat software. 
33 

CHAPTER 4 INITIAL MODEL DEVELOPMENT 

The model developed starts after discharge is completed and cuttings are uniformly settled on the 

sea floor. The main mechanism of removal of SBF is through microbial degradation. The 

biodegradation of SBF base materials and other hydrocarbons is much more rapid in the presence 

of oxygen (aerobic) than its absence (anaerobic) (Scherrer and Mille 1989). But the amount of 

oxygen in the sea bottom is very limited and in the first centimeters or even millimeters all 

oxygen will be used by aerobes. This depletion of oxygen in the sediment will render the 

sediments anaerobic. Sulfate is abundant in seawater (~29 mM) therefore it is dominant terminal 

electron acceptor for microbial oxidation of SBF base chemicals in anoxic marine sediments 

(Getliff et al. 1997). Methanogenesis occurs only when most of the available sulfate is 

consumed (Friedheim 1997). Because of the availability of electron acceptors in the system, the 

model is divided into three zones; oxygen consumption zone, sulfate consumption zone and CO2

consumption zone. In addition to biodegradation, the concentrations of SBF and electron 

acceptors is affected by bioturbation, sedimentation, compaction, and diffusion. 

4.1 SBF REMOVAL

4.1.1 Oxygen Consumption Zone. 

In this zone, the factors affecting the degradation of SBF in the sediment are diffusion of oxygen 

to the sediment pore water from sea water, bioturbation, and biodegradation. Sediment mixing 

by organisms (bioturbation) and resuspension by bottom currents are two processes, which dilute 

and disperse contaminants that initially settle on the seafloor. Bothner et al. (1992) introduced 

contaminants at the sediment surface and they penetrated to a depth of 5 cm below the seafloor 

because of rapid vertical mixing by organisms living in the sediments and resuspension by 

bottom currents. Soetaert et al. (1996) also used the value of 5 cm for the constant mixed layer, 

after 5 cm they found an exponential decrease in bioturbation and bioturbation approached zero 

at about 10 cm depth. 

Assumptions of the model: 

1. The contaminant is SBF base chemical and it is non diffusible. 

2. The oxygen consumption layer is well mixed via organisms for the first 5 cm, then 

mixing is neglected. 

3. The initial concentration of SBF is uniform throughout the region. 

4. There is no compaction in sediments. 

5. The sediment has a constant porosity. 

6. Only single component (hexadecane) mass transfer is described.

The biodegradation rate of hydrocarbons in the oxygen consumption zone is modeled with 

Monod type kinetics with a factor that allows the concentration of oxygen to be used as a ratelimiting factor. The rate of metabolic activity depends not only on the degradability of the 

hydrocarbons, but also on the availability of the oxygen utilized. This oxygen limitation is 

represented by a hyperbolic function with a half –saturation constant Ks,O. When the 

concentration of oxygen increases, the limitation becomes weaker and rate of hydrocarbon 
34 

consumption will increase, on the other hand as oxygen is removed from the system the activity 

predicted for aerobes slows down and stops (Equation 4.1). 

( ) 















+ 















+ = − K O

O

Y K F

X F

r

s s O

F O

1 ,1 ,

1 1

,

μ Equation 4.1

Where rF,O = the rate of SBF removal due to oxygen consumption, (mg SBF/kg dry sediment •

time), X1 = aerobe concentration in sediment (mg cells/kg dry sediment), F = SBF base chemical 

concentration (mg base chemical/kg dry sediment), μ1 = maximum specific growth rate for 

aerobes (mg cell/mg cell ⋅ time), Ks,1 = half velocity coefficient in oxygen consumption zone (mg 

base chemical/kg dry sediment), Y1 = yield for aerobes (mg cell produced/mg hydrocarbon 

consumed), O = oxygen concentration (mg oxygen/L pore water), and Ks,o= half saturation 

constant for oxygen limitation (mg oxygen /L pore water). 

4.1.2 Sulfate Consumption Zone 

In the absence of oxygen or under limited oxygen concentration, organisms use sulfate as the 

electron acceptor. Because of the very low aqueous solubility of SBF base chemical, it will be 

biodegraded before it can diffuse to other layers. Since sulfate is an electron acceptor, sulfate 

availability will be a limiting factor in hydrocarbon biodegradation. This can be represented by 

the Monod equation with half-saturation constant Ks, SO4. In the sulfate consumption zone 

oxygen is inhibitory for sulfate reducing organisms. This inhibition is added to the rate equation 

with a function suggested by Van Capellan et al. (1993). When the concentration of oxygen 

increases the usage of sulfate in biodegradation of hydrocarbon will decrease. Limiting and 

inhibitory functions in the model will allow the use of a single equation for each electron 

acceptor zone. The equation describing the SBF concentration in the sulfate consumption zone 

is presented as Equation 4.2. 

( ) 















 +















+ 















+ = − K O

K

K S

S

Y K F

X F

r

O SO

O SO

s s SO

F SO '

,

'

,

2 ,2 ,

2 2

,

4

4

4

4

μ Equation 4.2

Where rF,SO4 = the rate of SBF degradation in the sulfate utilizing region (mg SBF/kg dry 

sediment • time), X2 = SRB concentration in sediment (mg cell/kg dry sediment), F = SBF base 

chemical concentration (mg base chemical/kg dry sediment), μ2= maximum specific growth rate 

for SRB (mg cells/mg cells ⋅ time), Ks,2 = half velocity coefficient in sulfate consumption zone 

(mg base chemical /kg dry sediment), Y2 = yield for SRB (mg cells produced/mg base chemical 

consumed), S = sulfate concentration (mg sulfate/L pore water), Ks,SO4= half saturation constant 

for sulfate limitation (mg sulfate/L pore water), O = oxygen concentration (mg oxygen/L pore 

water), and K`O,SO4 =half saturation constant for oxygen inhibition against sulfate usage (mg 

oxygen/L pore water). 

4.1.3 CO2 Consumption Zone 

In the absence of sulfate or under limited sulfate concentrations, methanogens will use CO2 as an 

electron acceptor and degrade hydrocarbons. O2 and SO4 are inhibitory for methanogens and 
35 

inhibition functions must be included on the equation. The mass balance equation becomes 

Equation 4.3. The concentration of CO2 is expected to be non-limiting since it is produced by 

the other organisms in the O2 and sulfate consumption zones and it is produced in the 

methanogenic zone, so there is no component of the methanogenic equation limiting SBF 

degradation based on CO2 concentration. 

( ) 















 +















+ 















+ = K O

K

K S

K

Y K F

X F

r

O CO

O CO

SO CO

SO CO

s

F CO '

,

'

,

'

,

'

,

3 ,3

3 3

, 2

2

2

4 2

μ 4 2

Equation 4.3

Where rF,CO2 = the rate of SBF degradation in the methanogenic region (mg SBF/kg dry sediment 

• time), X3 = methanogen concentration in sediment (mg cell/kg dry sediment), F = SBF base 

chemical concentration (mg base chemical/kg dry sediment), μ3 = maximum specific growth rate 

for methanogens (mg cells/mg cells • time), Ks,3 = half velocity coefficient in carbon dioxide 

consumption zone (mg base chemical/kg dry sediment), Y3 = yield for methanogens (mg cells 

produced/mg base chemical consumed), S = sulfate concentration (mg sulfate/L pore water), 

K`SO4,CO2= half saturation constant for sulfate inhibition against CO2 usage (mg sulfate/L pore 

water), O = oxygen concentration (mg oxygen/L pore water), and K`O,CO2 = half saturation 

constant for oxygen inhibition against CO2 usage (mg oxygen/L pore water). 

4.1.4 General Formula for All Zones 

When the above three equations are combined the result is Equation 4.4 which has 

biodegradation and mixing by bioturbation as the two effects that control changes in 

concentrations of SBF base chemical in the sediment. 
36 

( )

( )

( )

.

2

2

'

,

'

,

'

,

'

,

3 ,3

3 3

'

,

'

,

2 ,2 ,

2 2

1 ,1 ,

1 1

2

2

4 2

4 2

4

4

4













































































∂

∂

+

















 +















+ 















+ −

















 +















+ 















+ −

















+ 















+ −

=

z

F D

K O

K

K S

K

Y K F

X F

K O

K

K S

S

Y K F

X F

K O

O

Y K F

X F

dt

dF

b

O CO

O CO

SO CO

SO CO

s

O SO

O SO

s s SO

s s O

μ

μ

μ Equation 4.4

4.2 FATE OF PORE WATER SPECIES (OXYGEN AND SULFATE) 

The concentrations of oxygen and sulfate in the pore waters are both used in the SBF equations 

as controls on SBF degradation, equations that can predict their concentration in the pore water 

are necessary. The concentrations of these species in pore water are influenced by bioturbation, 

molecular diffusion, and biodegradation. In the initial model, the biodegradation of each pore 

water species is modeled using the theoretical requirement for each species based on hexadecane 

degradation. 

The summary reactions when hexadecane is the electron donor, oxygen is electron acceptor, and 

NH4

+ is the nitrogen source is: 

C16H34+12.25 O2+2.45 HCO3

- +2.45 NH4+ → 2.45 C5H7O2N + 6.2 CO2 +14.55 H2O

This suggests that for each mole of hexadecane utilized 12.25 moles of oxygen will be required, 

or 1.7 g O2 will be required per g of hexadecane consumed. The overall mass balance for 

oxygen in the sediment pore water then becomes Equation 4.5. 

( ) 















 +















+ −















∂

∂ = +

∂

∂

K O

O

Y K F

X F 1.7*

z

O D ) D

( O

1 S,1 s,O

1 1

2

2

2 b

'

O μ

t θ

Equation 4.5

When hexadecane is the electron donor, sulfate is the electron acceptor, and NH4

+

 is the nitrogen 

source the overall growth equation is: 

C16H34+ 6.125 SO4

2-+ 2.45 HCO3-

+ 2.45 NH4

+

+6.2 H+ → 2.45 C5H7O2N + 6.125 HS- +14.55 

H2O +6.2 CO2. 
37 

This suggests that 6.125 moles of sulfate will be required for each mole of hexadecane 

consumed (or 2.6 g/g). Equation 4.6 presents the overall mass balance for sulfate in the pore 

water. 

















+ 















+ 















+ −















∂

∂ = +

∂

∂

K O

K

K S

S

K F

X F

z

S D D

t

S

O SO

O SO

s s so

b

SO

'

, 4

'

, 4

,2 , 4

2 2

2

2

2

'

4 ( ) 2.6* μ

θ

Equation 4.6

As stated earlier, it is assumed that CO2 will always be in excess, so there is no need to model its 

concentration in sediment pore waters.

4.3 SOLUTION FOR EQUATIONS

To predict the fate of SBF in the sediment it is important to determine concentrations with 

respect to both time and depth. Due to diffusion limitations the different electron acceptor 

processes will be occurring at different sediment depths. To derive a solution for this the depth 

dimension z must be added to the equations. For the oxygen consumption zone the equation then 

becomes Equation 4.7. 

( ) 











































+ 















+ −

















∂

∂

+

= ∂

∂

( , )

( , )

( , )

( , ) 1.7*

( , ) ) ' (

( , )

1 ,1 ,

1

2

2

2

K O z t

O z t

Y K F z t

XF z t

z

O z t D D

t

O z t

s s O

b

o

μ

θ

Equation 4.7

With explicit differencing Equation 4.8 and Equation 4.9 are found. 

( ) 











































+ + −

















∆

− +

+

= ∆

−

+ −

+

k

s O i

k

i

k

s i

k

i

k

i

k

i

k

i

b

o

k

i

k

i

K O

O

Y K F

XF

z

O O O D D

t

O O

1 ,1 ,

1

2

1 1

2 1

1.7 *

2 )'

(

μ

θ

Equation 4.8
38 













































+ + −

















∆

− +

+

= + ∆

+ −

+

k

s O i

k

i

k

s i

k

i

k

i

k

i

k

i

b

o

k

i

k

i

K O

O

Y K F

XF

z

O O O D D

O O t

1 ,1 ,

1

2

1 1

2

'

1

( )

1.7*

2 ( )

μ

θ

Equation 4.9

Similarly Equation 4.10 and Equation 4.11 are found for the concentrations of sulfate in the pore 

water and the concentration of SBF in the bulk sediment. 

































































+ 















+ + −

















∆

− +

+

= + ∆

+ −

+

k

O SO i

O SO

k

s S i

k

i

k

s i

k

i

k

i

k

i

k

i

b

SO

k

i

k

i

K O

K

K S

S

Y K F

XF

z

S S S D D

S S t

'

,

'

, 4

2 ,2 ,

2

2

1 1

2

4

1

4 ( )

2.6*

2 ( )

μ

θ

Equation 4.10

( )

( )

( )













































































∂

− + −

















 +















+ 















+ −

















 +















+ 















+ −

















+ 















+ −

= +∆

+ −

+

2

1 1

'

,

'

,

'

,

'

,

3 ,3

3

'

,

'

,

2 ,2 ,

2

1 ,1 ,

1

1

2

........

2

2

4 2

4 2

4

4

4

z

F F F

D

K O

K

K S

K

Y K F

XF

K O

K

K S

S

Y K F

XF

K O

O

Y K F

XF

F F t

k

i

k

i

k

i

b

k

O CO i

O CO

k

SO CO i

SO CO

k

s i

k

i

k

O SO i

O SO

k

s SO i

k

i

s

k

i

k

s O i

k

i

k

s i

k

i

k

i

k

i

μ

μ

μ Equation 4.11

Where: ∆t is the time step, k Ci is the concentration at the grid point x=xi at time tk (time at the kth 

time step). 
39 

4.4 SPREADSHEET SOLUTION TO THE MODEL

4.4.1 Layout 

A solution to the initial model was developed using two Excel (TM) spreadsheets. In the first sheet 

there was one input matrix and eight solution matrices with 365 rows and 40 columns each. In 

the second sheet there was one solution matrix with 365 rows and 40 columns. In the first sheet 

each solution matrix calculated one aspect of the overall model i.e. substrate concentration due to 

oxygen consumption, number of substrate consuming aerobes, oxygen concentration, etc. The 

new concentrations in each row or column were derived from previous rows or columns by 

applying the appropriate equations. 

4.4.2 Input Parameters 

The input parameters were obtained from the literature wherever possible, estimated from 

preliminary lab data, or obtained using Excel solver. These included the physical properties of 

the sediment, initial concentration of electron donor and electron acceptors, initial organism 

concentrations, time and depth increments, oxygen and sulfate diffusion coefficients, kinetics 

parameters for different electron acceptors consumption zones and bioturbation effect with 

changing depth. These initial parameters used in initial modeling are detailed in Table 4.1. 

4.5 BOUNDARY CONDITIONS

Initial data (time=0) for sulfate and oxygen are taken from Prof. John H. Trefry (Florida State 

University) personal communications. Sulfate concentration was almost constant at 2688 mg/L 

in uncontaminated sites. This was used as the initial average sulfate concentration, at all depths. 

Oxygen was never found deeper than 6 cm. Therefore oxygen diffusion after 6 cm was 

neglected. The initial hexadecane concentration was assumed constant in all depths and 2000 

mg hexadecane per kg dry sediment. 

4.6 SENSITIVITY ANALYSIS

The initial model was developed based on first principles with the intent on using it to determine 

the parameters that would have the most influence on the fate of SBF base chemicals in marine 

sediments. This would then allow the focus on the experimental portion of the research to 

determine the most sensitive factors. The sensitivity of the model to the various parameters was 

investigated by varying one input parameter and generating curves for SBF (hexadecane), 

oxygen and sulfate concentrations in the sediment after two years at different depths, returning 

the changed parameter back to the initial setting (Table 4.1) and then changing the next 

parameter, etc. 
40 

Table 4.1 

Parameter Values Used in Initial Modeling 

Param. Value Units Description Ref 

ρs 2.65 kg/L Density of sediment 1 

ε 0.924 Porosity 2 

θ 1.082 Turtuosity (1/ ε) 3 

F 2000 mg/kg Hexadecane concentration in dry sediment A 

O 6.8 mg/L Oxygen concentration 1 

S 2688 mM Sulfate concentration 1 

X1.0 2.347 mg/kg Initial aerobic cell concentration 4

X2,0 5035 mg/kg Initial anaerobic (SO4) cell concentration C.E

X3,0 0.589 mg/kg Initial anaerobic (CO2) cell concentration C.E

X1.f 33.56 mg/kg Average final aerobic cell concentration A 

X2,f 50350 mg/kg Average final anaerobic (SO4) cell concentration A 

X3,f 589 mg/kg Average final anaerobic (CO2) cell concentration. A 

μ1 0.017 d-1 Maximum specific growth rate (O2) M 

μ2 7.5x10-6 d-1 Maximum specific growth rate (SO4) M 

μ3 0.001 d-1 Maximum specific growth rate (CO2) M 

Ks,1 1.19 mg/kg Half-saturation conc. F for aerobic degradation 5 

Ks,2 1.17x10-6 mg/kg Half-saturation conc. F for anoxic (SO4) deg. A 

Ks,3 1.17x10-6 mg/kg Half-saturation conc. F for anoxic (CO2) deg. A 

Y1 0.30 g/g Yield (g aerobic matrices/g hexadecane) 5 

Y2 0.0654 g/g Yield (g anaerobic (SO4) matrices/g hexadecane) 6 

Y3 0.0637 g/g Yield (g anaerobic (CO2) matrices/g hexadecane) C 

Ks,o 0.0192 mg/L Half saturation concentration for O2 limitation for aerobes 5 

KS,SO4 156 mg/L Half saturation concentration for SO4 limitation SRB 7 

K`O,SO4 0.256 mg/L Half saturation concentration for O2 inhibition for SRB 8 

K`O,CO2 0.256 mg/L Half saturation concentration for O2 inhibition for methanogens 8 

K`SO4,CO2 98 mg/L Half saturation concentration for SO4 inhibition for methanogens 8 

∆z 2 cm Depth increment M 

∆t 2 day Time increment M 

D`O 0.955 cm2

/d Diffusion coefficient of O2 in sea water 9 

D`SO4 0.522 cm2

/d Diffusion coefficient of SO4 in sea water 10 

D O 0.815 cm2

/d Diffusion coefficient of O2 in sediment pore water C 

D SO4 0.446 cm2

/d Diffusion coefficient of SO4 in sediment pore water C 

Db0 3.3x10-2 cm2

/d Bioturbation coefficient 11 

xb 5 cm Thickness of constant bioturbation layer 11 

coeffDb 1 cm Coefficient of exponential bioturbation decrease 11 

1)John H. Trefry, Florida State University, Personal Communication (2) Murray et al. 1978, (3) Ullman and Aller, 

1982, (4) Berte-Corti and Bruns 1999, (5) Chakravarty 1975, (6) So and Young 1999b, (7) Boudreau and Westrich 

1984, (8) Van Cappellen and Wang 1995, (9) Soetaert 1996, (10) Li and Gregory 1974, (11) Wijsman et al. 1997** 

A) Assumed parameters, C.E) Calculated from experimental results, C) Calculated, M) parameter derived by model 

calibration. ** original data adapted to appropriate unit. 
41 

4.6.1 Physical Properties 

4.6.1.1 Porosity and Tortuosity of the Sediment 

The initial porosity assumption was based on work by Murray et al. (1978). The sediments in 

the Gulf of Mexico may have different porosities than those studied by Murray and the addition 

of cuttings may affect the porosity of the sediment. Sediment porosity could vary from as low as 

0.4 (high clay soil) to 0.98 (sandy sediment). When the porosity assumption used in the model 

was 0.924 (Figure 4.1 a), the hexadecane was removed from the first 4 cm (due to oxygen 

consuming reactions) and decreased from the initial 2,000 mg/kg to about 1200 mg/kg in the rest 

of the sediment during the first two years. Oxygen was completely consumed in the first four 

cm. The concentration of sulfate decreased slightly but it never became limiting, so 

methanogenesis would not be expected to be important. When the porosity was reduced to 0.7 

(Figure 4.1 b) the model predicted the concentration of hexadecane left in the sediment would 

increase slightly in the first four cm because of oxygen diffusion limitations but remained 

relatively the same in the rest of the sediment because sulfate was never depleted from the 

sediment, even though the concentration of sulfate decreased greatly due to diffusion limitations. 

When the porosity was decreased to 0.4 (Figure 4.1-c), the sulfate was depleted below 7 cm in 

the two year period and the hexadecane concentration remaining in the sediment increased to 

approximately 1600 mg/kg. 

These results suggest that the model is sensitive to the porosity parameters, but it would take a 

significantly low porosity to cause a complete depletion of sulfate in the sediment. 

4.6.1.2 Oxygen Diffusion Coefficient 

In this sensitivity analysis the initial assumption of the oxygen concentration with depth was not 

changed. The initial oxygen profile taken from non-contaminated Gulf sediment is used and in 

any point it is assumed that oxygen concentration cannot be higher than this initial condition. 

The diffusion coefficient can change with temperature and dynamic viscosity. The diffusion 

coefficient for oxygen was calculated at 0o

C, 5oC, 20oC to be 0.938, 0.955, and 1.01 cm2/day 

respectively. In this temperature range changes in diffusion coefficient do not significantly 

change the results of model (Figure 4.2). 

4.6.1.3 Sulfate Diffusion Coefficient. 

Similarly to the oxygen diffusion coefficient the sulfate diffusion coefficient would be different 

at different water temperatures. The diffusion coefficient for sulfate was calculated for 

temperatures of 0o

C, 5oC, 20oC as 0.422, 0.522, and 0.823 cm2/day respectively. In this 

temperature range changes in the sulfate diffusion coefficient do not change the results of model 

(Figure 4.3). 
42 

a) Porosity = 0.924 

0

500

1000

1500

2000

2500

3000

0 5 10 15 20 25 30

Hexadecane (mg/kg dry sed.)

Sulfate (mg/L pore water)

0

1

2

3

4

5

6

7

Oxygen (mg/L pore water)

b) Porosity = 0.7

0

500

1000

1500

2000

2500

3000

0 5 10 15 20 25 30

Hexadecane (mg/kg dry sed.)

Sulfate (mg/L pore water)

0

1

2

3

4

5

6

7

Oxygen (mg/L pore water)

c) Porosity = 0.4 

0

500

1000

1500

2000

2500

3000

0 5 10 15 20 25 30

Hexadecane (mg/kg dry sed.)

Sulfate (mg/L pore water)

0

1

2

3

4

5

6

7

Oxygen (mg/L pore water)

Hexadecane Sulfate Oxygen

Depth (cm) 

Figure 4.1. Effect of porosity on O2, SO4, and hexadecane concentrations 

in the first 30 cm after two years. 
43 

a) DO = 0.938 cm2

/ day 

0

500

1000

1500

2000

2500

3000

0 5 10 15 20 25 30

Hexadecane (mg/kg dry sed.)

Sulfate (mg/L pore water)

0

1

2

3

4

5

6

7

Oxygen (mg/L pore water)

b) DO = 0.955 cm2

/ day

0

500

1000

1500

2000

2500

3000

0 5 10 15 20 25 30

Hexadecane (mg/kg dry sed.)

Sulfate (mg/L pore water)

0

1

2

3

4

5

6

7

Oxygen (mg/L pore water)

c) DO = 1.01 cm2

/ day 

0

500

1000

1500

2000

2500

3000

0 5 10 15 20 25 30

Depth (cm)

Hexadecane (mg/kg dry sed.)

Sulfate (mg/L pore water)

0

1

2

3

4

5

6

7

Oxygen (mg/L pore water)

hexadecane Sulfate oxygen

Depth (cm) 

Figure 4.2. Effect of the oxygen diffusion coefficient on O2, SO4, and hexadecane 

concentrations in the first 30 cm after two years. 
44 

a) DSO4 = 0.422 cm2

/ day 

0

500

1000

1500

2000

2500

3000

0 5 10 15 20 25 30

Hexadecane (mg/kg dry sed.)

Sulfate (mg/L pore water)

0

1

2

3

4

5

6

7

Oxygen (mg/L pore water)

b) DSO4 = 0.522 cm2

/ day

0

500

1000

1500

2000

2500

3000

0 5 10 15 20 25 30

Hexadecane (mg/kg dry sed.)

Sulfate (mg/L pore water)

0

1

2

3

4

5

6

7

Oxygen (mg/L pore water)

c) DSO4 = 0.823 cm2

/ day 

0

500

1000

1500

2000

2500

3000

0 5 10 15 20 25 30

Hexadecane (mg/kg dry sed.)

Sulfate (mg/L pore water)

0

1

2

3

4

5

6

7

Oxygen (mg/L pore water)

Hexadecane Sulfate Oxygen

Depth (cm) 

Figure 4.3. Effect of sulfate diffusion coefficient on O2, SO4, and hexadecane 

concentrations in the first 30 cm after two years. 
45 

4.6.1.4 Initial Concentration of Hexadecane 

In the initial parameters it is assumed that the initial hexadecane amount in all sediment is 

homogenous and 2000 mg/kg dry sediment. In reality, the hexadecane concentration in the 

sediment will be different depending on how the cuttings are processed before disposal and how 

the cuttings become dispersed on the sediment. In this sensitivity analysis, the initial hexadecane 

concentration was varied from 400 to 4000 mg/kg sediment. As would be expected a lower 

initial hexadecane concentration results in more complete biodegradation of hexadecane in the 

two-year period (Figure 4.4). The model is sensitive to different initial hexadecane 

concentrations. 

4.6.2 Biological Parameters 

Although the theory for modeling biological systems is quite well developed, there are very few 

studies reported in the literature that can be used as sources of the coefficients for modeling 

biological processes in the environment. The sensitivity analysis was generally conducted by 

varying the biological coefficient 10-fold higher and lower than the value used as the initial 

assumption. 

4.6.2.1 Bioturbation Coefficient 

Because bioturbation is effective in the first few centimeters but decreases exponentially with 

depth, the effect of bioturbation is only shown in the first few centimeters in Figure 4.5. 

Decreasing the bioturbation coefficient from 0.033 to 0.0022 cm2

/d did not significantly change 

the model predictions for oxygen, sulfate or tetradecene concentration at any depth. Increasing 

the coefficient to 0.33 cm2

/d resulted in a prediction of higher concentrations of hexadecane in 

shallower sediment. Hexadecane concentration as shown in Figure 4.5 c is higher shown in 

Figure 4.5 a or b. The more disturbed sediment is also more homogenous throughout the depth. 

4.6.2.2 Oxygen Consumption Zone 

The limitation of the presence of oxygen to the first few centimeters limits the magnitude of 

effects that changing the parameters associated with degradation of the substrate in the oxygen 

zone will have on the system as a whole. 

Maximum Growth rate constant (μ1): The maximum growth rate for aerobes was decreased 

(Figure 4.6 a) or increased (Figure 4.6 c) by tenfold. Increasing the growth rate did not affect the 

consumption of hexadecane in the sediment significantly (due to oxygen limitations) but 

decreasing the value tenfold caused the hexadecane consumption to decrease in the first few 

centimeters than in the deeper sediment. This is because aerobic degradation became very slow 

and oxygen was inhibitory for anaerobic biodegradation of hexadecane by SRB so no 

degradation occurred. In Figure 4.6 a the predicted concentration of hexadecane in the aerobic 

zone is actually higher than predicted concentration of hexadecane in the anaerobic zone (deeper 

than 8 cm because the activity of the SRB was greater than the activity of the aerobes. 
46 

a) F = 500 mg hexadecane/kg dry sediment 

0

500

1000

1500

2000

2500

3000

0 5 10 15 20 25 30

Hexadecane (mg/kg dry sed.)

Sulfate (mg/L pore water)

0

1

2

3

4

5

6

7

Oxygen (mg/L pore water)

b) F = 2000 mg hexadecane/kg dry sediment

0

500

1000

1500

2000

2500

3000

0 5 10 15 20 25 30

Hexadecane (mg/kg dry sed.)

Sulfate (mg/L pore water)

0

1

2

3

4

5

6

7

Oxygen (mg/L pore water)

c) F = 4000 mg hexadecane/kg dry sediment

0

500

1000

1500

2000

2500

3000

3500

0 5 10 15 20 25 30

Hexadecane (mg/kg dry sed.)

Sulfate (mg/L pore water)

0

1

2

3

4

5

6

7

Oxygen (mg/L pore water)

Hexadecane Sulfate Oxygen

Depth (cm) 

Figure 4.4. Effect of the initial hexadecane concentration on O2, SO4, and hexadecane 

concentrations in the first 30 cm after two years. 
47 

a) Db = 0.00022 cm2

/ day 

0

500

1000

1500

2000

2500

3000

0 1 2 3 4 5 6 7 8 9 10

Hexadecane (mg/kg dry sed.)

Sulfate (mg/L pore water)

0

1

2

3

4

5

6

7

Oxygen (mg/L pore water)

b) Db = 0.033 cm2

/ day

0

500

1000

1500

2000

2500

3000

0 1 2 3 4 5 6 7 8 9 10

Hexadecane (mg/kg dry sed.)

Sulfate (mg/L pore water)

0

1

2

3

4

5

6

7

Oxygen (mg/L pore water)

c) Db = 0.33 cm2

/ day 

0

500

1000

1500

2000

2500

3000

0 1 2 3 4 5 6 7 8 9 10

Hexadecane (mg/kg dry sed.)

Sulfate (mg/L pore water)

0

1

2

3

4

5

6

7

Oxygen (mg/L pore water)

Hexadecane Sulfate Oxygen

Depth (cm) 

Figure 4.5. Effect of the bioturbation coefficient on O2, SO4, and hexadecane 

concentrations in the first 10 cm after two years. 
48 

a) μ1 = 0.0017 day-1

0

500

1000

1500

2000

2500

3000

0 1 2 3 4 5 6 7 8 9 10

Hexadecane (mg/kg dry sed.)

Sulfate (mg/L pore water)

0

1

2

3

4

5

6

7

Oxygen (mg/L pore water)

b) μ1 = 0.017 day-1

0

500

1000

1500

2000

2500

3000

0 1 2 3 4 5 6 7 8 9 10

Hexadecane (mg/kg dry sed.)

Sulfate (mg/L pore water)

0

1

2

3

4

5

6

7

Oxygen (mg/L pore water)

c) μ1 = 0.17 day-1

0

500

1000

1500

2000

2500

3000

0 1 2 3 4 5 6 7 8 9 10

Hexadecane (mg/kg dry sed.)

Sulfate (mg/L pore water)

0

1

2

3

4

5

6

7

Oxygen (mg/L pore water)

Hexadecane Sulfate Oxygen

Depth (cm) 

Figure 4.6. Effect of the growth rate of aerobes on O2, SO4, and hexadecane 

concentrations in the first 10 cm after two years. 
49 

Aerobic initial cell concentration (X1,0): When the concentration of hexadecane degrading 

aerobes was increased, hexadecane consumption did not change greatly (Figure 4.7 c) again due 

to oxygen limitations. When the initial aerobe concentration was decreased (Figure 4.7 a) the 

model predicted that slightly more hexadecane would be left in the sediment after 2 years of 

incubation. This is not a significant difference and can only be observed at the 2 cm depth. 

Yield (Y1): The calculated yield and the yield found in archives for aerobes depicted in Table 

2.3 are 1.3965 and 0.3 g cells per g hexadecane consumed. In this sensitivity analysis, the 

calculated yield was used as a maximum yield, because this value is maximum theoretical yield. 

The minimum yield was chosen to be 10 fold less than the archival observed yield. When the 

yield was decreased (Figure 4.8 a) there was very little difference in the predicted concentration 

of hexadecane, sulfate or oxygen in the sediment from those observed when the archival 

assumption was used, again a small difference at 2 cm is visible. When the yield was increased 

to the theoretical value, the concentrations of O2 and hexadecane in the first few centimeters 

were increased greatly (Figure 4.8 c). Increasing the yield resulted in a reduction in 

biodegradation activity because the population reached its maximum carrying capacity. It is 

unlikely that environmental organisms will ever be able to achieve theoretical yields. The major 

differences are observed in the first 4 cm. 

Half saturation constant for hexadecane limitation in oxygen consumption zone (KS,1): The 

half saturation coefficient should be evaluated in terms of the substrate concentration. When it is 

low and the substrate concentration is high, it will have very little effect. As it approaches the 

substrate concentration (or the substrate concentration decreases), its effect becomes more 

important. The most observable effect here was when KS,1 was 1190 mg/kg (Figure 4.9 c) or 

about 1⁄2 of the initial substrate concentration, there was still a significant amount of hexadecane 

remaining in the aerobic zone (first 4 cm). 

Oxygen limitation coefficient (Ks,o): The oxygen limitation for degradation of hexadecane is 

determined by the enzymes employed in oxygenic reactions by the organisms. Typical 

environmental organisms will have multiple oxygen utilizing systems some with low efficiencies 

that are more rapid when excess oxygen is present and some with very high binding efficiencies 

but have slower rates of reaction. When the oxygen limitation coefficient is high, it means the 

enzyme has low binding capacity and the system will shut down at higher oxygen 

concentrations. When the limitation coefficient was increased, the model predicted the amount 

of hexadecane consumed would decrease as expected (Figure 4.10). It should also be noted that 

the decrease in aerobic activities at higher oxygen concentrations also caused and increase in the 

concentration of hexadecane in the SRB zone, due to the higher concentrations of oxygen in the 

sediment Figure 4.10 c. 
50 

a) X1,0 = 0.2347 mg aerobes /kg dry sediment 

0

500

1000

1500

2000

2500

3000

0 1 2 3 4 5 6 7 8 9 10

Hexadecane (mg/kg dry sed.)

Sulfate (mg/L pore water)

0

1

2

3

4

5

6

7

Oxygen (mg/L pore water)

b) X1,0 = 2.347 mg aerobes /kg dry sediment 

0

500

1000

1500

2000

2500

3000

0 1 2 3 4 5 6 7 8 9 10

Hexadecane (mg/kg dry sed.)

Sulfate (mg/L pore water)

0

1

2

3

4

5

6

7

Oxygen (mg/L pore water)

c) X1,0 = 23.47 mg aerobes /kg dry sediment 

0

500

1000

1500

2000

2500

3000

0 1 2 3 4 5 6 7 8 9 10

Hexadecane (mg/kg dry sed.)

Sulfate (mg/L pore water)

0

1

2

3

4

5

6

7

Oxygen (mg/L pore water)

Hexadecane Sulfate Oxygen

Depth (cm) 

Figure 4.7. Effect of the initial concentration of aerobes on O2, SO4, and 

hexadecane concentrations in the first 10 cm after two years. 
51 

a) Y1 = 0.03 g aerobes formed / g hexadecane consumed 

0

500

1000

1500

2000

2500

3000

0 1 2 3 4 5 6 7 8 9 10

Hexadecane (mg/kg dry sed.)

Sulfate (mg/L pore water)

0

1

2

3

4

5

6

7

Oxygen (mg/L pore water)

b) Y1 = 0.3 g aerobes formed / g hexadecane consumed 

0

500

1000

1500

2000

2500

3000

0 1 2 3 4 5 6 7 8 9 10

Hexadecane (mg/kg dry sed.)

Sulfate (mg/L pore water)

0

1

2

3

4

5

6

7

Oxygen (mg/L pore water)

c) Y1 = 1.4 g aerobes formed / g hexadecane consumed

0

500

1000

1500

2000

2500

3000

0 1 2 3 4 5 6 7 8 9 10

Hexadecane (mg/kg dry sed.)

Sulfate (mg/L pore water)

0

1

2

3

4

5

6

7

Oxygen (mg/L pore water)

Hexadecane Sulfate Oxygen

Depth (cm) 

Figure 4.8. Effect of the yield value for aerobic hexadecane degradation on 

O2, SO4, and hexadecane concentrations in the first 10 cm after 

two years. 
52 

a) KS,1 = 1.190 mg hexadecane / kg dry sediment 

0

500

1000

1500

2000

2500

3000

0 1 2 3 4 5 6 7 8 9 10

Hexadecane (mg/kg dry sed.)

Sulfate (mg/L pore water)

0

1

2

3

4

5

6

7

Oxygen (mg/L pore water)

b) KS,1 = 119.0 mg hexadecane / kg dry sediment 

0

500

1000

1500

2000

2500

3000

0 1 2 3 4 5 6 7 8 9 10

Hexadecane (mg/kg dry sed.)

Sulfate (mg/L pore water)

0

1

2

3

4

5

6

7

Oxygen (mg/L pore water)

c) KS,1 = 1190.0 mg hexadecane / kg dry sediment

0

500

1000

1500

2000

2500

3000

0 1 2 3 4 5 6 7 8 9 10

Hexadecane (mg/kg dry sed.)

Sulfate (mg/L pore water)

0

1

2

3

4

5

6

7

Oxygen (mg/L pore water)

Hexadecane Sulfate Oxygen

Depth (cm) 

Figure 4.9. Effect of the half saturation constant for aerobes on O2, 

SO4, and hexadecane concentrations in the first 10 cm after 

two years. 
53 

a) KS,O = 0.0192 mg oxygen / L pore water 

0

500

1000

1500

2000

2500

3000

0 1 2 3 4 5 6 7 8 9 10

Hexadecane (mg/kg dry sed.)

Sulfate (mg/L pore water)

0

1

2

3

4

5

6

7

Oxygen (mg/L pore water)

b) KS,O = 0.192 mg oxygen / L pore water 

0

500

1000

1500

2000

2500

3000

0 1 2 3 4 5 6 7 8 9 10

Hexadecane (mg/kg dry sed.)

Sulfate (mg/L pore water)

0

1

2

3

4

5

6

7

Oxygen (mg/L pore water)

c) KS,O = 1.92 mg oxygen / L pore water

0

500

1000

1500

2000

2500

3000

0 1 2 3 4 5 6 7 8 9 10

Hexadecane (mg/kg dry sed.)

Sulfate (mg/L pore water)

0

1

2

3

4

5

6

7

Oxygen (mg/L pore water)

Hexadecane Sulfate Oxygen

Depth (cm)

Figure 4.10. Effect of the oxygen limitation coefficient on O2, SO4, and 

hexadecane concentrations in the first 10 cm after two years. 
54 

4.6.2.3 Sulfate Consumption Zone 

Since most of the hexadecane consumption is expected to occur with sulfate as the electron 

acceptor, the kinetic parameters for sulfate reduction should have more of an effect on the model 

predictions. 

Maximum growth rate constant (μ2): As expected the model was very sensitive to changes in 

the maximum growth rate constants for SRB. Even a very small increase (doubling) in μ2 caused 

a large increase in hexadecane consumption (Figure 4.11 a vs b) as indicated by the decrease in 

hexadecane concentrations remaining after two years of incubation. Even a small decrease 

(halving) in μ2 caused large decrease in hexadecane consumption (Figure 4.11 c) as indicated by 

the large increase in hexadecane remaining after 2 years of incubation. The changes in μ2 also 

affected the sulfate concentration in the sediment (as expected). The oxygen concentrations in 

the sediment were not affected, also as expected. 

SRB initial concentration (X2,): When the initial SRB concentration was increased more 

biodegradation of hexadecane occurred as evidenced by the decreasing concentrations of 

hexadecane predicted by the model and shown in Figure 4.12 a through c. High initial SRB 

concentration would occur when sediment has been exposed to hydrocarbons or other carbon 

sources. High initial SRB concentration could also decrease the adaptation period for organisms 

to degrade hexadecane. 

Yield (Y2): The calculated yield and the yield found in archives for SRB were presented in 

Table 2.3 as 0.1446 and 0.0327 g SRB produced per g hexadecane consumed. In this sensitivity 

analysis the theoretical (calculated) yield is used as maximum yield and a value 10 times less 

than the archival yield was used as a minimum yield. In Figure 4.13 a the low yield (0.00327) of 

SRB caused more SO4 to be used but was accompanied by complete removal of hexadecane in 

all depths within the first 2 years. This is due to two factors; 1) the increase in the rate due to an 

increase in yield, an intrinsic relationship in the Monod model and 2) it takes longer to reach the 

carrying capacity of the system. Conversely increasing the yield to the calculated theoretical 

yield caused less sulfate and hexadecane removal from the sediment (Figure 4.13 c). 

Half saturation constant for hexadecane limitation in sulfate consumption zone (Ks,2): 

Because of the high hexadecane concentration in sediment, a change in half saturation constant 

(1000 fold up or down) had no effect on the results from the model prediction (Figure 4.14). In 

the sulfate reaction zone, the half saturation constant for hexadecane is the least effective 

parameter in the model. To have any effect the KS,2 would have to be very near the hexadecane 

concentration. 
55 

a) μ2 = 1.502E-5 day-1 

0

500

1000

1500

2000

2500

3000

0 5 10 15 20

Hexadecane (mg/kg dry sed.)

Sulfate (mg/L pore water)

0

1

2

3

4

5

6

7

Oxygen (mg/L pore water)

b) μ2 = 7.508E-6 day-1

0

500

1000

1500

2000

2500

3000

0 5 10 15 20

Hexadecane (mg/kg dry sed.)

Sulfate (mg/L pore water)

0

1

2

3

4

5

6

7

Oxygen (mg/L pore water)

c) μ2 = 3.754E-6 day-1

0

500

1000

1500

2000

2500

3000

0 5 10 15 20

Hexadecane (mg/kg dry sed.)

Sulfate (mg/L pore water)

0

1

2

3

4

5

6

7

Oxygen (mg/L pore water)

Hexadecane Sulfate Oxygen

Depth (cm) 

Figure 4.11. Effect of the growth rate of SRB on O2, SO4, and hexadecane 

concentrations in the first 30 cm after two years. 
56 

a) X2 = 503.5 mg SRB / kg dry sediment 

0

500

1000

1500

2000

2500

3000

0 5 10 15 20

Hexadecane (mg/kg dry sed.)

Sulfate (mg/L pore water)

0

1

2

3

4

5

6

7

Oxygen (mg/L pore water)

b) X2 = 5035 mg SRB / kg dry sediment 

0

500

1000

1500

2000

2500

3000

0 5 10 15 20

Hexadecane (mg/kg dry sed.)

Sulfate (mg/L pore water)

0

1

2

3

4

5

6

7

Oxygen (mg/L pore water)

c) X2 = 50350 mg SRB / kg dry sediment

0

500

1000

1500

2000

2500

3000

0 5 10 15 20

Hexadecane (mg/kg dry sed.)

Sulfate (mg/L pore water)

0

1

2

3

4

5

6

7

Oxygen (mg/L pore water)

Hexadecane Sulfate Oxygen

Depth (cm) 

Figure 4.12. Effect of the number of SRB on O2, SO4, and hexadecane 

concentrations in the first 20 cm after two years. 
57 

a) Y2 = 0.00327 g SRB formed / g hexadecane consumed 

0

500

1000

1500

2000

2500

3000

0 5 10 15 20

Hexadecane (mg/kg dry sed.)

Sulfate (mg/L pore water)

0

1

2

3

4

5

6

7

Oxygen (mg/L pore water)

b) Y2 = 0.0327 g SRB formed / g hexadecane consumed 

0

500

1000

1500

2000

2500

3000

0 5 10 15 20

Hexadecane (mg/kg dry sed.)

Sulfate (mg/L pore water)

0

1

2

3

4

5

6

7

Oxygen (mg/L pore water)

c) Y2 = 0.1446 g SRB formed / g hexadecane consumed

0

500

1000

1500

2000

2500

3000

0 5 10 15 20

Hexadecane (mg/kg dry sed.)

Sulfate (mg/L pore water)

0

1

2

3

4

5

6

7

Oxygen (mg/L pore water)

Hexadecane Sulfate Oxygen

Depth (cm) 

Figure 4.13. Effect of the yield of SRB on O2, SO4, and hexadecane 

concentrations in the first 20 cm after two years. 
58 

a) KS,2 = 1.17x10-6 mg hexadecane / kg dry sediment 

0

500

1000

1500

2000

2500

3000

0 5 10 15 20

Hexadecane (mg/kg dry sed.)

Sulfate (mg/L pore water)

0

1

2

3

4

5

6

7

Oxygen (mg/L pore water)

b) KS,2 = 1.17x10-3 mg hexadecane / kg dry sediment 

0

500

1000

1500

2000

2500

3000

0 5 10 15 20

Hexadecane (mg/kg dry sed.)

Sulfate (mg/L pore water)

0

1

2

3

4

5

6

7

Oxygen (mg/L pore water)

c) KS,2 = 1.17 mg hexadecane / kg dry sediment

0

500

1000

1500

2000

2500

3000

0 5 10 15 20

Hexadecane (mg/kg dry sed.)

Sulfate (mg/L pore water)

0

1

2

3

4

5

6

7

Oxygen (mg/L pore water)

Hexadecane Sulfate Oxygen

Depth (cm) 

Figure 4.14. Effect of the half saturation constant for SRB on O2, SO4, and 

hexadecane concentrations in the first 20 cm after two years. 
59 

Half saturation constant for sulfate limitation (Ks,SO4): Because of the high sulfate 

concentration in sediment pore water; a change in half saturation constant (of 10 fold up or 

down) has little effect on the result from the model (Figure 4.15). Changing Ks,SO4 would only 

be effective when the concentration of sulfate was very low or the value of the constant was 

close to or higher than the sulfate concentration. Other than when the porosity was decreased to 

a very low value did the model ever predict the sulfate concentration would become limiting. 

Oxygen inhibition coefficient in sulfate consumption (K`

O, SO4): Because of the low oxygen 

concentration in the sediment, and because oxygen can only diffuse to the first few centimeters, 

changing this constant had very little effect on the model predictions. Figure 4.16 demonstrates 

that the only visible effect of decreasing the O2 inhibition coefficient 10X was observed as 

slightly higher hexadecane concentration in the first 4 cm. Increasing KO,SO4 10X caused a 

slightly lower hexadecane concentration at 4 cm. 

4.6.2.4 CO2 Consumption Zone 

Because of high sulfate concentration and low initial methanogen concentration, methanogenesis 

is limited. Therefore, all parameters related to methanogens had very little effect on the model 

predictions. Research concerning methanogenic activities that can be found in the literature does 

not do more than document that this type of biodegradation may occur in deep-sea sediment. 

The sensitivity analysis was run for all of the methanogenic parameters, but the results will not 

be presented here since there were not any significant differences observed in the predictions of 

hexadecane, sulfate, and oxygen concentrations observed in the graphs. 

4.7 CONCLUSIONS FROM INITIAL MODELING

The model was developed using existing fundamental equations for modeling physical and 

biological rates of compound diffusion and biodegradation. The input parameters were obtained 

from a review of existing information from related articles and research or they were estimated 

based on solving for a predicted model performance. With these initial parameters, the model as 

developed in the spreadsheet solution performed well, in other words the predicted results 

compare reasonably with expectations. After all of the hexadecane was consumed in the all 

depths of the sediment, the model predicted oxygen and sulfate concentrations in the sediment 

would to slowly return to initial conditions due to the effects of diffusion and bioturbation. 

The sensitivity analysis showed that the parameters the model was most sensitive to were a) 

porosity of the sediment, b) maximum growth rate constants for SRB and less so for aerobes, c) 

initial cell concentrations of SRB, and d) yields of aerobes and SRB. Sulfate was never limiting 

in the sediment (unless the porosity became very low) and because of the high sulfate 

concentration methanogens had very little impact on the biodegradation of hexadecane. 
60 

a) KS,SO4 = 1555 mg / L pore water 

0

500

1000

1500

2000

2500

3000

0 5 10 15 20

Hexadecane (mg/kg dry sed.)

Sulfate (mg/L pore water)

0

1

2

3

4

5

6

7

Oxygen (mg/L pore water)

b) KS,SO4 = 156 mg / L pore water 

0

500

1000

1500

2000

2500

3000

0 5 10 15 20

Hexadecane (mg/kg dry sed.)

Sulfate (mg/L pore water)

0

1

2

3

4

5

6

7

Oxygen (mg/L pore water)

c) KS,SO4 = 16 mg / L pore water

0

500

1000

1500

2000

2500

3000

0 5 10 15 20

Hexadecane (mg/kg dry sed.)

Sulfate (mg/L pore water)

0

1

2

3

4

5

6

7

Oxygen (mg/L pore water)

Hexadecane Sulfate Oxygen

Depth (cm) 

Figure 4.15. Effect of the sulfate limitation coefficient for SRB on O2, SO4, and hexadecane 

concentrations in the first 20 cm after two years. 
61 

a) K`O,SO4 = 2.56 mg / L pore water 

0

500

1000

1500

2000

2500

3000

0 5 10 15 20

Hexadecane (mg/kg dry sed.)

Sulfate (mg/L pore water)

0

1

2

3

4

5

6

7

Oxygen (mg/L pore water)

b) K`O,SO4 = 0.256 mg / L pore water 

0

500

1000

1500

2000

2500

3000

0 5 10 15 20

Hexadecane (mg/kg dry sed.)

Sulfate (mg/L pore water)

0

1

2

3

4

5

6

7

Oxygen (mg/L pore water)

c) K`O,SO4 = 0.0256 mg / L pore water

0

500

1000

1500

2000

2500

3000

0 5 10 15 20

Hexadecane (mg/kg dry sed.)

Sulfate (mg/L pore water)

0

1

2

3

4

5

6

7

Oxygen (mg/L pore water)

Hexadecane Sulfate Oxygen

Depth (cm) 

Figure 4.16. Effect of the oxygen inhibition coefficient for SRB on O2, SO4, 

and hexadecane concentrations in the first 20 cm after two years. 
62 

a) K`O,CO2 = 2.56 mg / L pore water 

0

500

1000

1500

2000

2500

3000

0 5 10 15 20

Hexadecane (mg/kg dry sed.)

Sulfate (mg/L pore water)

0

1

2

3

4

5

6

7

Oxygen (mg/L pore water)

b) K`O,CO2 = 0.256 mg / L pore water 

0

500

1000

1500

2000

2500

3000

0 5 10 15 20

Hexadecane (mg/kg dry sed.)

Sulfate (mg/L pore water)

0

1

2

3

4

5

6

7

Oxygen (mg/L pore water)

c) K`O,CO2 = 0.0256 mg / L pore water

0

500

1000

1500

2000

2500

3000

0 5 10 15 20

Hexadecane (mg/kg dry sed.)

Sulfate (mg/L pore water)

0

1

2

3

4

5

6

7

Oxygen (mg/L pore water)

Hexadecane Sulfate Oxygen

Depth (cm) 

Figure 4.17. Effect of the oxygen inhibition of methanogens on O2, SO4, and 

hexadecane concentrations in the first 20 cm after two years. 
63 

a) K`SO4,CO2 = 980 mg / L pore water 

0

500

1000

1500

2000

2500

3000

0 5 10 15 20

Hexadecane (mg/kg dry sed.)

Sulfate (mg/L pore water)

0

1

2

3

4

5

6

7

Oxygen (mg/L pore water)

b) K`SO4,CO2 = 98 mg / L pore water 

0

500

1000

1500

2000

2500

3000

0 5 10 15 20

Hexadecane (mg/kg dry sed.)

Sulfate (mg/L pore water)

0

1

2

3

4

5

6

7

Oxygen (mg/L pore water)

c) K`SO4,CO2 = 9.8 mg / L pore water

0

500

1000

1500

2000

2500

3000

0 5 10 15 20

Hexadecane (mg/kg dry sed.)

Sulfate (mg/L pore water)

0

1

2

3

4

5

6

7

Oxygen (mg/L pore water)

Hexadecane Sulfate Oxygen

Depth (cm) 

Figure 4.18. Effect of the sulfate inhibition of methanogens on O2, SO4, and 

hexadecane concentrations in the first 20 cm after two years. 
65 

CHAPTER 5 MICROECOLOGY STUDIES 

5.1 METHOD DEVELOPMENT 

Although the methods used in this research were not developed de novo for this research, a 

considerable effort was made to validate that the methods used were appropriate to meet the 

objectives of the research. 

5.1.1 Separation of Cells and Sediment 

The general appearance of the sediments under the microscope suggested that the sediments 

contained a lot of diffuse organic material that was fluorescing with the cells. Figure 5.1 

presents a photomicrograph of a sediment sample magnified with the 100X objective and viewed 

using the DAPI filter. This is one of the better microscopic fields, and several DAPI stained 

cells can be seen. The cells stained with DAPI are a true blue (a few examples are highlighted 

with a white circle). The organic material is yellow, green, or grey and can mask the blue of the 

DAPI cells. This fluorescence posed problems while performing DAPI counts as well as 

counting through FITC and TRITC filters since there were low levels of autofluorescence in 

these filters as well. 

Figure 5.1. Sediment viewed using the DAPI filter (100x oil objective). 

A sample of sediment was fixed and homogenized as described above (Section 3.2.3). After 

homogenization, the sediment slurry was disrupted by sonication three times at 2 min intervals 

using the sonic probe (25 kHz). The sand particles were allowed to settle out into a pellet and 

the supernatant was poured off carefully into two 40 ml glass centrifuge tubes. These were 

centrifuged slowly (300 rpm) for 2 min using a MSE GT-2 table centrifuge. This resulted in the 

formation of three layers. The topmost clear layer from both the tubes was separated and labeled 

as 1st layer. The second, cloudy, layers from both the tubes were combined in one tube. The 

third layer (i.e., the pellet) was added to the sand pellet. 
66 

The second layer from each tube was diluted with PBS, and the process (from slow 

centrifugation) was repeated twice. All the 1st (clear) layers were added together into one 1st

layer and all the pellets were added into one pellet. The remaining second layer obtained after 

slow centrifugation and separation (3 times) was now treated as the original homogenized 

sediment slurry by adding some more PBS and the whole process (from sonication) was 

repeated. The 1st layer, 2nd layer and pellet were all separated into their respective tubes and the 

volumes noted. These layers were then used for DAPI staining. 

Table 5.1 presents the cell counts after DAPI staining all the three layers of the sediment. 

Theoretically the first layer should have more cells and fewer sediment particles, so that it can be 

used for FISH. The other two layers were expected to be difficult to use in FISH due to the 

presence of interfering sediment particles. The goal was to prove that these layers could be 

discarded because they did not contain significant numbers of cells. The results indicate that the 

2nd layer and the pellet cell counts account for a significant percentage of the total counts and that 

they cannot be discarded. In the case of Galveston Bay sediment the results clearly indicate that 

the 2nd layer has more cell numbers than the 1st layer implying that the cells cannot be separated 

from the sediment particles using these techniques. 

Another attempt to separate the sediments and the cells was done by increasing the pH of the 

supernatant in an attempt to dissolve the organic material, which was thought to be humic or 

fulvic acids. This was accomplished by taking a sample of GC112 fixed sediment slurry and 

disrupting the cells by sonication three times at two-minute intervals using the sonic probe 

(25HZ). The sand portion was then allowed to settle for less than three minutes. The supernatant 

was decanted into a second tube, and after removing a small sample for DAPI staining, its pH 

was raised to about 13 by using 2N NaOH. This basic supernatant was centrifuged for 15 

minutes to remove the cells. The supernatant was then decanted from the pellet. Table 5.2 

presents the results obtained after performing DAPI staining on samples of these solutions to 

visualize the total amount of cells present. 

The results revealed that the sand pellet contained more cells than expected (25 percent of the 

total). This was unexpected. The amount of cells present in the first layer supernatant was 75 

percent of those present in the entire solution (first layer supernatant plus the sand pellet). The 

cell pellet only contained 21 percent of the cells that were in the original supernatant. This is 

where the majority of the cells were supposed to be detected. 

These results again suggest that the removal of the cells from the sediment would not be possible 

with these techniques. Further attempts to separate/clarify the microbial fractions of the 

sediment from the particles in the sediment were as follows: 1. acidification of the fixed sample 

before probing; 2. acidification of the sample after probing; 3. fast centrifugation to separate cells 

into a pellet and leave diffuse organic material in the supernatant. None of these procedures was 

successful and counting was the same as when just homogenization was done for 15 min with 

addition of 0.5 percent sodium pyrophosphate. In summary, the attempts made at cell separation 

were not successful. In order to count as many cells as possible, the whole sediment was used 

for MPN and FISH analysis. It must be kept in mind that there will be interference from natural 

sediment particles.
67 

Table 5.1

Quantitative Analysis of Cell Counts in Separation Layers 

Sediment 1st Layer 

(cells) 

2nd Layer 

(cells) 

Pellet 

(cells) 

Total 

Counts 

(% of total) (% of total) (% of total) (cells) 

Freeport 

Trial I 9.1x108 (65%) 2.7x108 (19%) 2.3x108 (16%) 1.4x109 

Trial II 1.0x108 (18%) 3.5x108 (64%) 1.0x108 (18%) 5.5x108

Galveston Bay 

Trial I 1.3x108

 (40%) 1.4x108 (45%) 4.9x107 (15%) 3.2x108 

Trial II 7.6x107

 (21%) 2.5x108 (67%) 4.5x107 (12%) 3.7x108 

Trial III 7.3x107

 (20%) 2.5x108 (69%) 4.1x107 (11%) 3.6x108 

Sportsman Road 

Trial I 7.1x107

 (56%) 1.9x107 (15%) 3.8x107 (29%) 1.3x108

Trial II 5.0x107

 (49%) 2.6x107 (25%) 2.7x107 (26%) 1.0x108 

Table 5.2 

DAPI Counts on Separated Cells and Supernatants 

Layers DAPI Counts (cells) Cell Recovery 

Original supernatant (OS) 1.4 x 108 75% of total 1 

Sand pellet 4.7 x 107 25% of total 1 

Total 1 1.87 x 108

 

Basic supernatant 7.3 x 107 52% of OS 

Cells 3.00 x 107 21 % of OS 

Total 2 1 x 108 71% of OS 

5.1.2 Most Probable Number (MPN) Technique 

Engineers and microbiologists have used the MPN method to enumerate microorganisms in 

samples since 1915 (Cochran 1950). The validation portion of this research was to ensure that 

the media used gave the highest number of organisms for each of the different types of 

nutritional groups given that the procedures have not been extensively applied to marine 

sediments. The majority of the media used were taken from literature sources but altered to fit 

the desired marine conditions and then tested to see if they were acceptable. There was no way 

to prove that the media was the “best” except by whether it gave higher counts than a different 

formulation, or whether the counts obtained could be predicted based on the expected counts 

from the sediment activity studies. The validation activities also allowed the selection of 

appropriate dilutions for future research. 
68 

Sediments collected from the shores of the Gulf of Mexico were used for the media validation 

studies since there were insufficient amounts of the deep Gulf sediments to use for this test. 

Table 5.3 presents the results obtained during the MPN validation studies. Two media 

formulations were examined for their ability to give the greatest number of SRB. The major 

differences were the use of sodium lactate or sodium acetate as carbon sources. Sodium lactate 

is the standard carbon source used in SRB media, but since the research goal is to study the 

number of organisms that could possibly be involved in hydrocarbon degradation, it was felt that 

acetate would be the more appropriate carbon source since this compound is a product of the βoxidation of hydrocarbons. Lactate is an intermediate of sugar, not hydrocarbon, metabolism. 

The results showed that the use of acetate as an electron donor and carbon source produced 

higher numbers than the use of lactate did, especially in the sediment that was known to be more 

competent at hydrocarbon degradation (Freeport#1). The use of the lactate medium was 

dropped. 

Table 5.3 

Method Validation for MPN Media 

MPN Test Sediment Result 

(MPN/g dry sediment) 

SRB (acetate utilizing) Freeport#1 1.4x109 

Fourchon#4 7.5x107

SRB (lactate utilizing) Freeport#1 2.0x108

 Fourchon#4 2.6x107 

General Anaerobes Freeport#1 1.7x108

 Fourchon#4 5.3x107

Methanogens Freeport#1 5.1x103

 Fourchon#4 3.5x103

The validation of the media used to enumerate other nutritional groups was primarily to show 

that some positive results could be produced using the specific media. Only one formulation of 

each medium was examined. The media for general anaerobes and methanogens both produced 

numbers that would be acceptable. Organisms were counted with each medium and higher 

numbers were found in the sediments that displayed more SBF-degrading activity (Freeport#1, 

see Herman and Roberts 2005). During method validation work, all the dilution sets were started 

at 10-2 and ended in 10-6. The results allowed the selection of different dilution ranges for 

different organisms i.e., decrease dilutions (10-1 - 10-5) for the methanogens, increase to higher 

dilutions (10-3 - 10-7) for SRB and general anaerobes. 

The overall numbers obtained also met theoretical expectations when compared to other 

nutritional groups. The SRB were higher in number than others and this is expected because of 

the high concentration of sulfate in seawater. General anaerobes were lower in numbers than 

SRB, possibly because the media has no electron acceptor and only allows fermentation. 

Methanogens were the lowest in numbers. They were expected to be present in low numbers 

because of the high concentrations of sulfate in seawater, which inhibits methanogenesis. 
69 

5.1.3 Verification of Molecular Technique 

The idea that any growth medium or method, such as those described above for the MPN of 

different nutritional groups, would always give lower numbers than would be truly found in any 

environment has prompted the development of molecular techniques like FISH to allow the 

enumeration of organisms based on their DNA or RNA sequences. The oligonucleotide probes 

used in this study were purchased with fluors that produce different colored signals so that each 

sample could be tested with probes directed to at least two different phylogenetic groups and 

sample volume could be conserved. The ability to sandwich the probes (i.e. use two probes on 

one sample) allows more information to be obtained from each sample. The oligonucleotide 

probe sequences were selected to allow the enumeration of all Eubacteria (Eub 338), all 

Archaebacteria (Arch 915), all Clostridia (Clost I), and most SRB (SRB 385). There is no 

oligonucleotide probe that can be used to enumerate all SRB, but SRB 385 will bind to the 

majority of SRB. The Eubacterial probe was purchased with a Texas Red fluor, which 

fluoresces red and is observed through a filter with excitation and emission wavelengths 

specifically for this fluor (TRITC filter). All of the other probes were purchased conjugated to a 

fluorescein fluor, which is observed through a filter with excitation and emission wavelengths 

specifically for this fluor (FITC filter). 

The main objective of the method development and validation studies was to determine a 

hybridization temperature (TH) that would allow for successful hybridization of both probes and 

to verify that each probe was hybridizing to the correct organisms at that temperature. The 

objective for each probe combination was to prove that the two probes could be used 

simultaneously (sandwiched) at a selected TH and maintain selectivity. 

5.1.3.1 Probe Combination Eub 338 and Clost I. 

The positive controls for Clost I probe were C. alginoliticum and C. sordelli, i.e. the probe 

should bind to these organisms, fluoresce green and be observable using the FITC filter on the 

microscope. The negative controls for Clost I probe were B. subtilis, D. multivorans, D. 

salexigens, E. coli, P. aeruginosa, and S. aureus i.e. the probe should not bind to these organisms 

and there should be no fluorescence observed through the FITC filter. The positive controls for 

Eub 338 probe were B. subtilis, C. alginoliticum, C. sordelli, D. multivorans, D. salexigens, E. 

coli, P. aeruginosa, and S. aureus which should be bound by the probes and thus be observable 

as red fluorescence through the TRITC filter. The negative controls for Eub 338 were run later 

(see 5.1.3.3) and gave the expected results. 

For the combination of Clost I and Eub 338 probes, samples were hybridized at hybridization 

temperatures from 53o

C to 57oC in increments of 0.5°C. The highest number of cells showing 

fluorescence was observed at TH = 53.5°

C. The probe combination of Clost I and Eub 338 

worked as expected with all the pure cultures used. Table 5.4 presents the matrix obtained when 

pure cultures were probed with the two probes simultaneously at TH = 53.5o

C. All of the cultures 

were Eubacteria and were detected as having the Eub 338 probe hybridized to them (TRITC 

filter) and only the Clostridia were detected with the Clost I probe (FITC filter). The DAPI also 

stained all of the cells. The culture C. alginoliticum was attached to the alginate in the medium 
70 

and was therefore, clumpy. The culture M. roseus was also clumpy. These cultures were not 

used in further experiments. 

Table 5.4 

Probe Combination Eub 338 and Clost I Validation (TH = 53.5o

C) 

Culture DAPI FITC TRITC 

B. subtilis + - + 

C. sordelli + + + 

C. alginoliticum + + + 

D. multivorans + - + 

D. salexigens + - + 

E. coli + - + 

M. roseus + - + 

P. aeruginosa + - + 

S. aureus + - + 

Figure 5.2 a presents photomicrographs of C. sordelli using phase contrast microscopy and a 40x 

objective after fixing and probing. Figure 5.2 b, c, and d present the same field at 40x objective 

through DAPI, FITC, and TRITC filters, respectively. C. sordelli should fluoresce through all 

the filters as shown in the figure. These photomicrographs were taken to represent the same 

observation area viewed through all the three filters consecutively. 

As an example of a negative control for this probe combination Figure 5.3a-d present 

photomicrographs of the S. aureus culture after fixing and probing. S. aureus is a positive 

control for DAPI and TRITC and is a negative control for FITC. It should fluoresce blue and red 

through DAPI and TRITC filters, respectively but should not fluoresce at all through the FITC 

filter as shown. 

5.1.3.2 Probe Combination Eub 338 and SRB 385. 

The positive controls for SRB 385 probe were D. multivorans and D. salexigens and should be 

observed as green fluorescence through the FITC filter. The negative controls for SRB 385 

probe were B. subtilis, C. sordelli, E. coli, P. aeruginosa, and S. aureus. Hybridization was 

attempted at 54o

C and 53.5oC. Good probing was observed at TH = 53.5oC. This probe 

combination worked as expected with all the pure cultures used. Table 5.5 presents the matrix of 

results obtained when the two probes were used in combination at TH = 53.5o

C. 

Figure 5.4a-d present photomicrographs of the D. multivorans culture magnified using the 100x 

objective with oil immersion and viewed using phase contrast as well as using the DAPI, FITC 

or TRITC filters. D. multivorans is a positive control for all the probes so it should fluoresce 

through all the filters as shown in the figures. These photomicrographs were taken to represent 

the same observation area viewed through all the three filters consecutively. 
71 

a. Phase Contrast b. DAPI filter 

c. FITC filter d. TRITC filter 

Figure 5.2. C. sordelli using Eub 338 and Clost I probes (40x objective). 

a. Phase contrast b. DAPI filter 

c. FITC filter d. TRITC filter 

Figure 5.3. S. aureus using Eub 338 and Clost I probes (100x objective). 
72 

Table 5.5 

Matrix Obtained for Probe Combination Eub 338 and SRB 385 (TH = 53.5oC) 

Culture DAPI FITC TRITC 

B. subtilis + - + 

C. sordelli + - + 

D. multivorans + + + 

D. salexigens + + + 

E. coli + - + 

P. aeruginosa + - + 

S. aureus + - + 

Figure 5.5 a-d presents photomicrographs of C. sordelli using a 100x oil objective viewed using 

phase contrast, as well as DAPI, FITC, and TRITC filters. C. sordelli is a positive control for 

DAPI and TRITC and is a negative control for FITC. It should fluoresce blue and red through 

DAPI and TRITC filters, respectively but should not fluoresce at all through the FITC filter as 

shown. These photomicrographs were taken to represent the same observation area viewed 

through all the three filters consecutively. 

a. Phase contrast b. DAPI filter 

c. FITC filter d. TRITC filter 

Figure 5.4. D. multivorans using Eub 338 and SRB 385 probes (100x objective). 
73 

a. Phase contrast b. DAPI filter 

c. FITC filter d. TRITC filter 

Figure 5.5. C. sordelli using Eub 338 and SRB 385 probes (100x objective). 

5.1.3.3 Probe Combination Eub 338 and Arch 915. 

The positive controls for the Arch 915 probe were H. salinarium and M. mazei and so should 

bind the probe and be observed as green fluorescence through the FITC filter. The negative 

controls for Arch 915 probe were B. subtilis, C. sordelli, D. multivorans, D. salexigens, E. coli, 

P. aeruginosa, and S. aureus and should not bind the probe nor be observed to have green 

fluorescence through the FITC filter. The positive controls for Eub 338 probe were B. subtilis, 

C. sordelli, D. multivorans, D. salexigens, E. coli, P. aeruginosa, and S. aureus. The negative 

controls for Eub 338 probes were H. salinarium and M. mazei. 

Initially this probe combination did not work as expected with H. salinarium because this culture 

requires a high salt concentration for cell integrity. To satisfy this, the salt concentration in the 

hybridization buffer was increased to 25 percent, which in turn interfered with the probing. The 

probe combination was then tried with M. mazei instead. Initially this also did not work as 

expected. 

The next step was to try various formamide percentages to make the cells more permeable to the 

probe. Formamide was added to the hybridization buffer starting from 10 percent increasing in 

increments of 5 percent. With the addition of 30 percent formamide in the hybridization buffer, 

the Arch 915 probe worked as expected. However, the Eub 338 probe worked best at a 

maximum of 10 percent formamide at the selected TH (53.5 °C) thus implying that the two 

probes cannot be sandwiched together. 
74 

The verification was then performed using the two probes separately. Table 5.6 presents the 

matrix of results obtained when the samples were probed with the two probes separately, Arch 

915 with 30 percent formamide and Eub 338 with no formamide, at TH = 53.5o

C. 

Table 5.6 

Matrix Obtained for Probe Combination Eub 338 and Arch 915 (TH = 53.5oC) 

Culture DAPI FITC TRITC 

B. subtilis + - + 

C. sordelli + - + 

D. multivorans + - + 

D. salexigens + - + 

E. coli + - + 

H. salinarium + + - 

M. mazei + + - 

P. aeruginosa + - + 

S. aureus + - + 

Figure 5.6a-d present photomicrographs of the M. mazei culture after fixing and probing viewed 

using a 100x oil objective through phase contrast, DAPI, FITC, or TRITC filters. M. mazei is a 

positive control for DAPI and FITC and it fluoresced the respective colors through these filters. 

M. mazei is a negative control for Eub 338 and did not fluoresce red in TRITC at any percent of 

formamide. 

Figure 5.7a-d present photomicrographs of C. sordelli after fixing and probing viewed using a 

100x oil objective and through phase contrast, DAPI, FITC, or TRITC filters. Since C. sordelli

is a positive control for DAPI and TRITC and is a negative control for FITC it fluoresces blue 

and red through DAPI and TRITC filters respectively, but does not fluoresce through the FITC 

filter as shown in the figure. These photomicrographs were taken to represent the same 

observation area viewed through all the three filters consecutively. 

Method validation experiments using pure cultures were repeated at the end of the research. In 

this case two probe combinations (Eub 338 and Clost Ι or Eub 338 and SRB 385) were verified 

as effective again. The results obtained for enumeration of the cells when probed with the probe 

combination of Eub 338 and Clost Ι are shown in Table 5.7. The positive control used for the 

Clost Ι probe was C. sordelli. The negative controls for the Clost Ι probe used were D. 

multivorans, E. coli, and P. aeruginosa. For the Eub 338 probe the positive controls that were 

used were C. sordelli D. multivorans, E. coli, and P. aeruginosa. The Clost Ι probe was working 

well as it did not hybridize to any of the negative controls. The results also suggest that the 

probes are accounting for approximately 50 percent of the total cells as detected by DAPI except 

in the case of D. multivorans in which Eub 338 only hybridized to 22 percent of the total cells. 

This is reasonable as the Eub 338 and Clost I probes are directed at rRNA which is only present 

in large amounts in active cells while DAPI will detect any cell that has DNA. The low counts 

for D. multivorans are most likely due to the clumpy nature of that organism. 
75 

a. Phase contrast b. DAPI filter 

c. FITC filter d. TRITC filter 

Figure 5.6. M. mazei using Eub 338 and Arch 915 probes (100x objective). 

a. Phase contrast b. DAPI filter 

c. FITC filter d. TRITC filter 

Figure 5.7. C. sordelli using Eub 338 and Arch 915 probes (100x objective). 
76 

Table 5.7 

Probe Combination of Clost Ι and Eub 338 

Culture DAPI 

(cells/ml) 

FITC 

(cells/ml)

TRITC 

(cells/ml) 

FITC/DAPI 

(%) 

TRITC/DAPI

(%) 

C. sordelli 1.89 x 105

 9 x 104 8.1 x 104 48 43 

D. multivorans 3.3 x 105

 - 7.2 x 104 22 

E. coli 2 x 105

 - 9.9 x 104 49.5 

P. aeruginosa 1.8 x 105

 - 9.9 x 104 55 

Table 5.8 shows the results obtained for the probe combination of Eub 338 and SRB 385. The 

positive control used for the SRB 385 probe was D. multivorans so it should fluoresce green 

when observed through the FITC filter. The negative controls used for the SRB 385 probe were

C. sordelli, S. aureus, E. coli and P. aeruginosa. The RNA probes detected about 50 percent of 

the organisms that DAPI detected, which is as expected even though attempts were made to fix 

the pure cultures in the most active state. 

Table 5.8 

Probe Combination of SRB 385 and Eub 338 

Culture 

DAPI 

(cells/ml) 

FITC 

(cells/ml) 

TRITC 

(cells/ml) 

FITC/DAPI 

(%) 

TRITC/DAPI 

(%) 

D. multivorans 2.3 x 105

 1.17 x 105 9.9 x 104 51 43 

E. coli 2.2 x 105

 - 9.9 x 104 45 

P. aeruginosa 1.94 x 105

 - 1.13 x 105 58 

S. aureus 2.12 x 105

 - 8.6 x 104 41 

C. sordelli 2.3 x 105

 - 1.1 x 105 48 

5.2 RESULTS FROM SAMPLE ANALYSIS

Samples from six locations were used for the majority of the research. The sediments chosen for 

study were MP299 (NF and FF), GC112 (NF and FF), and VK916 (NF and FF). The sediments 

were chosen because they encompassed the range of depth of the samples available. FISH and 

MPN analysis were performed on the original sediments collected from the Gulf of Mexico (time 

zero samples) and on samples from the anaerobic microcosms of Gulf sediments incubated with 

surrogate SBF (time final samples). 
77 

5.2.1 Time Zero Samples 

Both MPN and FISH analyses were performed on the original sediment samples as received 

(other than homogenization). These will be referred to as time zero samples to differentiate them 

from the samples processed after incubation in microcosms with spiked substrates or controls. 

5.2.1.1 Results of FISH Analysis 

Table 5.9 presents the DAPI, Archaebacterial, SRB, and Eubacterial counts obtained from the 

time zero enumerations of organisms in the sediments. Four of the six samples were processed 

in replicate to allow an estimation of the error of the procedure. The coefficient of variability for 

replication based on counting of three separate sub samples of the fixed sediment ranged from 14 

to 87 percent. The coefficient of variability for replication based on three separate counts of the 

same filter of one sub sample ranged from 15 to 23 percent. 

The numbers of SRB, Archaebacteria or Eubacteria detected in these samples are very high in 

relationship to the numbers of organisms detected with the DAPI probe. The numbers of SRB 

should be only a small fraction of the Eubacterial numbers, typically the percentages vary from 

0.7 to 11.7 percent (Ravenschlag et al. 2000). This suggests that the DAPI probe is 

underestimating the numbers of organisms in the sediment, most likely due to interference from 

sediment detritus.

Table 5.9 

Results of FISH Analysis on Time Zero Sediments (cells/g dry sediment) 

Sediment Location DAPI SRB Archaebacteria Eubacteria 

MP299 NF 1.1 x 108 1.6 x 108 2x108 4.1 x 108

 FF1 (2.9±0.4)x108 (1.6 ± 0.8) x 108 (1.2 ± 0.2) x108 (3.4 ±1.0) x 108

GC112 NF2

 3.5 x 108 (3.4 ± 0.5) x 108 2.8 x 108 (9.8 ± 4.2) x 108

 FF 8.8 x 107 2.7 x 108 2.1 x 108 9.1 x 108

VK916 NF1

 (6.7 ± 5.8) x 107 (1.7 ± 0.6) x 108 (1.6 ± 0.5) x108 (4 ± 0.7) x 108

 FF1

 (9.8 ± 4.7) x 107 (2.0 ± 0.6) x 108 (1.2 ± 0.4) x 108 (4.5 ± 1.6) x 108

1

Replication is based on counting of three separate sub samples of the fixed sediment. 

2

Replication is based on three separate counts of the same filter of one sub sample. 

5.2.1.2 Results of MPN Analysis 

MPN tubes were set up for the sediment samples at time zero containing media to support the 

growth of methanogens, hydrocarbon-utilizing aerobes, SRB, and general anaerobes. No 

methane was detected in the tubes used to enumerate methanogens even after two years of 

observation. The lowest dilution used for this measurement was 10-1. This could be because 

methanogenesis is a very slow process and the organisms are only present in low numbers in the 

sediment. The medium contained a redox indicator and even after the long incubation periods, it 

indicated that the tubes were still reduced enough for methanogens to grow if they were there in 
78 

sufficient numbers. The medium controls that were spiked with near shore sediment known to 

contain methanogens were positive for methane production. 

There was also a lack of growth of hydrocarbon-utilizing aerobes in the time zero samples. This 

is also unusual since one of the ingredients in the sheen screen test was tetradecene, which some 

microcosms proved was degraded by the sediments. An incubation period of 8-10 weeks was 

used for this enumeration, apparently it was too short. As is reported in Chapter 6 the lag time 

for tetradecene degradation was up to 22 weeks in some cases. Controls inoculated with near 

shore sediments did show the removal of sheen, which was the expected positive result. 

The method used to grow SRB and general anaerobes did produce positive results. Table 5.10 

presents the results for SRB and general anaerobes in all six sediments. The results for the time 

zero analysis of GC112 NF were lost. The results presented for general anaerobes in the MP299 

NF and FF samples are the detection limits based on the lowest dilution (10-1) and the amount of 

sediment that was used. No growth was observed for these two sets of tubes. 

 Table 5.10 

Results of Time Zero MPN Enumerations 

MPN/g dry sediment 

Sediment Location* SRB General 

Anaerobes 

MP299 NF 7.2 x 106 <7.22 x 102

 FF 9.6 x 105 <1 x 103

GC112 NF N/A N/A 

 FF 2.3 x 106

 1.1 x 107

VK916 NF 1.7 x 107 4.8 x 108

 FF 5 x 106

 2.3 x 108

5.2.1.3 Discussion of the Effect of Oil Exploration Activities on Sediment Microbial Populations 

The three possible effects that could be observed from exposure to cuttings coated with SBF 

would be: 1) a decrease in microbial numbers and diversity due to the addition of possible toxins 

or sediment texture changes; 2) an increase in microbial numbers due to the input of carbon from 

the SBF on the cuttings; or 3) no change in microbial numbers because the numbers of organisms 

in the sediment are already at a maximum carrying capacity. The third assumption comes from 

the fact the there are physical and chemical limitations to how many organisms can be actively 

growing in a sediment due to the volume of pore spaces and mass transport limitations that exist. 

Another explanation is that the death rate and growth rate are balanced, so no net overall change 

in number is measured. 

One of the reasons several methods of analysis were used during this study was to determine 

which measures or population being measured might be a discriminating factor. Two methods to 

measure SRB were selected because theory suggests that the SRB population would respond to 

the addition of carbon sources to the environment. 
79 

A comparison of the time zero results (Table 5.9, Table 5.10) for the near field samples with the 

far field samples should reveal if the exposure of the near field samples to the drilling cuttings 

coated with SBF had any effect. The numbers of organisms as determined by the MPN analysis 

was typically lower than the numbers of organisms as determined by the FISH analysis (Figure 

5.8). It is also apparent that the numbers of organisms did not vary with water depth, no matter 

the enumeration method. 

A statistical comparison of the data obtained for the time zero samples was performed to reveal if 

any significant differences in the results could be determined (Table 5.11). The MPN results for 

time zero are compared using the method of Cochran (1950). In this test, a Z value is computed 

for the data and if this is greater than 1.96, the results are significantly different. 

The statistical analyses showed that for MP299 there were significantly more SRB in the NF 

samples than in the FF samples. The comparison could not be made for the GC112 sediment 

because of missing data. The lack of difference in the SRB numbers for VK916 NF and FF 

sediments could be due to the relatively recent exposure of this site to the SBF (Table 3.1). The 

cuttings were discharged during November and December 2001 and the sediment collected 

approximately six months later. The exposure of the organisms at this site to 2,510 bbl of SBF 

contaminated cuttings over such a short period may have been of such volume and so recent that 

the population was overwhelmed and had not had time to react to the contamination in a 

measurable way. The results of the anaerobic biodegradation studies (Chapter 6) also support 

this hypothesis. 

Depth (m)

0 200 400 600 800 1000 1200

Microbial Numbers (per g dry sediment)

1e+1

1e+2

1e+3

1e+4

1e+5

1e+6

1e+7

1e+8

1e+9

SRB (MPN) 

SRB (FISH) 

General Anaerobes (MPN) 

Eubacteria (FISH)

Archaebacteria (FISH)

MP299

GC112

VK916

Figure 5.8. Microbial numbers in sediments at time zero. 
80 

Table 5.11 

Comparison of Microbial Numbers in NF and FF Sediment (Time =0) 

Sediment SRB 

(MPN) 

General 

Anaerobes 

(MPN) 

MP299 S nd 

GC112 n/a n/a 

VK916 nd nd 

S = significantly different results were determined (NF value was 

significantly greater than the FF value); nd = the results were not 

significantly different; n/a = no comparison could be made. 

5.2.2 Time Final Samples 

The time final samples for the various microcosms were taken after either the tetradecene or the 

ethyl oleate were degraded in the microcosms as determined by GC-FID analysis. For GC112 

NF the time final analyses were taken after tetradecene was removed (50 weeks). For GC112 FF 

the time final was also the time required for the removal of tetradecene (54 weeks). The time 

final for MP299 NF of 70 weeks was also the time needed to remove tetradecene. The time final 

for MP299 FF microcosms was the time to remove ethyl oleate (23 weeks) (and only the ethyl 

oleate and control microcosms were enumerated). The time to remove ethyl oleate (26 weeks) 

was also the factor used to determine the time final for VK916 FF sediment. Although 

tetradecene was removed in the last two sediments, MPN incubations were not initiated with 

tetradecene microcosm samples since there was not enough time for the incubations to be 

complete before the report was due. 

5.2.2.1 FISH Analyses 

The results of FISH analysis of the MP299 FF sediment sample after 23 weeks of incubation 

with ethyl oleate or incubation with no addition other than seawater are presented in Table 5.12. 

The table also presents a preliminary analysis of the numbers with the objective of determining 

whether they make sense within the generally accepted theory of the expected results using these 

techniques. It is typical to present the results from RNA probes as a percentage of the population 

that would be represented by the DAPI counts. It is also typical that no one population in an 

environmental sample would represent more than 12-20 percent of the total population unless 

there were extreme pressure on the organisms in the environment which would allow one 

population to dominate because they are the only ones that can survive. This was not expected to 

occur in these sediments because they are exposed to diverse carbon sources and electron 

acceptors. As pointed out in the discussion of Table 5.9 the FISH analysis of the original 

sediments showed that the numbers of SRB, Archaebacteria and Eubacteria were individually 

greater than the numbers of total organisms as measured by DAPI for most of the samples. 

Although the numbers of any one population were less than the whole population in the MP299 

FF sample after incubation, the numbers of the different groups of organisms still accounted for 
81 

too high a percentage of the DAPI numbers. The lowest fraction of any population as compared 

to the to the DAPI counts was 56 percent for Archaebacteria in the controls. This can be 

accounted for by masking of the DAPI counts from sediment particles and detritus. This would 

provide overall lower DAPI counts and an underestimation of the total population. 

It is also unusual that the SRB and Clostridia make up such a large percentage of the Eubacterial 

counts. These organisms are both Eubacteria but should not be such a large fraction of the total 

population. Adding the Clostridia and SRB counts accounts for more than 100 percent of the 

Eubacterial counts in both the control and ethyl oleate spiked microcosms. This again is 

improbable. This would suggest either the Eubacterial counts are low, the SRB or Clostridial 

counts are high, or a combination of both. 

Table 5.12 

Results of FISH Analysis of MP299 FF Time Final Sediments 

Probe Control 

(cells/g dry 

sediment x 

108) 

DAPI 

(%) 

Eub 338 

(%) 

Ethyl Oleate 

(cells/g dry 

sediment x 

108) 

DAPI 

(%) 

Eub 338 

(%) 

DAPI 1.6 ± 0.14 100 na 1.5 ±0.05 100 na 

Eubacteria 1.3 ± 0.3 81 100 1.1 ±0.01 73 100 

SRB 1.2 ± 0.3 75 92 1.3 ±0.067 87 118 

Clostridium 1.01 ± 0.034 63 78 0.9 ± 0.066 61 84 

Archaebacteria 0.9 ± 0.05 56 na 0.9 ± 0.035 98 na 

Eubacteria+ 

Archaebacteria 2.2 ± 0.35 138 na 2± 0.13 133 na 

na-analysis not applicable. 

Table 5.13 presents the results from the FISH analysis of the GC112 FF sediment after 54 weeks 

of incubation in the presence of ethyl oleate or incubation with only a seawater amendment 

(control). The Eubacterial counts of the microcosm spiked with ethyl oleate accounted for 25 

percent of the DAPI counts, which is reasonable. The Eubacteria are 50 percent of the total 

counts in the control microcosm, which is high. Again, the SRB and Clostridium are too large a 

percentage of the Eubacterial counts, they individually account for more than 100 percent of the 

Eubacterial counts. Since the method did not seem to be producing reliable results in the 

sediment samples no further FISH analyses were performed. 
82 

Table 5.13 

Results of FISH Analysis of GC112 FF Time Final Sediments 

Probe 

Control 

(cells/g dry 

sediment x 

108) 

DAPI 

(%) 

Eub 338

(%) 

Ethyl oleate 

(cells/g dry 

sediment x 

108) 

DAPI 

(%) 

Eub 338

(%) 

DAPI 7.8 ± 0.5 100 na 13 ± 1 100 na 

Eubacteria 3.9 ± 0.2 50 100 3.2 ± 0.3 25 100 

SRB 4.6 ± 0.14 59 118 2.5 ± 0.2 19 78 

Clostridium 4.9 ± 0.4 63 126 3.3 ± 0.2 25 103 

Archaebacteria 5.4 ± 0.14 69 na 3.5 ± 0.2 27 na 

Eubacteria+ 

Archaebacteria 9.3 ± 0.35 119 na 6.7 ± 0.52 127 na 

na-analysis not applicable 

5.2.2.2 MPN Analyses 

As discussed above for the time zero samples, there were no positive results from the attempts to 

enumerate methanogens and hydrocarbon-utilizing aerobes. There was growth in the tubes used 

to measure general anaerobes and SRB. The results are presented in Table 5.14. 

5.2.2.3 Discussion of the Effect of Anaerobic Incubations with Surrogate SBF on Microbial 

Populations 

The determination of the response of the organisms to incubation with the surrogate SBF was 

accomplished by comparing the microbial number in the control microcosms with those in the 

microcosms spiked with ethyl oleate or tetradecene. To avoid any interference in the 

comparisons from artificially high numbers at time zero due to the prior field exposure of the NF 

sediments to SBF coated cuttings, only the analysis of samples from FF sediments was used. 

There was not an MPN or FISH analysis of VK916 controls because the samples were all used 

for GC analyses during the incubations. 

The incubation of the sediment with ethyl oleate increased the number of SRB in MP299 FF 

sediment as determined by the MPN method (Table 5.15). Similar results were obtained for the 

GC112 FF sample. The incubation with ethyl oleate caused a significant increase in SRB 

numbers as determined by the MPN methods. The controls also showed an increase in SRB, 

which is possibly due to growth on natural organic material in the control sample. The SRB 

present in the VK916 FF sediment incubated with ethyl oleate did not increase in number. 
83 

Table 5.14 

Results Time Final MPN Enumerations 

Sample SRB 

(MPN/g dry sediment) 

General Anaerobes 

(MPN/g dry sediment) 

MP299 NF 

Ethyl oleate microcosm N/A N/A 

Tetradecene microcosm 3.24 x 106 5.8 x 108 

Control microcosm 4.7 x 106 5.8 x 108 

MP299 FF 

Ethyl oleate microcosm 1.2 x 108 1.7 x 107 

Control microcosm 4.8 x 105 5.4 x 107 

GC112 NF 

Ethyl oleate microcosm 2.0 x 108 1.1 x 109 

Tetradecene microcosm 8.5 x 107 5.3 x 107 

Control microcosm 4.6 x 107 3.3 x 109 

GC112 FF 

Ethyl oleate microcosm 4.6 x 108 1.0 x 106 

Control microcosm 3.7 x 108 1.9 x 105 

VK916 FF 

Ethyl oleate microcosm 3.6 x 106 6.3 x 106 

Table 5.15 

Statistical Comparison of Time Final FF MPN Results for SRB 

Sediment T Zero vs. 

Control 

T Zero vs. Ethyl 

Oleate 

Control vs. Ethyl 

Oleate 

Z = 0.8 Z = 3.33 Z = 6 MP299 FF SRB1 = SRB2 SRB1

 < SRB3 SRB2 < SRB3

VK916 FF Z = 0.4 

SRB1 = SRB3

Z=6 Z=6.3 Z=0.25 GC112 FF SRB1

 < SRB2 SRB1 < SRB3 SRB2 = SRB3

SRB1 = SRB at time zero, SRB2 = SRB in controls after incubation, SRB3

= SRB in ethyl oleate spiked microcosms after incubation. The Z-statistic 

is similar to the t-statistic with the population variance replacing the 

sample variance in the denominator of the calculation. For this data the Z 

at 95 percent confidence is 1.96. 

All three sediments showed a difference in numbers of general anaerobes between the time zero 

samples and the time final samples from the microcosms spiked with ethyl oleate (Table 5.16). 

The general anaerobe sample at time zero for MP299 was a non-detect, thus the time final 

numbers (both in the range of 107

) were significantly different. The GC112 FF samples spiked 
84 

with ethyl oleate showed an increase in general anaerobes over the time zero samples, while the 

controls showed a decrease in general anaerobes, which is difficult to reconcile with the increase 

in SRB measured in both samples. The numbers of general anaerobes also increased in the 

VK916 FF ethyl oleate spiked sediments over those at time zero, indicating that the general 

anaerobe measure may be a discriminatory measure. 

Table 5.16 

Statistical Comparison of Time Final FF MPN Results for General Anaerobes 

Sediment T Zero vs. 

Control 

T Zero vs. 

Ethyl Oleate 

Control vs. 

Ethyl oleate 

MP299 FF Z = 13 

GA1 < GA2

Z = 12 

GA1 < GA3

Z = 1.4 

GA2 = GA3

VK916 FF Z = 4.3 

GA1 < GA3

GC112 FF Z = 5 

GA1 > GA2

Z = 2.8 

GA1 > GA3

Z = 2 

GA2 < GA3

GA1 = general anaerobes at time zero, GA2 = general anaerobes in controls after 

incubation, GA3

 = general anaerobes in ethyl oleate spiked microcosms after 

incubation. 

5.3 CONCLUSIONS FROM MICROECOLOGY STUDIES

Straightforward conclusions can be drawn concerning the applicability of the methods used to 

these types of environmental samples, but conclusions as to the meaning of the results from the 

samples themselves are only preliminary and should be verified by further testing and repetition. 

A summary of the results during method development is presented in Table 5.17. 

The most obvious conclusion concerning the methods used is that the use of the FISH technique 

and phylogenetic probes is not recommended for these sediments. Although many others have 

used FISH successfully in marine sediments, these were all sandy sediments and did not present 

the problems associated with the sediments from the Gulf of Mexico, which had very little sand 

and up to 74 percent clay (Table 3.2). 

No methanogens or aerobic hydrocarbon degraders were detected in this study. The presence of 

SRB and general anaerobes was detected. The only possible microbial response to the possible 

exposure of sediment to SBF and the incubation of sediment samples with surrogate SBF (ethyl 

oleate or tetradecene) is a possible increase in SRB (as measured by MPN) to approximately 108

cells/g dry sediment. 
85 

Table 5.17 

Method Development Summation 

Target Population Method Conclusion Comment 

Total Bacteria FISH (DAPI) Not acceptable Sediment interference 

causes low numbers 

SRB (acetate 

utilizing) 

MPN Acceptable 

SRB (lactate 

metabolizing) 

MPN Acceptable Low numbers in 

verification test 

SRB FISH (SRB 385) Not acceptable Possibly high 

numbers 

General Anaerobes MPN Acceptable 

Methanogens MPN Acceptable 

Eubacteria FISH (EUB 338) Not acceptable Possibly high 

numbers 

Clostridia FISH (Clost I) Not acceptable Possibly high 

numbers 

Archaebacteria FISH (Arch 915) Not acceptable Possibly high 

numbers 
87 

CHAPTER 6 RESULTS OF BIODEGRADATION STUDIES 

6.1 METHOD DEVELOPMENT

6.1.1 Pressure Chamber Development 

The need to incubate the sediments spiked with surrogate SBF at the higher than atmospheric 

pressures the microorganisms would be exposed to in their natural environment required that the 

traditional incubation vessels for anaerobic testing (serum bottles) be changed to flexible walled 

vessels that would allow the transfer of pressure from the incubation vessels into the cultures. 

Plastic bags were considered as the new incubation vessels. To prove that the spiked compounds 

would not leak out of the bags, sediments from Galveston Bay that had been sterilized by 

autoclaving were spiked with ethyl oleate or tetradecene and placed in serum bottles or the heat 

seal bags and incubated under atmospheric (bottles) or pressurized to 790 psi. The 

concentrations of the compounds were monitored over seven months. The results indicate that 

there was very little is any leakage of ethyl oleate or tetradecene from the bags (Figure 6.1). 

Time (months)

01234567

Substrate concentrations (mg/kg dry sediment)

0

500

1000

1500

2000

2500

3000

Ethyl oleate - bottles

Ethyl oleate - bags

Tetredecene - bottles

Tetradecene - bags

Figure 6.1. Effect of incubation vessel on concentration of surrogate SBF in 

sterile sediments. 

To prove that a change in the incubation vessel would not affect the organisms in the sediments, 

inoculum from Galveston Bay shoreline sediment was set up in both bags and serum bottles. 

The bags were incubated in the pressure vessel (filled with water but not pressurized since these 

were near shore sediments). The serum bottles were incubated alongside the pressure vessel. 

Figure 6.2 presents the concentrations of sulfate in control and tetradecene-spiked sediments 

incubated in serum bottles or bags. The data points represent the average sulfate concentration 

of three replicate cultures. The error bars represent one standard deviation. The removal of 

sulfate in microcosms spiked with tetradecene and not in the controls indicates anaerobic 

microbial activity linked to tetradecene removal. The fact that the sulfate in the serum bottle 
88 

microcosms spiked with tetradecene was removed at the same rate as in the bag suggests that 

both incubation methods provide equivalent environments for the activity of marine tetradecene 

oxidizing, SRB. 

 Time (days)

0 10 20 30 40 50

Sulfate Concentration (mg/L pore water)

0

500

1000

1500

2000

2500 Bottles, Control Sediment 

Bags, Control Sediment

Bottles, Tetradecene-spiked sediment

Bags, Tetradecene-spiked sediment

Figure 6.2. Sulfate removal in incubation vessel tests. 

These results demonstrate that the closed bottle test as developed for the API and EPA can be 

converted for use in incubating sediments in plastic heat seal bags in a pressure chamber. The 

depletion of sulfate and surrogate SBF (ethyl oleate or tetradecene) are monitored to indicate 

culture activity. 

6.2 ANAEROBIC INCUBATIONS

For each sediment, the first experiment was designed to determine whether the organisms present 

in the sediment required high pressure for SBF degrading activity. Samples of near field 

sediment from each location were spiked with 2,000 mg ethyl oleate/g dry sediment or 2,000 mg 

tetradecene/g dry sediment and mixed with additional synthetic seawater to replenish the sulfate 

concentration, or just mixed with seawater (control). Samples of these were then incubated in 

serum bottles at room temperature or in bags pressurized to the pressure at the depth the 

sediment was exposed to when it was collected. 

In all of the figures presented below the symbols represent the average of the analysis of three 

samples; the error bars represent one standard deviation. The curves overlain on the data were 

generated using the first order with time delay equation that is presented later (Section 6.3). 

6.2.1 MP299 Site 

The MP299 samples represent the shallowest depth sampled (65 m). Sediment from this site (NF 

and FF) did not contain any detectable peaks in the GC-FID analysis of extracts (Table 3.1). The 
89 

NF sediment was exposed to drilling fluids from 1963-2000. The 966 bbl of either IO or LAO 

cuttings would have been discharged from the mid-1990’s to 2000. This would constitute 

chronic exposure to low levels of SBF. It is entirely possible that the site has recovered from 

exposure. The NF site still had elevated levels of SRB over those in the FF site. The NF sample 

had the highest clay content (74 percent) of all of the sediments tested and the highest 

phosphorous concentrations (Table 3.2). NF sediment samples were incubated both at 97 psi 

hydraulic pressure (in bags) and at atmospheric pressure (in bottles) in a cold room at 4°C. 

Replicate samples were sacrificed periodically and analyzed to determine the sulfate 

concentration in the pore water and the concentration of surrogate SBF in the sediment. Figure 

6.3 presents the results of the degradation of tetradecene and ethyl oleate at atmospheric pressure 

and 97 psi. As expected ethyl oleate was degraded more rapidly and with less of a lag than 

tetradecene. This is typical and has been observed in all of the studies using shoreline sediments. 

The figure also demonstrates that the organisms in the MP299 sediment did not perform any 

differently when they were incubated under pressure than they did at atmospheric pressure 

whether degrading ethyl oleate or tetradecene. 

Time (week)

0 10 20 30 40 50 60 70 80 90

Ethyl oleate or Tetradecene

(mg/kg dry sediment)

0

500

1000

1500

2000

2500

3000

3500

Ethyl oleate - atmospheric pressure

Tetradecene - atmospheric pressure

Ethyl Oleate - 97 psi

Tetradecene - 97 psi

Figure 6.3. Ethyl oleate and tetradecene concentrations in MP299 NF 

sediment incubated at 97 psi or atmospheric pressure. 

The concentrations of tetradecene and sulfate in tetradecene spiked microcosms are presented in 

Figure 6.4. Tetradecene degradation and sulfate removal began at very close to the same time 

and the two compounds were removed at very similar rates; strongly supporting the conclusion 

that sulfate was the terminal electron acceptor during tetradecene degradation. The lines 

overlaying the data were generated using first order kinetics delayed by a lag time. The 

determination of the lag time and the kinetic coefficients used for each dataset are explained 

below (Section 6.3). The link to sulfate depletion is even more apparent for ethyl oleate 

degradation (Figure 6.5). The only difference in the curves for sulfate and ethyl oleate 
90 

degradation is that the initial concentration of sulfate in the microcosms was greater than that of 

ethyl oleate. The control samples that were not spiked with substrate did not remove significant 

amounts of sulfate, again supporting the hypothesis that the degradation of the substrate was 

linked to sulfate reduction. 

Time (week)

0 10 20 30 40 50 60 70

Tetradecene (mg/kg dry sediment)

Sulfate (mg/L pore water)

0

500

1000

1500

2000

2500

3000

3500

Tetradecene - atmospheric

Sulfate with tetradecene - atmospheric

Tetradecene - 97 psi

Sulfate with tetradecene - 97 psi

Sulfate control - atmospheric 

Sulfate control - 97 psi

Figure 6.4. Tetradecene and sulfate concentrations in MP299 NF sediment 

incubated at 97 psi or atmospheric pressure. 

Time (week)

0 10 20 30 40 50 60

Ethyl oleate (mg/kg dry sediment)

Sulfate (mg/L pore water)

0

500

1000

1500

2000

2500

3000

3500

Ethyl oleate - atmospheric pressure

Sulfate with ethyl oleate - atmospheric

Ethyl oleate - 97 psi

Sulfate with ethyl oleate - 97 psi 

Sulfate control - atmospheric 

Sulfate control - 97 psi

Figure 6.5. Concentrations of sulfate and ethyl oleate in MP299 NF 

sediment incubated at 97 psi or atmospheric pressure. 

Incubations using the far field sediment were initiated as soon as the data suggested that pressure 

had no effect on substrate degradation. Samples were only incubated at atmospheric pressure. 

The original hypothesis was that since the far field samples were not previously exposed to SBF 
91 

they would degrade the substrates more slowly so sampling events were scheduled less often. 

Unexpectedly, this was not the case. New microcosms were set up and sampled more frequently. 

The data for the removal of ethyl oleate and tetradecene as well as the sulfate in these 

microcosms is presented in Figure 6.6. Lag times were observed before both ethyl oleate and 

tetradecene were degraded. Ethyl oleate was again removed sooner than the tetradecene, mostly 

due to a much shorter lag time (6 weeks). The link between ethyl oleate degradation and sulfate 

removal is again apparent. Tetradecene degradation began after a long lag period but then 

proceeded at a rapid rate. Sulfate removal lagged behind tetradecene degradation. Sulfate was 

not removed in controls that were not spiked with surrogate SBF. 

Time (week)

0 5 10 15 20 25 30

Sulfate (mg/L) 

 Ethyl oleate (mg/kg dry sediment)

0

500

1000

1500

2000

2500

3000

3500

Tetradcecene (mg/kg dry sediment)

0

500

1000

1500

2000

Ethyl Oleate

Sulfate with ethyl oleate

Tetradecene

Sulfate with tetradecene

Sulfate control

Figure 6.6. Concentrations of sulfate, ethyl oleate, and tetradecene in MP299 FF 

sediment incubated at atmospheric pressure. 

6.2.2 GC112 Site 

The GC112 sediment was obtained from a depth of 535 m. GC-FID analysis of sediment 

extracts showed peaks with retention times similar to commercially available SBF and thus this 

sediment was still impacted from drilling operations. Although the last discharge of cuttings was 

in 1997, over 5,000 bbl of cuttings were discharged and the site has not recovered yet. 

Incubations of the near field sediment at atmospheric pressure and at 790 psi were conducted. 

The concentrations of tetradecene and ethyl oleate in the extracts of samples sacrificed during the 

incubations are presented in Figure 6.7. There was no discernable lag time before ethyl oleate 

degradation began and only a very short lag time before tetradecene degradation began. Ethyl 

oleate was degraded at a faster rate than tetradecene was. There was no significant difference in 

the results from incubations at atmospheric pressure to those at 790 psi. Organisms in these 

sediments did not require pressure to metabolize the substrates. 
92 

Time (weeks)

0 10 20 30 40 50 60 70 80

Ethyl oleate or Tetradecene

(mg/kg dry sediment)

0

500

1000

1500

2000

2500

Ethyl oleate - atmospheric

Tetradecene - atmospheric

Ethyl Oleate - 790psi

Tetradecene - 790psi

Figure 6.7. Ethyl Oleate and tetradecene concentrations in GC112 NF sediment 

incubated at 790 psi or atmospheric pressure. 

The dependence of substrate degradation on sulfate is presented in Figure 6.8 and Figure 6.9. As 

the sulfate is used up (around 37 weeks) the tetradecene degradation slows down, possibly 

stopping altogether (Figure 6.8). The control samples that were not spiked with surrogate SBF 

removed some sulfate, probably due to the metabolism of the SBF present in the sediment. The 

ethyl oleate and sulfate were exhausted at the same time (Figure 6.9). 

As soon as it was determined that samples could be incubated at atmospheric pressure, the far 

field incubations were started using only atmospheric incubations. As shown in Figure 6.10 the 

ethyl oleate was degraded without any observable lag and this was accompanied by a depletion 

of sulfate from the microcosms. The degradation of tetradecene occurred after a short lag, and 

proceeded at a similar rate to that observed for ethyl oleate removal. The sulfate was only slowly 

removed in the microcosms spiked with tetradecene, and sulfate removal did not continue after 

the tetradecene was removed, and since the sulfate in the tetradecene spiked microcosms is very 

similar in concentration to that in the control microcosms it is possible that sulfate was not used 

as an electron acceptor for tetradecene in this sediment. The sediment was uncontaminated and 

aerobic in nature. The sediment appeared a creamy brown, rather than the grey black of the NF 

sediments. It is possible that the electron acceptor used in these microcosms was oxygen. 
93 

Time (weeks)

0 10 20 30 40 50 60 70 80

Tetradecene concentration (mg/kg dry sediment)

Sulfate concentration (mg/L pore water)

0

500

1000

1500

2000

2500

3000

3500

Tetradecene - atmospheric

Sulfate with tetradecene - atmospheric

Sulfate with tetradecene - 790 psi

Sulfate control - atmospheric

Sulfate control - 790 psi

Tetradecene 790 psi

Figure 6.8. Tetradecene and sulfate concentrations in GC112 NF sediment incubated 

at 790 psi or atmospheric pressure. 

Time (weeks)

0 10 20 30 40 50 60 70 80

Ethyl oleate (mg/kg dry sediment)

Sulfate (mg/L pore water)

0

500

1000

1500

2000

2500

3000

3500

Sulfate control - atmospheric

Sulfate control - 790 psi

Ethyl oleate - atmospheric

Sulfate with ethyl oleate - atmospheric

Ethyl oleate - 790 psi

Sulfate with ethyl oleate - 790 psi

Figure 6.9. Ethyl Oleate and sulfate concentrations in GC112 NF sediment incubated 

at 790 psi or atmospheric pressure. 
94 

Time (week)

0 10 20 30 40 50 60 70 80

Ethyl oleate or Tetradecene (mg/kg dry sediment)

Sulfate (mg/L pore water)

0

500

1000

1500

2000

2500

3000

3500

Ethyl oleate

Sulfate with ethyl oleate

Tetradecene

Sulfate with Tetradecene

Sulfate in Controls

Figure 6.10. Concentrations of sulfate, ethyl oleate, and tetradecene in GC112 FF 

sediment incubated at atmospheric pressure. 

6.2.3 VK916 Site 

The sediment from VK916 represents the deepest site (1135 m) that was sampled for this study. 

A GC-FID analysis of extracts of the near field samples revealed peaks at retention times similar 

to commercial SBF, indicating the sediment was impacted by drilling operations (Table 3.1). 

Sediment samples spiked with tetradecene, ethyl oleate, or unspiked controls were incubated at 

1700 psi. The initial sulfate concentration in the microcosms set up with near field sediment was 

much lower than expected (Figure 6.11), even though excess sulfate was added into the sediment 

with seawater. This was the second incubation of this sediment to show this. In the initial 

incubation that was set up with this sediment, the sulfate was depleted so quickly it was gone by 

the first sampling. In the second incubation, sulfate was also removed very quickly and within 

12 weeks it was depleted in the ethyl oleate spiked samples. The sulfate controls also showed 

low initial concentrations of sulfate and evidence of sulfate depletion. This is not surprising 

because of the high concentrations of SBF in this sediment (Table 3.1). Fewer controls were set 

up for this incubation since it was a second incubation and there was not sufficient sediment, so 

there were no control samples after 12 weeks of incubation. 

The ethyl oleate spike in this sample was measured to be almost three times the intended 

concentration of 2000 mg/Kg dry sediment. This could be due to analytical interference from 

SBF in the sediment. Ethyl oleate was initially degraded rapidly in this sediment, but after 12 

weeks ethyl oleate degradation slowed. This occurred at the same time that the sulfate was 

depleted from the sediment, indicating that the rapid ethyl oleate depletion rate was coupled to 

sulfate metabolism. 
95 

Tetradecene was not removed in this incubation of VK916 NF sediment even though 

tetradecene depletion was apparent during the first few sampling periods of the initial incubation. 

The sulfate was also not removed until after 20 weeks in the microcosms spiked with tetradecene 

but then at a very rapid rate (Figure 6.11). This suggests that the addition of tetradecene 

inhibited the sulfate reducers in some way, and that when they recovered there was a lot of easily 

degraded material for them to use, thus the rapid degradation. This sediment showed the highest 

contamination of SBF and undoubtedly, this had an affect on how the sediment behaved in the 

test. 

The VK916 FF sediment was also used to inoculate microcosms spiked with ethyl oleate, 

tetradecene, or controls and incubated at 1700 psi. This sediment contained the usual 

concentration of sulfate initially. The ethyl oleate and sulfate were removed simultaneously; 

again, sulfate appears to be the electron acceptor for the degradation of ethyl oleate. 

The results for tetradecene analysis in this sediment are the least reproducible of any results in 

this study. The dotted line is a best approximation of the possible curve for tetradecene 

degradation extrapolated from these data. There are two data points that are not well represented 

by the line. It is also interesting that sulfate was not degraded in the microcosms that were 

spiked with tetradecene even though tetradecene was removed in these microcosms. 

Time (weeks)

0 5 10 15 20 25 30

Ethyl Oleate (mg/kg dry sediment)

0

2000

4000

6000

8000

Tetradecene (mg/kg dry sediment)

Sulfate (mg/L pore water)

0

500

1000

1500

2000

2500

3000 Ethyl oleate

Sulfate with ethyl oleate

Tetradecene

Sulfate with tetradecene

Sulfate control

Figure 6.11. Concentration of sulfate, ethyl oleate, and tetradecene in VK916 NF 

sediment microcosms incubated at 1700 psi. 
96 

Time (weeks)

0 5 10 15 20 25 30 35 40 45 50

Ethyl oleate or Tetradecene (mg/kg dry sediment)

Sulfate (mg/L pore water)

0

500

1000

1500

2000

2500

3000

3500

Ethyl oleate

Sulfate with Ethyl oleate

Tetradecene

Sulfate with Tetradecene

Sulfate in Control

Figure 6.12. Concentrations of sulfate, ethyl oleate, and tetradecene in VK916 FF 

sediment microcosms incubated at 1700 psi. 

6.3 INTERPRETATION OF ANAEROBIC INCUBATION DATA

6.3.1 Determination of the Decay Coefficient from Anaerobic Degradation 

The major objectives of performing the anaerobic incubations were to provide direct evidence 

that organisms present in Gulf of Mexico sediments were capable of metabolizing SBF and to 

determine the kinetic coefficients that describe this degradation mathematically. The first 

objective was accomplished and as described above each of the sediments contained organisms 

that were capable of degrading ethyl oleate and tetradecene. The second objective is achieved by 

a more in depth analysis of the data. 

The rate of change in substrate concentration in the microcosms spiked with ethyl oleate or 

tetradecene shown in Figures 6.3 to 6.12 was observed to follow first order kinetics after a period 

of initial adaptation (lag phase). First order kinetics suggest that the rate of change in substrate 

concentration was dependant on the substrate concentration itself. The equation describing first 

order kinetics describes the rate of change in terms of the concentration and a kinetic coefficient 

or k as shown in Equation 6.1. There is no currently accepted method of predicting the lag time 

before microbial degradation begins. 

kC

dt

dC = Equation 6.1

Where C is the concentration of the substrate, k is the kinetic coefficient and t is time. 
97 

A rigorous approach was taken to determine the value of the coefficient k from the anaerobic 

incubations. The determination of k depends quite heavily on the determination of the end of the 

lag time before substrate degradation begins, and on the determination of a stopping point of 

degradation. Initially the data points in the first-order decay region of the curve (i.e. after any lag 

time was complete) were linearized to generate a system of linear equations. The decay 

coefficients were then estimated by finding the least squares solutions to this system of linear 

equations. The estimated decay coefficients were then used as parameters in a nonlinear system 

(which included both lag and decay phases) to determine the exact coefficient value in an 

iterative manner. The determination of the lag time was initially performed by insinuating the 

decay curve over the data and determining the time point at which the curve intersected the 

initial concentration. Later a mathematical expression was developed from the theory of 

microbial growth and substrate degradation. 

A summary of the degradation kinetics as determined from the experimental data for ethyl oleate 

degradation is presented in Table 6.1. Statistical analyses were performed to determine if the 

predicted exposure of the samples (i.e. near field vs. far field) had an effect, and the results were 

not different at the 95 percent confidence limit. When the data were organized based on whether 

contamination was detected in the sediment by extraction and GC analysis (i.e. MP299 NF was 

moved to the uncontaminated category) there was a significant difference in the k values. This 

supports the theory that pre exposure to SBF (even though the exposure was to IO’s not to esters) 

caused an increase in the microbial population and thus an increased degradation rate. 

Averaging the two sets of data reveal that the removal of ethyl oleate from a pre-exposed site 

could be described using a k value of -0.22 ± 0.02 week-1. For a model that assumes no preexposure, the more important data would be that the removal of the substrate from an 

uncontaminated site would occur with a k value of -0.11 ± 0.02 week-1. The lag time is another 

important factor in the fate model. Ethyl oleate degradation at most sites occurred with at most 

11 weeks lag. The detection of SBF in the sediment sample also had an effect on the lag time. 

The lag times for ethyl oleate degradation in sediments that contained SBF (GC112 and VK916 

NF) were significantly (p=0.05) shorter (average of 3 weeks) than those that did not contain 

detectable amounts of SBF (average of 4 weeks). 

The degradation of tetradecene by organisms in the sediment samples obtained was much more 

complicated to analyze. The degradation appeared to be different in the true far field samples 

from the near field samples (Table 6.2). The degradation of tetradecene did not appear to be 

linked to sulfate reduction in the far field samples, presumably due to the aerobic nature of the 

sediments. The FF sediments were all a cream to brown color, not the grey black that would be 

associated with anaerobic sediments. A t-test comparing tetradecene degradation results in the 

NF sediments revealed that there was no significant difference in the k values determined from 

the substrate decay curves. The average k value for the removal of tetradecene linked to sulfate 

reduction was -0.05 ± 0.01 week-1. 
98 

Table 6.1 

Kinetic Data for Ethyl Oleate Degradation 

Microcosm Substrate Co 

(mg/kg dry 

sediment) 

k 

(week-1) 

Correlation Tlag 

(week) 

GC 112 NF 790 psi ethyl oleate 2341 -0.23 1 2 

GC 112 NF atm. “ 2432 -0.2 .995 2 

VK 916 NF “ 7289 -0.22 .929 4 

Average -0.22 ± 0.02 2.7 ± 1

 

MP299 NF 97 psi ” 3117 -0.1 .982 2 

MP299 NF atm. “ 1960 -0.12 .998 7 

MP299 FF “ 2807 -0.13 .986 5 

GC 112 FF “ 3015 -0.07 .991 3 

VK 916 FF “ 2905 -0.13 .965 4 

Average -0.11 ±0.02 4.2 ± 2 

 

GC 112 NF 790 psi SO4

-2 with 3220 -0.25 .997 3.5 

GC 112 NF atm. ethyl oleate 3255 -0.3 .997 7 

VK 916 NF “ 1202 -0.22 .996 0 

Average -0.26 ± 0.04 3.5 ± 3.5 

 

MP299 NF 97 psi “ 3023 -0.05 .751 4 

MP299 NF atm. “ 3249 -0.08 .989 7 

MP299 FF “ 2769 -0.13 .997 5 

GC 112 FF “ 3195 -0.07 .994 8 

VK 916 FF “ 2713 -0.12 .984 11 

Average -0.09 ± 0.03 7 ± 2.7 

The lag times for tetradecene degradation were in the ranges of 4 to >30 weeks. The lag time for 

sulfate reduction was often longer than for tetradecene removal and sulfate reduction was slower 

than tetradecene removal. As mentioned earlier, it is also possible that tetradecene was 

inhibiting the SRB (and thus sulfate reduction) because in VK916 NF and VK916 FF sulfate 

removal either did not occur or occurred after a very long lag. In GC112 FF sulfate was never 

removed, even though tetradecene was. 
99 

Table 6.2 

Kinetic Data for Tetradecene Degradation 

Microcosm Substrate Co 

(mg/kg dry 

sediment) 

k 

(week-1) 

Correlation 

(r2) 

Tlag 

(week)

GC 112 NF 790 psi tetradecene 2338 -0.07 .983 4 

GC 112 NF atm. “ 2078 -0.05 .991 4 

VK 916 NF “ 2507 - - >30 

MP299 NF 97 psi “ 2250 -0.04 .829 26 

MP299 NF atm. “ 2124 -0.04 .958 28 

Average -0.05 ± 0.01 

 

MP299 FF “ 1776 -0.23* .971 14 

GC 112 FF “ 1750 -0.05* .984 10 

VK 916 FF “ 3059 -0.12* .768 12 

GC 112 NF 790 psi SO4

-2 with 3236 -0.07 .990 4 

GC 112 NF atm. tetradecene 3395 -0.07 .986 4 

VK 916 NF “ - - - - 

MP299 NF 97 psi “ 3019 -0.02 .754 25 

MP299 NF atm. “ 2900 -0.03 .986 23 

Average -0.05 ± 0.03 

 

MP299 FF “ 2950 -0.08 .799 18 

GC 112 FF “ 3227 - - 10 

VK 916 FF “ 3000 - - >30 

 

* These k values are most likely due to aerobic degradation and were not used to determine 

the k for sulfate reduction. 

6.4 AEROBIC BIODEGRADATION RESULTS

Although an aerobic biodegradation study was not part of the original objectives for this 

research, a limited study was performed to provide at least one data point for the aerobic terms in 

the fate model. The study was conducted using sediment from the MP299 far field site. The first 

order decay coefficient for the natural aerobic biodegradation of NOM was determined to be 

approximately kNOUR = -0.0018 h-1, or equivalently kNOUR = -0.3 week-1. The first order decay 

coefficient for the aerobic biodegradation of tetradecene was approximately kF, O2 = -0.0009 h-1, 

or equivalently k F, O2 = -0.15 week-1. 
101 

CHAPTER 7 FINAL MODEL DEVELOPMENT 

7.1 OVERVIEW OF THE FATE MODEL

As discussed in Chapter 4 the model was developed to predict the fate of SBF, O2, and SO4

-2

after discharge of cuttings to the sediment is completed. The main mechanism for removal of 

SBF from the sediment is through microbial degradation. In addition to biodegradation, the 

concentrations of the SBF, O2, and SO4

-2 are also affected by resuspension, bioturbation, 

sedimentation, compaction, and diffusion. Sediment mixing by organisms (bioturbation) and 

resuspension by bottom currents are two processes which dilute and disperse contaminants that 

initially settle on the seafloor. In the case of sediments affected by cuttings deposition, the 

results from the study by Continental Shelf Associates (2004) suggest that the redox potential 

discontinuity (RPD) was observed at less than 1 cm in most of the near-field sediments. This 

indicates that bioturbation does not play a significant role in impacted sediments since 

bioturbation only plays a role in aerobic sediments. In order to make the model conservative, the 

impact of bioturbation and resuspension in the sediments will be neglected. Sediment 

compaction is assumed to occur as the cuttings are deposited. Further compaction of the 

sediment after cuttings discharge is neglected in this model. The model as developed resolves 

only vertical gradients. 

The equations as presented in Chapter 4 reflected theoretically predicted Monod kinetics, which 

the data obtained and presented in Chapter 5 and Chapter 6 do not support. Attempts to fit the 

data to Monod kinetics using the data from Chapters 5 and 6 were unsuccessful. The expected 

changes in numbers of microorganisms that would occur if true growth were occurring were not 

measured. This could be because the techniques used to measure the microbial numbers were 

inadequate, or there was not a large amount of growth of organisms. 

The ability to fit the data for substrate degradation to a first order decay model indicates that 

there was not much growth after observable substrate degradation began. In a growing system, 

the rate of degradation would become faster and faster as the number of organisms increased. In 

this case the rate decreased with predictable first order kinetics, suggesting a population that is 

staying constant (at least once degradation starts) and is operating under diffusion limitations, 

thus first order kinetic are measured. 

The equations presented in Chapter 4 were rewritten as Equations 7.1 -7.3 to reflect first order 

kinetics as determined in Chapter 6. The term SC has been added as an input parameter to 

represent the stoichiometric coefficient that can be used to represent the stoichiometry of sulfate 

or oxygen usage due to substrate removal. In Chapter 4 this was presented as 2.6 g sulfate for 

each g of hexadecene, or 1.7 g O2 for each g of hexadecene consumed. The stoichiometry of 

sulfate usage for each substrate tested in this research (tetradecene or ethyl oleate) was 

determined by determining the stoichiometric coefficient needed to predict the sulfate 

concentrations in the samples from the ethyl oleate or tetradecene data. A summary of these 

coefficients is presented in Table 7.1. 
102 

Table 7.1 

Stoichiometric Coefficients for Sulfate Usage (g SO4/g substrate) 

Sediment Test Ethyl Oleate Correlation

(r2) 

Tetradecene Correlation

(r2) 

Predicted 4.4 4.9 

 

MP299 NF Atm. 1.381 0.994 1.33 (LA)3 0.991 

MP299 NF 97 psi 0.721 (LA)3 0.976 0.91 (LA)3 0.997 

MP299 FF 0.99 1.000 NL2 0.979 

 

GC112 NF Atm. 1.37 (LA)3 0.996 1.75 0.995 

GC112 NF 790 psi 1.38 (LA)3 0.999 1.38 1.000 

GC112 FF 1.06 (LA)3

 1.000 NL2 0.976 

 

VK916 NF1700 psi 0.1655

 (LA)3 1.000 NA4 NA4 

VK916 FF 1700 psi 0.923 (LA)3 0.999 NL2 NA4 

 

Mean (SD) 1.12 ± 0.26 1.34 ± 0.34 

Pooled Mean 1.2 ± 0.3 

1

 These coefficients gave good matches to initial curves but not the tails of the curves. 

2

 NL – it was determined that for these sediments sulfate reduction was not linked to 

tetradecene removal. 

3

 LA – the lag times for substrate and sulfate degradation were adjusted to be equal 

for this analyses. 

4

 NA – Not Available 

5

 not used in average 

The predicted stoichiometric coefficients were calculated assuming that all of the reactions are 

directed towards the electron acceptor and none towards growth. This is an overestimation of the 

actual requirement for electron acceptor. It was also apparent that the degradation of the electron 

acceptor sulfate could not be tied directly to substrate removal in every case. This suggests that 

the substrate, ethyl oleate or tetradecene, could be degraded to an intermediate, such as acetate, 

by a fermentative organism and that intermediate would then degraded by the SRB. Since the 

removal of sulfate could be modeled quite well using first order kinetics with regards to its own 

concentration (Table 6.1), it is likely that the sulfate was the limiting nutrient for sulfate 

reduction, and not the SBF, spiked substrate or intermediate present in these experiments. 

Equation 7.1, Equation 7.2, and Equation 7.3 are the stoichiometric equivalent forms of the three 

governing equations of the fate model. The advantage of using these equivalent forms is that the 

degradation of the electron acceptors can be controlled directly by the availability of SBF. As 

the concentration of SBF in the system is depleted, the reactive terms will also vanish, thus 

allowing the model to approximate the time taken for sulfate and oxygen replenishment by 
103 

diffusion. An additional oxygen utilization term was added to take into account the natural 

oxygen uptake rate in the sediments (NOUR). 









































+ 















+ − ⋅ ⋅ 















∂

∂ = ∂

∂

KO SO O

KO SO

Ks so S

S SC kF SO F

z

S

T

SO D

t

S

'

, 4

'

, 4

, 4

) , 4 ( 2

2

2

4

θ

Equation 7.1 

SC kF O F NOUR

t −































+ − ⋅ ⋅ 















∂

∂ = ∂∂

Ks,O O

O , 2 2zO2

2

T

O2 O D

θ

Equation 7.2





































−















 −

















∂

∂ = ∂∂

+ + KO SO + O

KO SO

S Ks SO

S

Ks O O

O k F k F

x

F

t

F

F O F SO '

4 ,

'

4 ,

4 , ,

, 2 , 4 2

2

2

T DF

θ

Equation 7.3

Where SC = the stoichiometric coefficient (g electron acceptor/g electron donor), kF,SO4 = the 

first order decay coefficient for fluid in the SRB zone (wk-1), kF,O2 is the first order decay 

coefficient in the oxygen zone (wk-1), NOUR = the natural oxygen uptake reactive term in the 

sediment (due to other organic compounds present in the sediment) and all other symbols have 

been defined previously. 

7.2 NUMERICAL SOLUTION FOR THE FATE MODEL

Due to the mathematical complexities involved in solving Equation 7.1, Equation 7.2, and 

Equation 7.3 simultaneously, a closed-form analytical solution was beyond the scope of this 

research. The solution method used was an explicit, forward-in-time, finite-difference 

approximation to the system of differential equations (Lapidus & Pinder, 1982). This is 

relatively straightforward and can be done using spreadsheet applications. The discretized forms 

of the partial equations of the model at time interval n and n + 1 are presented in Equation 7.4, 

Equation 7.5, and Equation 7.6. 









































− ⋅ ∆

− + = ⋅ ∆

−

+ +

+ − +

n

i KO SO O

KO SO

n

i

S KS SO

n

i

S n F i

n

i

n

i

n

i

S

n

i ni SC k F z

S S S

D

t

S S

, 4

, 4

, 4

2

1 1

1

( )

2 Equation 7.4

n NOUR i n

i

n F i

n

i

n

i

n

i

O

n

i

n

i k O

O

SC k F z

O O O

D

t

O O

Ks O

Ks O −















 − ∆

− + = ⋅ ∆

−

+

+ − +

,

,

2

1 1

1

( )

2 Equation 7.5

























 + 





















+

−

























+

−

∆

− − + + = ⋅ ∆

− +

n

i KO SO O

KO SO

n

i S K S SO

n

i S n

i kF SO F n

i K S O O

n

i O n

i kF O F

z

n

i F n

i F n

i F

DF t

n

i F ni F

'

4 ,

'

4 ,

, 4

, 4

,

, 2 2 ( )

1 2 1

1 Equation 7.6

The solutions to equations 7.4-7.6 were developed as Equation 7.7, Equation 7.8, and Equation 

7.9 were written into a VBA module within an Excel Workbook. 
104 









































= ⋅ + − ⋅ + ⋅ − ∆ ⋅ ⋅ ⋅

+ +

+ −

+

n

i KO SO O

KO SO

n

i

S KS SO

n

i

S n

F i

n

i

n

i

n

i

n Si S S S t SC k F

, 4

, 4

, 4

( 1 2 ) . 1 1

1 λ λ λ

Equation 7.7















 = ⋅ + − − ∆ ⋅ ⋅ + ⋅ − ∆ ⋅ ⋅ ⋅ + + −

+

n

i

n F i

n

i

n NOUR i

n

i

n

i O

O O t k O O t SC k F

Ks O

Ks O

,

, (1 2. ) . 1 1

1 λ λ λ Equation 7.8

n

i F n

i F n

i KO SO O

KO SO

n

i S K S SO

n

i S

kF SO n

i K S O O

n

i O

t k F O n

i F n

i F 1 ) '

4 ,

'

4 ,

, 4

, 4

,

, 2 (1 2. 1

1

− ⋅ + ⋅

















































 + 





















+

−

























+

+ − − ∆ ⋅ + = ⋅ + λ λ λ

Equation 7.9

Where: 2 ( z)

t D

∆

∆ λ =

The VBA model input section is presented in Figure 7.1. The initial and boundary conditions 

were simplified from those used in Chapter 4. When the program is executed the concentrations 

of oxygen, sulfate, and SBF are calculated for each time and each depth and these are used to 

populate three output result matrixes, (SBF, sulfate and oxygen concentrations) which are used 

to create graphic output. 

7.3 EXPLANATION OF MODEL INPUT

All of the model input parameters are contained within the input table (Figure 7.1) and can be 

changed depending on the scenario modeled. The summary below explains the parameters and 

the effects of changing those parameters in a sensitivity analysis. The results of the sensitivity 

analysis are not presented, but section 7.4 provides example model output designed to show the 

effectiveness of the specific parts of the model. 

7.3.1 Initial and Boundary Conditions 

7.3.1.1 Depth of the Saturated Layer 

The depth of the saturated layer parameter establishes the extent of contamination of sediment 

with SBF, oxygen or sulfate. The SBF saturation was initially set to 30 cm to allow visualization 

of a large layer of sulfate degradation results. If the depth of the contaminated layer is set to a 

lesser value (i.e. 10 cm) then the SBF is removed from all layers of the sediment more rapidly. 

The input for the depth of saturated layer of sulfate and oxygen are dependant on the space step 

chosen. The two values must be equal. 
105 

INITIAL AND BOUNDARY CONDITIONS

SBF O2 SO4

Depth of Saturated Layer L = cm 30 2 2

CONCENTRATION (mg/Kg)

Initial Condition t = 0 2500 6.8 2688

Boundary Conditions Top z = 0 0 6.8 2688

Bottom z = L 0 0 2688

MODEL PARAMETERS SBF O2 SO4 NOUR

Diffussivity Coefficient D = cm2/d 0 0.955 0.522 0.955

Aerobic Anaerobic

Decay Coefficient k = week-1 0.15 0.12 0.30 0.15

K o,so4 K s,o K s,so4

Half-saturation Constant KS = mg/Kg 0.256 0.0192 156

Aerobic Anaerobic

Lag-Phase tLag = week 0 5

STEP SIZES Stoichiometric Coefficients

Time Steps ∆t = week 0.50 SO4:SBF 1.2

Space Steps ∆z = cm 2.00 O2:SBF 1.2

Run time week 260

Sediment Porosity

ε θ

0.4 2.5

Figure 7.1. Model input table. 

7.3.1.2 Initial Concentration 

The VBA model has the ability to set upper and lower boundary conditions separate from the 

contaminated zone. This gives the ability to model diffusion of oxygen SBF and sulfate into the 

contaminated zone from both above and below. 

The boundary conditions set the initial SBF amount in the entire contaminated sediment zone to 

2500 mg /Kg dry sediment. Because the quality of the cuttings cleaning processes and the 

amount of cuttings discharged is variable from drill site to drill site, the initial SBF concentration 

can be very low or very high. A sensitivity run of the model indicated that there was enough 

sulfate in the sediment to support the anaerobic degradation of SBF to completion in 2 years 

when the initial concentration was 500 and 2000 mg/Kg. However, anaerobic degradation of 

4000 mg/Kg SBF slowed after the first year due to depletion of sulfate. The anaerobic 

degradation of SBF resumed when sufficient sulfate had diffused back into the sediment. The 

model predicted that the complete removal of 4000 mg/Kg of SBF in sediment would take 

approximately 5 years. The concentration of SBF in the boundaries to the contaminated zone 

was set to zero to reflect that the sediment above and below the cuttings zone is not contaminated 

with cuttings. 
106 

The initial concentration of oxygen was set to 6.8 mg/L pore water and it was present in only 

the upper boundary of the contaminated zone. Most analyses of both contaminated and 

uncontaminated sediments (e.g. Continental Shelf Associates 2004) showed that oxygen was 

only present in the first few centimeters of sediment, thus it is not expected to diffuse into the 

cuttings zone from below. 

The initial concentration of sulfate was set to 2688 mg/L pore water. Sulfate was set to be 

present in both the upper and lower boundaries. Sulfate is rarely limiting in natural sea water 

and should be able to diffuse into the cuttings layer from both the top and bottom boundaries. 

7.3.2 Diffusion and Decay Parameters 

7.3.2.1 SBF Diffusion Coefficient 

The SBF are typically assumed to have such low solubilities that the diffusion coefficient is 

effectively zero. The model assumes that the SBF are degraded in the bulk phase and do not 

have to diffuse into the aqueous phase before they can be degraded. The only results of diffusion 

would be to diffuse from the center of the contaminated zone out to the edges as the contaminant 

is removed from the edges. The ability to input an SBF diffusion parameter is retained in the 

model to allow versatility in the case where there is a need to model the fate of a diffusible SBF. 

7.3.2.2 Oxygen Diffusion Coefficient 

As discussed in Chapter 4, the diffusion coefficient was calculated to reflect the temperature and 

dynamic viscosity on the sea floor. As was reported in Chapter 4 changes in the O2 diffusion 

coefficient did not significantly change the overall prediction of SBF degradation. The VBA 

model predicted an improvement in the rate of oxygen diffusion back into the sediment after 

aerobic degradation was completed. This shows that the VBA model was somewhat sensitive to 

the oxygen diffusion coefficient but in the possible temperature ranges, there was no significant 

effect of oxygen diffusion coefficient on the overall biodegradation process. 

7.3.2.3 Sulfate Diffusion Coefficient 

The sulfate diffusion coefficient was also calculated according to changes in temperature. With 

an initial SBF concentration of 2500 mg/kg changes in the diffusion coefficient did not change 

the fate of SBF in the sediment significantly. Increasing the diffusion coefficient from 0.422, 

0.522 and 0.823 cm2

/day accelerated the rate of sulfate diffusion back into the sediment after the 

anaerobic degradation was completed. 

7.3.2.4 Aerobic Decay Coefficient 

The aerobic decay coefficient was determined by incubating one set of triplicate samples of 

MP299 FF sediment that had been spiked with tetradecene in a respirometer. The result was 

kF,O2 = 0.15. As discussed in Chapter 4 the model was not sensitive to this parameter because 

oxygen was limited to the first few centimeters of sediment. The sensitivity analysis in Chapter 
107 

4 was repeated and the results showed the oxygen profiles in the sediment after 2 years were 

similar for all cases, kF,O2 = 0.02, kF,O2 = 0.15 and kF,O2 = 0.80. 

The KS,O allows the ability to turn off the oxygen linked SBF degradation parameter when 

oxygen becomes limiting in the sediment pore water. This parameter was set to 0.0192 which 

was taken from the literature (Chakravarty 1975). 

7.3.2.5 Anaerobic Decay Coefficient 

The anaerobic decay coefficients were determined experimentally and reported in Chapter 6. 

They ranged from kF,SO4 = 0.04 to kF,SO4 = 0.22. For an arbitrary initial concentration of SBF, C0

= 2500 mg/Kg, the consumption of sulfate due to SBF degradation never lead to sulfate 

depletion. The faster the anaerobic degradation was completed, the faster the sulfate was 

replenished through diffusion. As a result, the sulfate profile in the sediment showed higher 

sulfate concentrations after 2 years for the higher anaerobic decay coefficients. 

The Ko,SO4 allows the ability to turn off the sulfate degradation parameter when oxygen is present 

in the sediment pore water. This parameter was set to 0.256 which was taken from the literature 

(Van Capellan and Wang 1995). 

The KS,SO4 allows the ability to turn off the sulfate linked SBF degradation parameter when 

sulfate becomes limiting in the sediment pore water. This parameter was set to 156 which was 

taken from the literature (Boudreau and Westrich 1984). 

7.3.2.6 NOUR Decay Coefficient 

The natural oxygen uptake rate (NOUR) was measured by incubating one set of triplicate 

samples of MP299 FF sediment in a respirometer and measuring the oxygen uptake rate. The 

result was a kNOUR = 0.3. Appling this value of the NOUR parameter in the model yielded 

similar oxygen profile to that measured in MP299 FF sediments during Sampling Cruise 1 

(Continental Shelf Associates 2004). 

7.3.2.7 Stoichiometric Coefficient and Lag Time 

The stoichiometric coefficient was explained in section 7.1. The value was set to 1.2 for both 

oxygen and sulfate. The experimentally determined lag time for anaerobic degradation varied 

widely. When the model was run using a lag time of 0, 10 and 30 weeks, the SBF removal 

profile was delayed but the curve shape once degradation started was not different. A lag time of 

5 weeks was used for most model runs. 

7.3.2.8 Step Sizes. 

The model solution is very sensitive to the step sizes. As mentioned above the space step must 

be equal to the depth of saturated layer for oxygen and sulfate. The model predictions become 

unstable if the time step ≤ 1/the highest decay rate used and ≤ 0.5*the (space step)2

/maximum 
108 

diffusion coefficient used. The run time selected relates to the time and space steps and the 

time available for computations. 

7.3.2.9 Porosity and Tortuosity of the Sediment 

The porosity term did not have as much effect on the model predictions in the VBA model. 

There was enough sulfate in the sediment to support the anaerobic degradation of 2500 mg/Kg 

SBF during the course of two years. The rate of sulfate replenishment in the sediment after SBF 

degradation was complete was faster as the porosity of the sediment increased (lower turtuosity). 

The rate of SBF degradation was similar in all cases since sulfate was not limited. 

7.4 VERIFICATION OF MODEL PERFORMANCE

Several scenarios were applied to the model to verify performance. Certain parameters were 

turned off to observe their effects on the model predictions. These include removing all 

degradation terms so the diffusion terms and natural oxygen uptake rate terms could be evaluated 

since these were new to the model. When each term was adjusted the model responded 

predictably, suggesting that the code is working as predicted. The following sections summarize 

the more important model responses. 

7.4.1 Simulation of the Natural Oxygen Profile 

The ability of the model to predict the natural oxygen profile in the sediment was evaluated by 

turning off all of the degradation kinetics as well as the sulfate diffusion terms. Thus the only 

modules of the model that were running were oxygen diffusion and natural oxygen uptake rate 

(NOUR). When the oxygen diffusion coefficient was set to 0.955 and the NOUR was turned off, 

the model predicted that oxygen would diffuse in to the sediment with time Figure 7.2a. This is 

what would be expected when no reactive terms are incorporated into the model. When the 

NOUR of 0.3 wk-1 obtained from a preliminary aerobic incubation of MP299 FF sediment were 

input to the model it was able to predict a profile very similar to that found by Continental Shelf 

Associates (2004) (Figure 7.2b). The model is able to predict a believable diffusion of oxygen 

and use of this with a natural oxygen uptake rate. 
109 

a 

0

2

4

6

8

0

10

20

30

40

50

60

5

10

15

20

25

30

Oxyg

e

n

m( g

L/ )

Time (week)

Depth (cm)

0 

2 

4 

6 

8 

b 

0

2

4

6

8

0

10

20

30

40

50

60

5

10

15

20

25

30

Oxyg

e

n

m( g

L/ )

Time (week)

Depth (cm)

0 

2 

4 

6 

8 

Figure 7.2. Oxygen profile with oxygen diffusion (D=0.955 cm2/sec) with a) no reactive 

terms and b) with NOUR (0.3 wk-1). 
110 

7.4.2 Simulation of Aerobic SBF Degradation 

To verify the aerobic degradation portions of the equations were functioning as expected the 

model was run with all parameters off except the aerobic degradation decay coefficient (0.15 wk1

) and with the aerobic parameters on including oxygen diffusion. The initial and upper 

boundary oxygen concentrations were set to 6.8 mg/L, the NOUR was set to 0.3 and the initial 

SBF concentration was 2500 mg/kg. When the diffusion term was left at zero (Figure 7.3a) the 

SBF profile shows that very little SBF is used when oxygen cannot diffuse into the sediment as 

expected. With the full aerobic degradation parameters (initial and upper boundary O2=6.8, O2

diffusion coefficient 0.955, an aerobic decay coefficient of 0.15, and an NOUR of 0.3) input into 

the model the SBF profile changes only slightly from when oxygen diffusion is not operative 

(Figure 7.3b). 

The predicted oxygen profile shows that the oxygen is completely removed from all depths of 

the sediment rapidly in the absence of diffusion Figure 7.4a. The typical diffusion is too slow to 

have a visible effect on SBF consumption. The oxygen profile is somewhat different when 

diffusion and degradation are both turned on. Slightly higher levels of oxygen are observed 

deeper into the sediment in Figure 7.4a than in Figure 7.4b. 

7.4.3 Simulation of Anaerobic Degradation 

To test the model’s ability to predict the anaerobic degradation of SBF all of the aerobic 

parameters were turned off, the sulfate was set to 2688 mg/L initially and at the top and bottom 

boundary layers. The anaerobic decay coefficient was set to 0.12 and the lag time was set to 5 

weeks. The anaerobic degradation of SBF removes the majority of the SBF present in the 

sediment at most depths because the amount of sulfate originally in the sediment supports the 

degradation of most of the SBF present (Figure 7.5a). When the diffusion of sulfate into the 

sediment from the top and bottom boundary layer is allowed, then even more SBF is removed, 

most noticeably the SBF in later times and the middle depths are different between Figure 7.5 a 

and b. 

The sulfate profile shows more marked differences when diffusion of sulfate is on or off (Figure 

7.6a and b). The sulfate concentrations are increasing with time and from the boundaries in, 

indicating the model is predicting that after the SBF is removed, the sulfate will diffuse back into 

the sediment as it is expected to. 
111 

a 

0

500

1000

1500

2000

2500

3000

10

20

30

40

50

60

0

2

4

6

8

10

SBF 

m(

g

Kg /

)

Time (wk)

Depth (cm)

0 

500 

1000 

1500 

2000 

2500 

3000 

b 

0

500

1000

1500

2000

2500

3000

10

20

30

40

50

60

0

2

4

6

8

10

SBF

m(

g

Kg /

)

Time (wk)

Depth (cm)

0 

500 

1000 

1500 

2000 

2500 

3000 

Figure 7.3. SBF profile when a) only aerobic decay (k=0.15) is active and b) when 

oxygen diffusion is added using a diffusion coefficient of 0.955. 
112 

a 

0

2

4

6

8

0

10

20

30

40

50

60

3

4

5

6

7

8

9

10

O

xygen (mg

L/ )

Time (week)

Depth (cm)

0 

2 

4 

6 

8 

b 

0

2

4

6

8

0

10

20

30

40

50

60

3

4

5

6

7

8

9

10

O

xygen (mg

L/ )

Time (week)

Depth (cm)

0 

2 

4 

6 

8 

Figure 7.4. Oxygen profile when a) only aerobic decay (k=0.15) is active and b) when 

oxygen diffusion is added using a diffusion coefficient of 0.955. 
113 

a 

0

500

1000

1500

2000

2500

3000

0 10

20

30

40

50

60

5 10 15 20 25 30

S

B

F

m( g/K

g)

Time (wk)

Depth (cm)

0 

500 

1000 

1500 

2000 

2500 

3000 

b 

0

500

1000

1500

2000

2500

3000

0 10

20

30

40

50

60

5 10 15 20 25 30

S

B

F

m( g/K

g)

Time (wk)

Depth (cm)

0 

500 

1000 

1500 

2000 

2500 

3000 

Figure 7.5. SBF profile with anaerobic decay of SBF occurs with a) no sulfate 

diffusion, and b) sulfate diffusion using a coefficient of 0.522. 
114 

a 

0

500

1000

1500

2000

2500

3000

0

10

20

30

40

50

60

5 10 15 20

25

30

S

ulfate

m( g

L/ )

Time (week)

Depth (cm)

0 

500 

1000 

1500 

2000 

2500 

3000 

b 

0

500

1000

1500

2000

2500

3000

0

10

20

30

40

50

60

5 10 15 20

25

30

S

ulfate

m( g

L/ )

Time (week)

Depth (cm)

0 

500 

1000 

1500 

2000 

2500 

3000 

Figure 7.6. Sulfate profile with a) anaerobic decay (k=0.12) only and b) anaerobic 

decay plus sulfate diffusion (D=0.522). 
115 

7.4.4 Simulation of Aerobic-Anaerobic Degradation with Diffusion of SO4 and O2

All of the model parameters were set to the experimentally determined or estimated values 

(Table 7.2) and the model was run to generate SBF, oxygen, and sulfate profiles. The output is 

presented graphically in Figure 7.7, and Figure 7.9 

Table 7.2 

Input Parameters Used for Full Model Run 

Parameter SBF O2 SO4 NOUR 

Depth 30 3 3 

Initial 2500 6.8 2688 

Top 0 6.8 2688 

Concentration 

Bottom 0 0 2688 

Diffusion Coefficient 0 0.955 0.522 

NA 

Decay Coefficient Aerobic Anaerobic 

0.15 0.12 

Lag Time 0 5 

0.3 

0

500

1000

1500

2000

2500

3000

0

20

40

60

5 10 15 20 25 30

S

B

F

m

(

g/K

g)

Time (wk)

Depth (cm)

0 

500 

1000 

1500 

2000 

2500 

3000 

Figure 7.7. Predicted SBF profile with all model parameters set. 
116 

0

2

4

6

8

0

10

20

30

40

50

60

5

10

15

20

25

30

O

xygen

m( g

L/ )

Time (week)

Depth (cm)

0 

2 

4 

6 

8 

Figure 7.8. Predicted oxygen profile with all model parameters set. 

0

500

1000

1500

2000

2500

3000

0

10

20

30

40

50

60

5 10 15 20 25 30

S

ulfat

e

m

( g/L)

Time (week)

Depth (cm)

0 

500 

1000 

1500 

2000 

2500 

3000 

Figure 7.9. Predicted sulfate profile with all model parameters set. 
117 

CHAPTER 8 CONCLUSIONS 

The literature review conducted as part of this research revealed that there are some initial 

findings concerning the anaerobic degradation of SBF and similar compounds under anaerobic 

(specifically sulfate reducing) conditions. The information available is enough to predict that the 

degradation of SBF could occur in deep anaerobic sediments, but the extent of degradation and 

the time required to achieve a significant degradation could not be predicted from the literature. 

An initial mathematical framework to model SBF fate in marine sediments was developed using 

existing microbial growth theory and with the input parameters obtained from a review of 

existing information from related articles and research. With these initial parameters, the model 

as developed in a spreadsheet solution performed well, in other words the predicted results 

compared reasonably with existing research and articles. A sensitivity analysis using assumed 

parameters revealed that when all other parameters were assumed to be in expectable ranges the 

biodegradation of the SBF would be controlled by sulfate reducing organisms. The predictions 

showed that unless diffusion of sulfate were impeded to a great extent sulfate would never 

become limiting, thus it would be the dominant electron acceptor present in the sediments. 

Aerobic organisms did contribute to the depletion of the SBF in the first few centimeters of 

sediment. 

Two techniques were used (growth based and molecular) to characterize the microbial 

populations and the examination of four nutritional types of organisms as well as four 

phylogenetic groups of organisms were performed. Straightforward conclusions can be drawn 

concerning the applicability of the methods used to these types of environmental samples, but 

conclusions as to the meaning of the results from the samples themselves are only preliminary 

and should be verified by further testing and repetition. 

The most obvious conclusion concerning the methods used is that the use of the FISH technique 

and phylogenetic probes is not recommended for these sediments. Although FISH has been 

successfully used by other researchers in sandy marine sediments, sediments from the Gulf of 

Mexico have little sand and up to 74 percent clay. It was not possible to successfully dislodge or 

extract cells from the Gulf of Mexico sediments by sonication, slow centrifugation, and 

supernatant removal, or dissolution of material in acid or base before fast centrifugation. The 

sediments had to be analyzed as a whole since too many organisms were present in each fraction 

in all of the attempts to separate organisms from the sediment particles. The use of DAPI as a 

general DNA stain on whole sediment samples resulted in a yellow fluorescence of the sediment 

particles, which masked the fluorescence of the DAPI stained organisms and caused an 

underestimation of the total microbial populations. 

The degradation of surrogate SBF tetradecene and ethyl oleate under conditions designed to 

mimic the floor of the Gulf of Mexico were examined. Sub-samples of NF and FF samples from 

three locations were incubated at 4°C at atmospheric pressure and at pressures similar to those 

they would experience at the depth of sampling. The results showed that the incubation pressure 

had no effect on the degradation of the substrates. The organisms in all of the sediments could 

degrade the ethyl oleate spiked into the sub samples in a reasonably short time. The degradation 
118 

of tetradecene typically required a longer lag period before degradation began and proceeded at 

a slower rate. 

A summary of the degradation kinetics as determined from the experimental data for ethyl oleate 

degradation revealed that there was a significant difference in the kinetic coefficients in 

sediments with a detectable pre-exposure to SBF. This supports the theory that pre-exposure to 

SBF (even though the exposure was to IO’s not to esters) caused an increase in the capable 

microbial population and thus an increased degradation rate. The removal of ethyl oleate from a 

contaminated site could be described using a first order k value of -0.22 ± 0.02 week-1. The 

removal of ethyl oleate from an uncontaminated site can be predicted using a k value of -0.11 ±

0.02 week-1. The lag time is another important factor in modeling the time required to remove a 

substrate from the sediment. Ethyl oleate degradation at most sites occurred with at most 11 

weeks lag. The presence of SBF in the sediment sample also had an effect on the lag time. The 

lag times for ethyl oleate degradation in sediments that contained SBF (GC112 and VK916 NF) 

were significantly (p=0.05) shorter (average of 3 weeks) than those that did not contain 

detectable amounts of SBF (average of 4 weeks). 

The degradation of tetradecene from the sediments could also be described using a first order 

kinetic model. The average k value for the removal of tetradecene linked to sulfate reduction 

was -0.05 ± 0.01 week-1. It appears that the rate of tetradecene removal was not linked to sulfate 

reduction in the far field sediments. The lag time for sulfate reduction was longer than for 

tetradecene removal and sulfate reduction was slower than tetradecene removal if sulfate was 

removed. It could be possible that tetradecene was inhibiting the SRB (and thus sulfate 

reduction) because in VK916 NF and VK916 FF sulfate removal either did not occur or occurred 

after a very long lag. 

The information obtained in the study was used to compile a final version of a visual basic 

spreadsheet based model. The model worked as predicted, in other words the predicted results 

compared reasonably with existing research and articles. 
119 

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