Souring and Corrosion in Light Oil Producing Reservoirs and in Pipelines Transporting Light Hydrocarbon

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2015-11-19 Souring and Corrosion in Light Oil Producing Reservoirs and in Pipelines Transporting Light Hydrocarbon

Menon, Priyesh

Menon, P. (2015). Souring and Corrosion in Light Oil Producing Reservoirs and in Pipelines Transporting Light Hydrocarbon (Unpublished master's thesis). University of Calgary, Calgary, AB. doi:10.11575/PRISM/27835 http://hdl.handle.net/11023/2644 master thesis

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UNIVERSITY OF CALGARY

Souring and Corrosion in Light Oil Producing Reservoirs and in Pipelines Transporting Light Hydrocarbon

Priyesh Menon

A THESIS

SUBMITTED TO THE FACULTY OF GRADUATE STUDIES

IN PARTIAL FULFILMENT OF THE REQUIREMENTS FOR THE

DEGREE OF MASTER OF SCIENCE

GRADUATE PROGRAM IN BIOLOGICAL SCIENCES

CALGARY, ALBERTA

NOVEMBER, 2015

Abstract

Microbial life can be hindered by the presence of light oil or low molecular weight hydrocarbons. The study focuses on how microorganisms survive in a diluent transporting pipeline, on souring in a field producing light oil, and on inhibition of acetate-utilizing sulfate reducing bacteria (SRB) by light oil. The study of pigging samples from a diluent transporting pipeline showed that microorganisms were able to survive in encrusted nodules where they were protected from the toxic and harsh environment and would contribute to corrosion. The study of water samples from light oil field showed that biocide, tetrakis hydroxymethyl phosphonium sulphate (THPS) could be the source of sulfate in some of these facility waters.

Souring by acetate-utilizing SRB was inhibited by the presence of light oil, so in light oil producing operations once oil is removed from the water with sulfate there is a potential of souring and microbially-influenced corrosion.

Acknowledgement

I would like to express my deepest gratitude to my supervisor, Dr. Gerrit Voordouw who gave me an opportunity to join his research team and learn from the immense knowledge that he has. He gave me great research project to work on, he not only guided me through my research, but also been a great support in my personal life. I will always miss his guidance, his stories and his jokes (man of superb one liner). I would also like to thank my committee members, Dr. Lisa Gieg and Dr. Casey Hubert for their support and suggestions. I would also like to thank Dr. Thomas Jack for his expert advice on corrosion aspects.

I would like to thank members of Voordouw and Gieg labs. Special thanks to Johanna

Voordouw for helping me out with my sample and for being the lab mother. Special thanks to

Yin Shen for helping me with MPNs and reagent that I borrow and never return. Special thanks to Rhonda Clark for helping me with everything. Special thanks to Dr. Daniel Park for his effort in starting up my research project.

Finally, I wish to thank my parent for their support, love and faith, they were always there. I would like to thank my brother, Parag, friends; Navreet, Roshan, Tijan, Annie, Akshay,

Subu and others who stood by me and helped to finish this wonderful journey.

This work was funded by NSERC, Alberta innovates, University of Calgary and all our industrial sponsors. The samples were provided by Oil search Ltd., Baker Hughes and Enbridge

Inc.

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Table of Contents

Abstract …………………………………………………………………………………………………………………………………… ii Acknowledgement ………………………………………………………………………………………………………………….. iii Table of Contents ……………………………………………………………………………………………………………………. iv List of Tables …………………………………………………………………………………………………………………………. viii List of Figures ………………………….………………………………………………………………………………………………. x List of Symbols, Abbreviations and Nomenclature …………………………………………………………………. xii

CHAPTER ONE: INTRODUCTION ……………………………………………………………………………………………… 1

1.1 Alberta Oil & Gas Industry and Light oil reserves ……………………………………………………………….. 1 1.2 Pipelines an important mode of oil transportation ……………………………………………………………. 2 1.3 Corrosion in oil transporting pipeline ………………………………………………………………………………… 3 1.4 Microbially influenced corrosion ……………………………………………………………………………………….. 3 1.5 Light oil and Diluent (composition) ……………………………………………………………………………………. 4 1.6 Light oil toxicity …………………………………………………………………………………………………………………. 7 1.7 Sulfate Reducing Bacteria (SRB) ……………………………………………………………………………………….… 8 1.8 Methanogens …………………………………………………………………………………………………………………… 10 1.9 Microbial life in light hydrocarbon transporting pipeline …………………………………………………. 11 1.10 Souring and Biocorrosion in light oil producing oil fields ……………………………………………. 12 1.11 Light oil toxicity on acetate utilizing SRB ……………………………………………………………………. 13 1.12 Objective ……………………………………………………………………………………………………………………. 14

CHAPTER TWO: METHODS AND METERIALS …………………………...... 16

2.1 Molecular methods …………………………………………………………………………………………………………. 16 2.1.1 DNA extraction ……………………………………………………………………………………………………….. 16 2.1.2 Modified skim milk DNA extraction …………………………………………………………………………. 17 2.1.3 Polymerase chain reaction (PCR) …………………………………………………………………………….. 17 2.2 Analytical methods ………………………………………………………………………………………………………….. 19 2.2.1 Sulfide Analysis ………………………………………………………………………………………………………… 19 2.2.2 Volatile fatty acid analysis ……………………………………………………………………………………….. 20 2.2.3 Inorganic anion analysis …………………………………………………………………………………………… 21 2.2.4 Ammonium ……………………………………………………………………………………………………………… 21 2.2.5 Methane analysis …………………………………………………………………………………………………….. 22 2.2.6 Light oil composition analysis (GCMS) ……………………………………………………………………… 23 2.2.7 pH and conductivity determination …………………………………………………………………………. 23 2.3 Microbial counts and most probable number ………………………………………………………………….. 24

2.4 Corrosion Analysis ……………………………………………………………………………………………………………. 24 2.4.1 Coupons and beads treatment ………………………………………………………………………………… 24 2.4.2 Weight loss method ………………………………………………………………………………………………… 25 2.4.3 Linear polarization resistance method …………………………………………………………………….. 26

CHAPTER THREE: MIC IN DILUENT TRANSPORTING PIPELINE ………………………………………………. 27

3.1 Introduction …………………………………………………………………………………………………………………….. 27 3.2 Materials and methods ……………………………………………………………………………………………………. 28 3.2.1 Field samples …………………………………………………………………………………………………………… 28 3.2.2 Sample handling ………………………………………………………………………………………………………. 29 3.2.3 Water chemistry ……………………………………………………………………………………………………… 29 3.2.4 Microbial counts ……………………………………………………………………………………………………… 31 3.2.5 Corrosion rate measurements ………………………………………………………………………………... 31 3.2.6 Methanogenesis ……………………………………………………………………………………………………… 31 3.2.7 Community analysis by pyrosequencing ………………………………………………………………….. 32 3.3. Results ……………………………………………………………………………………………………………………………. 32 3.3.1 Water chemistry ……………………………………………………………………………………………………… 32 3.3.2 Microbial counts ……………………………………………………………………………………………………… 33 3.3.3 Corrosion rates by LPR …………………………………………………………………………………………….. 33 3.3.4 Methane production during incubation of samples …………………………………………………. 36 3.3.5 Weight loss corrosion rates of samples incubated in methane incubations …………….. 36 3.3.6 Community composition …………………………………………………………………………………………. 39 3.4 Discussion ……………………………………………………………………………………………………………………….. 40

CHAPTER FOUR: POTENTIAL OF BIOCORROSION AND SOURING IN A LIGHT OIL PRODUCING FIELD IN PAPUA NEW GUINEA …………………………………………………………………………………………… 43

4.1 Introduction and samples received ………………………………………………………………………………….. 43 4.2 Materials and methods ……………………………………………………………………………………………………. 49 4.2.1 Sample handling ………………………………………………………………………………………………………. 49 4.2.2 Water chemistry ……………………………………………………………………………………………………… 49 4.2.3 Most probable numbers (MPNs) ……………………………………………………………………………… 49 4.2.4 Corrosion rate measurements …………………………………………………………………………………. 49 4.2.5 Methanogenesis and acetogenesis ………………………………………………………………………….. 50 4.2.6 Microbial community composition ………………………………………………………………………….. 51 4.3 Results and discussion ……………………………………………………………………………………………………… 51 4.3.1 Water chemistry ……………………………………………………………………………………………………… 51

4.3.2 MPN ………………………………………………………………………………………………………………………… 52 4.3.3 Corrosion rates ………………………………………………………………………………………………………… 53 4.3.4 Methanogenesis and acetogenesis ………………………………………………………………………….. 57 4.3.5 Microbial community compositions ………………………………………………………………………… 60 4.4 Conclusion ……………………………………………………………………………………………………………………….. 64

CHAPTER FIVE: IS THPS A POSSIBLE SOURCE OF SULFATE FOR THE GROWTH OF SRB IN OIL PROCESSING FACILITIES IN PAPUA NEW GUINEA? ……………………………………………………………….. 67

5.1 Introduction …………………………………………………………………………………………………………………….. 67 5.2 Material and methods ……………………………………………………………………………………………………… 72 5.2.1 Sample handling ………………………………………………………………………………………………………. 72 5.2.2 Water chemistry ……………………………………………………………………………………………………… 72 5.2.3 Most probable numbers (MPNs) of SRB and APB …………………………………………………….. 72 5.2.4 Corrosion rate measurements …………………………………………………………………………………. 72 5.2.5 Methanogenesis ……………………………………………………………………………………………………… 73 5.2.6 Microbial community analyses ………………………………………………………………………………… 73 5.3 Results …………………………………………………………………………………………………………………………….. 73 5.3.1 Water chemistry ……………………………………………………………………………………………………… 73 5.3.2 MPNs of SRB and APB ……………………………………………………………………………………………… 74 5.3.3 Corrosion rate measurements …………………………………………………………………………………. 77 5.3.4 Methane in corrosion incubations …………………………………………………………………………… 81 5.3.5 Microbial community data of PNG samples …………………………………………………………….. 83 5.3.6 Microbial community data of corrosion incubations ……………………………………………….. 84 5.4 Conclusions ……………………………………………………………………………………………………………………… 88

CHAPTER SIX: IMPACT OF LIGHT OIL TOXICITY ON SOURING ……………………………………………….. 90

6.1 Introduction …………………………………………………………………………………………………………………….. 90 6.2 Materials and methods ……………………………………………………………………………………………………. 91 6.2.1 Samples …………………………………………………………………………………………………………………… 91 6.2.2 Water chemistry ……………………………………………………………………………………………………… 91 6.2.3 Microbial community analysis …………………………………………………………………………………. 93 6.2.4 Experimental setup …………………………………………………………………………………………………. 93 6.3 Results and observations …..…………………………………………………………………………………………….. 93 6.3.1 Experiment with 3-PW …………………………………………………………………………………………….. 93 6.3.2 Results …………………………………………………………………………………………………………………….. 93 6.3.3 Observation for experiment with 3-PW …………………………………………………………………… 97

6.3.4 Experiment with Desulfobacter postgatei ………………………………………………………………… 98 6.3.5 Results ……………………………………………………………………………………….……………………………. 98 6.3.6 Observation for experiment with Desulfobacter postgatei .……………………………………. 100 6.3.7 Experiments with SW enrichment ……………………………………………….………………………… 100 6.3.8 Results ………………………………………………………………………………………….……………………..… 100 6.3.9 Microbial community data …………………………………………………………….…………………….… 102 6.3.10 Observation for expertiment with SW enrichment ………………………………………………. 104 6.3.11 Minimum inhibitory volumes (MIVs) of light oils …………………………………………………. 104 6.3.12 Results …………………………………………………………………………………………………………………. 106 6.3.13 Observation for MIV of light oils ………………….………………………………………………………. 108 6.3.14 Oil compositions ………………………………………………………………………………………………….. 108 6.3.15 observation for oil compositions …………………………………………………………………………. 109 6.3.16 MIV of different light oil components ………………………………………………………………….. 109 6.3.17 Results …………………………………………………………………………………………………………………. 111 6.3.18 Observation for MIV of different light oil components .……….………………………………. 113 6.4 Conclusion ……………………………………………………………………………………………………………………… 113

CHAPTER SEVEN: CONCLUSIONS ………………………………………………………………………………………… 115

REFERENCES: …………………………………………………………………………………………………………………… 118

Appendix table S1: 2013/2014 PNG sample list ………………………………………………………………… 127 Appendix figure S1: Field diagram of Agogo, Moran and Kutubu 2013/2014 ……………………. 128 Appendix figure S2: Field diagram of Gobe Main and Gobe SE 2013/2014 ……………………….. 129 Appendix figure S3: Field diagram of Agogo, Moran and Kutubu 2014/2015 ……………………. 130 Appendix figure S4: Field diagram of Gobe Main and Gobe SE 2014/2015 ……………………….. 131

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List of Tables

Table 1.1 Light end components for different oils …………………………………………………………………... 6

Table 3.1 Identification numbers and a brief description of the pipeline samples …………………. 30

Table 3.2 Chemical analyses of aqueous sample extracts ………………………………………………………. 34

Table 3.3 VFA analyses of aqueous extracts …………………………………………………………………………… 34

Table 3.4 Microbial counts for aqueous extracts ……………………………………………………………………. 35

Table 3.5 Corrosion rates of aqueous sample extracts by portable LPR …………………………………. 35

Table 3.6 Corrosion rates of duplicate coupons incubated with samples ………………………………. 38

Table 4.1 Name, label and appearance for 2013/2014 samples …………………………………………….. 48

Table 4.2 Water chemistry and MPN analysis of 2013/2014 PNG samples …………………………….. 54

Table 4.3 Corrosion rates for PNG samples ……………………………………………………………………………. 55

Table 4.4 Methane and acetic acid production in incubations of 2013/2014 PNG samples in the presence of iron beads ………………………………………………………………………………………………………….. 56

Table 4.5 Acetate formation by 2013/2014 samples incubated with 80%H2 and 20%CO2 in the headspace ……………………………………………………………………………………………………………………………… 59

Table 4.6 Distribution of sequences over taxa for 2013/2014 samples ………………………………….. 63

Table 5.1 Names and descriptions for 2014/2015 samples ……………………………………………………. 71

Table 5.2 Samples received in 120 ml serum bottles with either carbon steel coupons or iron beads and an N2-CO2 atmosphere …………………………………………………………………………………………. 71

Table 5.3 Water chemistry results for 2014/2015 samples ……………………………………………………. 75

Table 5.4 MPNs of APB and SRB for 2014/2015 samples ……………………………………………………….. 76

Table 5.5 Survey of data collected for serum bottles used for corrosion rate measurements … 79

Table 5.6 Mass of individual beads (mg) following incubation to determine corrosion ………….. 79

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Table 5.7 Corrosion rate (mm/yr) calculated for weight loss of individual beads …………………… 80

Table 5.8 Distribution of sequence over taxa. The numbers are fractions (%) of the number of pyrosequencing reads for each taxon ……………………………………………………………………………………. 86

Table 5.9 Distribution of sequences over taxa for corrosion incubations ……………………………….. 87

Table 6.1 Types of crude oil used in light oil toxicity experiments ………………………………………….. 92

Table 6.2 Types of cultures used as inoculum SRB activity experiments ………………………………… 92

Table 6.3 Microbial community composition of SW enrichment ………………………………………….. 103

Table 6.4 Volumes of oil and HMN used in experiments to determine the minimum inhibitory volume (MIV) ………………………………………………………………………………………………………………………. 105

List of Figures

Figure 3.1 Samples from the inside surface of a pipeline and diluent ………………………..…………… 30

Figure 3.2 Methane in the headspace of incubations of sample solids …………………………………… 37

Figure 3.3 Pyrosequencing analysis of 16S rRNA genes showing a dendrogram for pipeline solids samples, major phyla and classes …………………………………………………………………………………………. 42

Figure 3.4 Depiction of how microbes survive in diluent transporting pipeline under nodule formation ………………………………………………………………………………………………………………………………. 42

Figure 4.1 Picture of samples received in December 2013 and January 2014 .……………………….. 47

Figure 4.2 Methane production of samples incubated with an H2-CO2 ……….………….………………. 58

Figure 4.3 Volume of headspace gas used during incubations with H2-CO2 …………….……………… 58

Figure 4.4 Pyrosequencing analysis of 16S rRNA genes showing dendrogram, major phyla and classes for PNG samples …………………………………………………………………………….………………………….. 62

Figure 5.1 Images of samples as received in 2014/2015 from PNG field ………………………………… 70

Figure 5.2 MPNs for APB and SRB for 2014/2015 PNG samples …………………………………….………. 76

Figure 5.3 Plot of standard deviation of residual bead weights versus average weight loss …… 80

Figure 5.4 Methane concentration (μM) in the headspace of corrosion incubations, containing either beads or coupons ………………….……………………………………………………………………………………. 82

Figure 6.1 Incubation of 3-PW, enrichment with lactate and sulfate with or without Tundra oil …………………………………………………………………………………………………………………………………...…………. 95

Figure 6.2 Measurements of samples incubated with 3-PW, VFA, and sulfate with or without Tundra oil ………………………………………………………………………………………………………………………………. 96

Figure 6.3 Incubations with Desulbacter postgatei, with sulfate and acetate in the presence of different oil …………………….…………………………………………………………………………………………………..... 99

Figure 6.4 Incubations of SW enrichment, with sulfate and acetate in the presence of different oil ………………………………….…………………………………………………………………………………………………….. 101

Figure 6.5 Incubations of SW enrichment, with sulfate, sulfide and acetate in the presence of different oil ………………..…………………………………………………………………………………………………………………….. 107

Figure 6.6 BTEX molecule compositions and Light molecular weight (LMW) alkane compositions of different oils ……………………………………………………………………………………………………………………. 110

Figure 6.7 Incubations of SW enrichment, with sulfate, sulfide and acetate in the presence of different concentration of oil components and HMN ..………………………………………………………… 112

List of Symbols, Abbreviations and Nomenclature

APB Acid producing bacteria API American Petroleum Institute BTEX Benzene, toluene, ethylbenzene and xylene

CH4 Methane

CO2 Carbon dioxide CPF Central processing facility CR Corrosion rate

CSBK Coleville synthetic brine media DNA Deoxyribonucleic acid EN Encrusted nodule Fe0 Elemental iron Fe2+ ferrous iron FS Filtered solids FW Facility water GPF Gobe processing facility

H2O water

H2S Hydrogen sulfide - HCO3 Bicarbonate HMN Heptamethylnonane hNRB Heterotrophic nitrate-reducing bacteria HPLC High-pressure liquid chromatography HS- Sulfide IW Injection water IW Injection water LMW Low molecular weight Meq Molar equivalent MIC Microbially influenced corrosion MIV Minimum inhibitory volume mM Millimolar MPN Most probable number

N2 Elemental nitrogen (gas)

NH3 Ammonia - NO2 Nitrite - NO3 Nitrate PAHs Polyaromatic Hydrocarbons PCR Polymerase chain reaction PS Pigging solids

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PWRI Produced water reinjection PW Produced water RNA Ribonucleic acid SD Standard deviation 2- SO4 Sulfate SS Sludge solids SRB Sulfate reducing bacteria THPS Tetrakishydroxymethylphosphonium sulfate VFA Volatile fatty acids

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1. Introduction: 1.1. Alberta Oil & Gas Industry and Light oil reserves

Alberta is a hub of the energy sector in Canada, which is mainly dominated by the oil sands industry. There are three major areas in Northern Alberta where oil sands are deposited,

Athabasca oil sands, Peace River oil sands, and Cold Lake oil sands. Together they cover a large land area (142,000 km2) (Government of Alberta, 2014). Alberta has about 168 billion barrels of oil in oil sands deposits, which is third only to Venezuela and Saudi Arabia. Most of the reserves in Alberta’s oil sands are heavy oil, and only 3% of which can be surface mined, the rest of the reserves are deep, requiring other extraction methods (Government of Alberta, 2014). Oil sand deposits are a mixture of sand, clay, water and heavy oil called bitumen. Once the bitumen is extracted from the deposits it is diluted by addition of diluent, so that it can flow easily and can be shipped easily using a pipeline. The product which is produced by combining diluent and bitumen is called dilbit or syndilbit (synbit) (Alberta Energy Regulator, 2014). It is generally believed that since diluent could be toxic to microorganisms, there would be not microbial growth in pipelines transporting diluent. So is there microbial growth in diluent transporting pipeline and can microorganisms influence corrosion in such harsh and dry conditions?

Apart from heavy oil, there are light oils (conventional and offshore oil) and shale oils which are produced in American countries, Middle Eastern countries and in European countries.

Conventional light oils makes up of 30% of world’s total oil reserves (Landartgenerator, 2009).

Conventional crude oil extraction is done by drilling wells, and the initial oil rises up to surface by the pressure built up in reservoir by gas pressure, rock pressure or natural water driving force; this type of oil recovery is termed as primary oil extraction (US patent, 1962). Once the

initial gas pressure decreases, water is injected into the reservoir to drive crude oil out of the reservoir; this type of oil recovery is termed as secondary oil extraction or water flooding process (Deng et al., 2009). One of the major concerns in the secondary oil extraction by water flooding is souring. Souring is a term used for undesirable production sulfide during secondary oil extraction by sulfate reducing bacteria (SRB) (Hubert and Voordouw, 2007). SRB are also one of the major players in microbially influenced corrosion (MIC) (McNeil and Odom, 1994). Light oil produced from these reservoirs can be toxic for microbial growth (Sherry et al., 2014); still problems like souring and MIC persist in these reservoirs. This leads us to an important question, how toxic is light oil to microorganisms and to what extent can it hinder microbial growth?

1.2. Pipelines an important mode of oil transportation

The distribution of crude oil from oil sands or from conventional light oil fields mainly depends on pipelines. Alberta itself has more than 400,000 kilometers of pipeline, of which

320,000 kilometers carry crude oil, natural gas and multiphase product (mixture of oil, gas and water) (Alberta Energy Regulator, 2013). One of the major concerns of the pipeline industry is pipeline failure. In the last 38 years, 29,229 pipeline incidents have been reported, of which

11,688 involved crude oil and multiphase product carrying pipelines (Wohlberg, 2013). Pipeline failure can be catastrophic; it can lead to great environmental impact, production losses as well as huge economic losses. The oil and gas industry has seen pipeline failure incidents, which have not only impacted the environment but have also led to loss of human life? Even though industry has tight regulations and there are government regulatory bodies that monitor industry practice, there are still incidents that lead to pipeline failures. Pipeline failures can be

caused by corrosion, construction damage, earth movements, joint failure, overpressure, weld, and operator error (Alberta Energy Regulator, 2013). Even though it is hard to predict these pipeline failures, they can definitely be minimized by safer practices like protecting the pipelines with coating and cathodic protection. Over time we have definitely seen a reduction in pipeline failure cases (Alberta Energy Regulator, 2013).

1.3. Corrosion in oil transporting pipelines

One of the major causes of pipeline failure is via corrosion. There are different mechanisms of corrosion which include physical, chemical and biological corrosion. Physical corrosion can include erosion or enhanced flow corrosion (by gas bubbles in transported crude oil). Chemical corrosion can be caused by oxygen, organic acids, sulfur or sulfide. Biological corrosion is usually referred to as microbially influenced corrosion (MIC). Corrosion includes uniform corrosion, stress corrosion cracking, and pitting corrosion (Jomdecha et al., 2007). Uniform corrosion can be measured easily (by electrochemical methods) compared to pitting corrosion, which needs visual inspection. One of the causes of pitting corrosion can be MIC (Jain et al.,

2015).

1.4. Microbially influenced corrosion

MIC is a serious problem in the oil and gas industry. It has been estimated that approximately 40% of all the internal corrosion in oil transporting pipelines can be attributed to

MIC (Naranjo et al., 2015). There are certain microbes that can cause corrosion or whose activities lead to corrosion, but for microbes to cause corrosion in oil transporting pipelines, they should be able to grow under conditions prevailing in pipelines carrying hydrocarbons

(Beech and Sunner, 2004). Prerequisites for microbial growth are an energy source which can

be constituted by an electron donor (inorganic or organic substance) and an electron acceptor

2- 2 - like (SO4 , CO , O2, NO3 and others), a carbon source (CO2 or organic substance), trace elements and water (Beech et al., 2000). The major players in MIC are sulfate reducing bacteria

(SRB) (Enning and Garrelfs, 2014). SRB can directly cause corrosion by stripping hydrogen from the metal surface and using this as an electron donor for sulfate reduction. SRB also cause corrosion through its by-product sulfide (Javaherdashti, 1999). Another group of microorganisms, methanogens, can strip proton from iron, which they combine with carbon dioxide to produce methane and water. Pipelines transporting crude oil or light hydrocarbon are often subjected to cathodic protection to maintain pipeline integrity. Under cathodic protection a pipeline is induced with electric charge to make the surface potential more negative and to make the pipeline a cathode compared to its surroundings. When the pipeline is subjected to a negative potential there can be evolution of hydrogen from the surface of the carbon steel and methanogens or SRB can possibly use this hydrogen to produce methane or sulfide. Methanogens can only cause corrosion directly, because their by-product methane does not contribute to corrosion. Acid producing bacteria (APB) are also associated with MIC; they select a desirable site and form a colony to develop crevice corrosion (Huggins, 1997). APB cannot cause direct corrosion, but their by-product organic acid can cause corrosion of the metal surface.

1.5. Light oil and Diluent (composition)

Light oil has API (American Petroleum Institute) gravity in excess of 31.1°. API gravity is calculated by using the specific gravity of oil, which will be the ratio of oil density to that of

water (Formula: API gravity = [141.5/Specific Gravity] – 131.5) (Petroleum UK, 2015). Light oil is a combination different of aromatic and aliphatic compounds. A study of Alberta sweet mix blend (ASMB), showed that there are 281 different compounds present in ASMB, which was dominated by aromatic compounds (126) followed by aliphatic compounds (102) and some biomarker hydrocarbons (triterpanes and steranes)(53) (Wang et al., 1994). Light oils are less viscous and have more volatile components than conventional heavy oil (Table 1.1) (Blackmore et al., 2014). Compared to heavy oil, light oil has a lower viscosity, a higher dispersion and a higher flammability (Tsaprailis and Zhou, 2013).

Diluent is either naphtha or naphtha with added natural gas condensate. Natural gas condensate is a liquid condensate; the lightest component of this condensate is butane

(Dettman, 2012). Diluent is added to bitumen to reduce its viscosity, allowing it to flow easily to transport it through pipeline. The major components of gas condensate may include butane, pentane, hexane, heptane, octane, and nonane (Blackmore et al., 2014). The concentrations of the light end of diluent (condensate) are much higher than those in conventional heavy oil or bitumen. Thus light condensate is used to dilute bitumen, so that bitumen can meet up to pipeline entry specifications (Blackmore et al., 2014). Below is a chart (Table 1.1) that shows how light oil, diluent and heavy oil differ from each other in composition (Blackmore et al.,

2014).

Table 1.1. Light end components for different oils (data from Alberta Innovates, Blackmore et al., 2014).

Crude C2 C3 C4 C5 C6 C7 C8 C9 Stream Minus Minus Minus Minus Minus Minus Minus Minus Conventional 0.03 0.49 4.47 7.78 13.47 20.56 27.70 33.21 Light Oil Conventional 0.02 0.09 1.48 5.49 8.60 11.43 14.07 16.27 Heavy Oil Condensate 0.03 0.23 3.44 33.60 50.16 65.00 76.50 82.19 (Diluent) Note: Values are cumulative: C5 Minus includes (C1, C2, C3, C4, and C5).

1.6. Light oil toxicity

Light oils are rich in low molecular weight (LMW) alkanes and BTEX molecules (benzene, toluene, ethyl benzene, and xylene). Microorganisms can degrade these molecules in low concentration, but at high concentration these molecules can be toxic to microorganisms. To understand light oil toxicity of microorganisms, we have to first understand the structure of the microbial cell envelope.

A cell envelope of microorganisms is made up of the cell wall and lipid membranes

(Beveridge et al., 1991). Cell envelope varies among different microorganisms; gram positive bacteria have a single cytoplasmic membrane inside the cell wall, whereas gram negative bacteria have a cytoplasmic membrane on the inside and an outer membrane made up of phospholipid and lipopolysaccharide on the outside of the cell wall (Neidhardt et al., 1987). The cytoplasmic membrane consists of a phospholipid bilayer in which membrane proteins are embedded (Gorter and Grendel, 1925; Singer and Nicolson, 1972). These transport proteins facilitate the intake of various solutes (Poolman et al., 1994). The cytoplasmic membrane not only regulates the uptake of solutes, but also controls the energy transduction processes and the cell internal environment (Booth, 1985; Stock et al., 1989). Permeability for polar and charged molecules is low for the cytoplasmic membrane, but apolar molecules like hydrocarbons can dissolve in it and pass through the lipid bilayer of the cytoplasmic membrane

(Sikkema et al., 1995). The transfer of these molecules can be through diffusion or by energy requiring transport. At lower concentration the cell can metabolise the hydrocarbon, but at higher concentration, when the rate of metabolism of hydrocarbon does not match the rate of

transport (higher transport than metabolism) the result can be lethal for the microorganism

(Sikkema et al., 1995). In the case of alkanes uptake the LPS of the outer membrane is released and encapsulates the hydrocarbon and assists in the uptake of hydrocarbon into the cell

(Witholt et al., 1990).

Toxic effects of benzene on strains of Pseudomonas were inhibition of growth and a decreased conversion rate of benzene to cis-3, 5-cyclohexadiene-1, 2-diol (Gibson et al., 1970;

Van den Tweel et al., 1987). Similar inhibitory effects were observed on P. putida in the presence of toluene (Jenkins et al., 1987). Aliphatic hydrocarbons may also be toxic to microorganisms (Atlas, 1981), but some data suggests that alkanes may only partially inhibit cellular activity (Blom et al., 1992). The toxicity of alkanes is related to their chain length, which determines their solubility in water as well as their hydrophobicity (Gill and Ratledge, 1972).

1.7. Sulfate Reducing Bacteria (SRB)

SRB are anaerobic microorganisms that reduce sulfate to sulfide by oxidising organic compounds (Muyzer and Stams, 2008). SRB can be a serious concern in oil and gas operations because of their souring ability and they can cause serious damage to infrastructure as they can be corrosive too. SRB can use hydrogen (H2) or common oil organics to reduce sulfate to sulfide

(equations 1 to 5) (Muyzer and Stams, 2008).

2- + - 4H2 + SO4 + H → HS + 4H2O (eq. 1)

- 2- - - Acetate + SO4 → 2HCO3 + HS (eq. 2)

- 2- - - - + Propionate + 0.75 SO4 → Acetate + HCO3 + 0.75 HS + 0.25 H (eq. 3)

- 2- - - + Butyrate + 0.5 SO4 → 2 Acetate + 0.5 HS + 0.5 H (eq. 4)

- 2- - - - Lactate + 0.5 SO4 → Acetate + HCO3 + 0.5 HS (eq. 5)

Another concern with SRB is their ability to cause corrosion to oil transporting pipelines as well as oil holding facilities. Some can use metallic iron (Fe0) directly as electron donor (eq. 6)

(Enning and Garrelfs, 2014).

4 Fe0 → 4 Fe2+ + 8 e− (eq. 6)

− 2− + 8 e + SO4 + 10 H → H2S + 4 H2O (eq. 7)

SRB can cause biogenic souring (eq. 1-5). Biogenic souring in oil reservoirs subjected to water flooding is a well-recognised problem, and can be dealt with nitrate injection (Nemati et al., 2001). Souring can change conventional oil fields producing light sweet crude into fields producing light sour crude, by the action of SRB (Eden et al., 1993). Techniques used to monitor souring and corrosion caused by SRB in oil fields includes community analysis by DNA sequencing (An et al., 2015). Methods to control souring include injections of nitrate or biocides. A recent study showed that biocide injection in a low temperature light oil field was not effective (Evans et al., 2015), whereas another study showed that biocides like

glutaraldehyde and tetrakishydroxymethyl phosphonium sulphate (THPS) have proven effective in souring control (Immanuel et al., 2015).

1.8. Methanogens

Methanogens are prevalent in petroleum reservoirs, and are anaerobic microorganisms that catalyze conversion of carbon dioxide or other C1 compounds to methane; or of acetate to

methane and CO2 (Head et al., 2003). Methanogens can use some of the common oil organics to produce methane (equation below) (Muyzer and Stams, 2008).

- + 4H2 + HCO3 + H → CH4 + 3H2O (eq. 8)

CO2 + 4H2 → CH4 + 2H2O (eq. 9)

- - CH3COO + H2O → CH4 + HCO3 (eq. 10)

CH3COOH → CH4 + CO2 (eq. 11)

The equation demonstrating iron corrosion by methanogens is as follows (Uchiyama et al.,

2010).

+ 2+ 8H + 4Fe + CO2 → CH4 + 4Fe + 2H2O (eq. 12)

Methanogens in oil reservoirs are usually active in biodegradation of oil components, whereas methanogens in pipelines can be associated with MIC. Methanogens can survive under harsh conditions (dry and toxic) in pipelines. One study showed that methanogens were found in a natural gas transporting pipeline with less than 1% water content and that they were associated with MIC (Zhu et al., 2003; Zhu et al., 2005). Methanogens can also grow in

syntrophy with SRB and can cause MIC (Park et al., 2011). There are thermophilic methanogens which can survive at high temperature and can cause MIC (Davidova et al., 2012). So in general it has been observed that methanogens are resilient and can survive and proliferate under harsh conditions.

1.9. Microbial life in light hydrocarbon transporting pipelines

Microbial life in a light hydrocarbon transporting pipeline is harsh. The environment in light hydrocarbon transporting pipelines is dry; by regulation the water content of the transported hydrocarbon should be less than 1% and it is usually around 0.5% (Place, 2013). The oil or the light hydrocarbon transported is not corrosive to the pipeline but the water present in the pipeline can accumulate in low points improving conditions for microbial growth (Place, 2013).

Microorganisms surviving and proliferating in light hydrocarbon transporting pipelines may degrade hydrocarbon components for energy. A required co-reactant in some of the biogenic hydrocarbon degradation is water (Callbeck et al., 2013). Below are the equations that demonstrate the use of water in biogenic hydrocarbon degradation reactions for hexadecane

(Callbeck et al., 2013).

- + 4C16H34 + 64H2O → 32CH3COO + 32H + 68H2 (eq. 13)

- + 32CH3COO + 32H → 32CH4 + 32CO2 (eq. 14)

68H2 + 17CO2 → 17CH4 + 34H2O (eq. 15)

4C16H34 + 30H2O → 49CH4 + 15CO2 (eq. 16)

Water is a key reagent needed for methanogenic degradation of hydrocarbon. The oxygen atoms in CO2 and bicarbonate formed during anaerobic degradation of hydrocarbon is derived from water. So water is must for microbial life to proliferate in a light hydrocarbon transporting pipeline. Another issue for microorganisms in light hydrocarbon transporting pipelines is light oil toxicity. Microbes must protect themselves against the toxic effects of light hydrocarbon by finding a niche on the pipe wall that shields them from exposure to light hydrocarbon in an area that has enough water for light hydrocarbon degradation. So microbial life in light hydrocarbon transporting pipelines is possible, but the conditions are harsh. Research on microbial life in a diluent storage tank showed that there are fungal strains that were able to survive and cause fungal influenced corrosion (FIC) (Khatib and Salanitro, 1997). Research has also been done to understand the properties of light hydrocarbons and their corrosivity (Dias et al., 2015), but not a lot of data exist on microbial life in the presence of light hydrocarbon, so it is a perfect area to study and understand how microbes survive and proliferate in light hydrocarbon transporting pipelines.

1.10. Souring and biocorrosion in light oil producing oil fields

Souring is a well-recognized problem in oil fields. Souring caused by SRB can impact oil field operations severely. Souring can be mitigated by nitrate injection in oil fields and by biocide injection in pipelines. Souring has been observed in various light oil producing fields in the

North Sea as well as in light oil producing fields in Papua New Guinea. An important aspect of souring is the source of sulfate. The water used for flooding the reservoir can introduce sulfate, which is then used by SRB to produce sulfide. In water flooding off-shore operations, seawater

is used with a high sulfate concentration (20-30 mM) (Khatib and Salanitro, 1997). Reservoirs on land may be injected with water with little sulfate. For souring control the important point is to find the source of sulfate, and if possible try and eliminate this sulfate source. One of my research areas focuses on corrosion in above ground facilities of a Papua New Guinea oil field.

The facility water (FW) showed the presence of higher sulfate concentration than the produced water (PW). This indicated an input of sulfate above ground, possibly the biocide (THPS) used to reduce the microbial counts in the FW. Other research has shown that use of the oxygen scavenger sodium bisulfite has increased SRB activity in a brackish water transporting pipeline

(Park et al., 2011). Although THPS has been shown to be an effective biocide in controlling souring along with reducing the SRB numbers in produced water (Talbot et al., 2000), its addition increases the sulfate concentration which eventually may cause more souring.

1.11. Light oil toxicity on acetate utilizing SRB

SRB play a key role in the carbon cycle. In the early 1980s, it was known that SRB like

Desulfovibrio and Desulfotomaculum oxidize organic compounds like lactate, pyruvate, malate and succinate incompletely oxidized to acetate for growth (Muyzer and Stams, 2008). It was only later, when Widdel Friedrich isolated acetate-utilizing SRB (Widdel and Pfennig, 1977), that it was realized that some SRB can oxidize organic carbon all the way to carbon dioxide. There are two different pathways used by these SRB to oxidize acetate to CO2, one is the modified citric acid cycle used by Desulfobacter species and the other is the acetyl CoA pathway used by

Desulfobacterium, Desulfotomaculum, and Desulfococcus species and by Desulfobacca acetoxidans (Muyzer and Stams, 2008). So in the environment certain SRB like Desulfovibrio or

Desulfomicrobium will incompletely oxidize organic compounds like pyruvate, lactate or succinate to acetate. In the presence of excess sulfate this acetate will not accumulate but will be further oxidized to carbon dioxide by acetate-utilizing completely oxidizing SRB.

It has been observed that there is accumulation of acetate in oil field waters; often from fields producing light oil as from a North Sea oil field (Beeder et al., 1994). The accumulation of acetate in these waters, where the sulfate concentration is high, suggests that oil in these waters could be toxic to acetate-utilizing SRB. Previous research has suggested light oil toxicity towards Desulfobacter species, but another acetate-utilizing SRB Desulfobacula toluolica are capable of reducing sulfate to sulfide in presence of toluene (Rabus et al., 1993). The study showed that toluene, methylbenzoate or lactate are completely oxidized to carbon dioxide by

Desulfobacula toluolica using the carbon monoxide dehydrogenase pathway (Rabus et al.,

1993). More research is required to understand how acetate-utilizing SRB are affected by the presence of light or heavy oil and which concentrations of these oils are inhibitory.

1.12. Objectives

In my thesis, work is focused on souring and MIC in light oil producing oil reservoirs as well as in light hydrocarbon transporting pipeline. There are three major objectives:

(i) MIC in diluent transporting pipeline. It is believed that microorganisms do not cause

corrosion in diluent transporting pipelines, as these pipelines are very dry and

diluent is very toxic to microorganisms. But still there are cases of corrosion

observed in these pipelines, so my objective was to study the solid samples taken

from inside of a diluent transporting pipeline and to find whether there is potential

of MIC on carbon steel in these samples and to understand how microorganisms

survive in these solid samples.

(ii) Potential of biocorrosion and souring in a light oil producing reservoir. Samples from

a light oil producing facility in Papua New Guinea were received. There were

incidents of pipeline failure due to corrosion. My objective was to find whether

these failures were caused by MIC, and whether there was potential for souring in

these samples. It was also observed that the facility water had more sulfate than

produced water, and the source of this sulfate was unknown. So to find the source

of sulfate was also important as it could pinpoint the cause of souring.

(iii) Impact of light oil toxicity on souring. Light oil is toxic to certain microorganisms, so

my objective was to understand how SRB survive and proliferate in the presence of

light oil. If presence of light oil hinders SRB activity, then a secondary objective was

to determine which components in light oil are toxic to SRB.

2. Chapter Two: Methods and Materials.

2.1. Molecular methods

2.1.1. DNA extraction

DNA extraction is a key method used to analyse the community composition of samples. It is important to collect cells from the sample and extract DNA as soon as possible, because the communities in samples are subject to change. All the samples received were stored in the anaerobic hood with a headspace of N2/CO2. DNA for all the samples was extracted using the

FastDNA® SPIN Kit (Qiagen). For liquid samples like source water, produced water or facility water, the cells were either collected by centrifuging 200 ml of samples at 12,000 rpm for 30 minutes at 4°C or by vacuum filtration of 200 ml of samples using a 0.2 µm filter. Solid samples were used directly for the DNA extraction process. The concentrated cells (liquid sample) or solid samples (approximately 500 mg) were re-suspended with sodium phosphate (978 µl) and

MT buffer (122 µl) in a Lysing Matrix E tube. Then the cells were subjected to bead beating

(FastPrep instrument from MP Biomedicals) to break the cells and releasing DNA out of the cells. The cell debris was pelleted by centrifuging at 14,000 g for 7 min. The supernatants were transferred to a clean 2.0 ml microcentrifuge with 250 µl of protein precipitation solution (PPS).

After shaking to mix the supernatants with PPS these were centrifuged at 14,000 g for 5 min to pellet the precipitates. The supernatants were transferred into a 15 ml Falcon tube with binding matrix suspension and where hand shaken for 2 minutes. Then the combined matrices were allowed to settle for 3 min on a rack and then 500 µl of supernatant were discarded. Later the binding matrix was resuspended with supernatant and transferred to a spin filter and centrifuged at 14,000 g for 1 min. The solution collected from the spin tubes was discarded and

500 µl of SEWS-M were added to the spin filter to resuspend the pellet collected on the spin filter. The spin filters were centrifuged at 14,000 g for 1 min to remove SEWS-M and without any addition of SEWS-M the spin filters were re-centrifuged for 2 minutes. The spin filters then were air dried for 5 minutes. Finally, the binding matrix was resuspended in 70 µl of DES

(DNase/Pyrogen-Free water) and incubated in a 55°C water bath for 5 min. DNA was then eluted by centrifuging at 14,000 g for 2 min.

2.1.2. Polymerase chain reaction (PCR)

The PCR amplification of extracted DNA was done using primers targeting the 16S rRNA genes. For both Roche 454 pyro-sequencing and Illumina sequencing appropriate primers were introduced and two separate PCR reactions were performed to collect enough PCR products to conduct sequencing.

PCR amplification for 454 sequencing was done first using the 16S primers 926F

(AAACTYAAAKGAATTGRCGG) and 1392R (ACGGGCGGTGTGTRC). For PCR, 2 µl of extracted DNA was used as the template with 25 µl of PCR master mix (contains 0.05 µl Taq DNA polymerase,

2.5 µl of reaction buffer, 4 mM MgCl2 and 0.4 mM of each dNTP), 22 µl of PCR grade water, and

0.5 µl of forward and reverse primers concentrations. The cycling conditions were set at 95°C for 5 min for 1 cycle, followed by 25 cycles, each consisting of 30 sec of 95°C, 45 sec of 55°C and

30 sec of 72°C, followed by a final step at 72°C for 10 min. PCR products were purified by a

Qaigen PCR purification kit. The PCR products were checked using 1.5% agarose gels. The second round of PCR was conducted using the first PCR product as DNA template. The primers used for second PCR were FLX titanium primers 454T_RA_X (barcoded) and 454T_FB. The

reaction conditions included 25 µl of master mix, 22 µl of PCR grade water, 0.5 µl of forward and reverse primers, and 2 µl of DNA template (first PCR product). The cycling conditions included 1 cycle of 95°C for 3 min, followed by 10 cycles each consisting of 30 sec of 95°C, 45 sec of 50-55°C and 30 sec of 72°C, followed by a final step at 72°C for 10 min. Again the PCR products were purified and checked on a 1.5% agarose gel.

PCR amplifications for Illumina sequencing in the first round were done using the 16S primers 926Fi5 (5’-TCGTCGGCAGCGTCAGATGTGTATAAGAGACAGAAACTYAAAKGAATWGRCGG-3’) and 1392Ri7 (5’-GTCTCGTGGGCTCGGAGATGTGTATAAGAGACAGACGGGCGGTGWGTRC-3’). For

PCR reaction conditions 2 µl of extracted DNA was used as the template with 25 µl of PCR master mix, 1 µl of MgCl2, 23 µl of PCR grade water, 0.75 µl of forward and reverse primers. The cycling conditions of PCR reaction were set at 95°C for 5 min for 1 cycle, followed by 25 cycles, each consisting of 30 sec of 94°C, 45 sec of 55°C and 2 min of 72°C, followed by a final step at

72°C for 10 min. PCR products were purified by PCR cleaning kit. Then the PCR products were checked using 1.5% agarose gels. The second round of PCR was conducted using the first PCR product as DNA template. The primers used for second PCR were forward Primer P5-S50X-

OHAF which contains a 29 nucleotide 5’ Illumina sequencing adaptor (P5,

AATGATACGGCGACCACCGAGATCTACAC), an 8 nucleotide index S50X and a 14 nucleotide forward overhang adaptor (OHAF, TCGTCGGCAGCGTC). The reverse Primer P7-N7XX-OHAF had a 24 nucleotide 3’ Illumina sequencing adaptor (P7, CAAGCAGAAGACGGCATACGAGAT), an 8 nucleotide index N7XX and a 14 nucleotide reverse overhang adaptor

(OHAF,GTCTCGTGGGCTCGG). The reaction conditions included 30 µl of master mix, 28 µl of PCR grade water, 0.5 µl of forward and reverse primers, 1 µl of MgCl2, and 2 µl of DNA template

(first PCR product). The reactions were divided over 3 tubes each of 20 µl, for better cycling conditions, in terms of temperature transfer between the cycles. The cycling conditions were the same as for the first PCR. Following the PCR cycles, the three 20 µl reactions were pooled to get a combined 60 µl reaction per sample. Again the PCR products were purified and checked on a 1.5% agarose gel.

Once the purified PCR products were obtained, their concentrations were determined using a Qubit Fluorometer (Invitrogen). The concentrations of PCR products were then adjusted to 20 ng/µl. They were then sent for pyro-sequencing to the Genome Quebec Sequencing Center in

Montreal, Quebec. After the pyro-sequencing the raw sequence data obtained were analysed in the lab at the University of Calgary, using the Phoenix 2 analysis pipeline (Soh et al., 2013).

2.2. Analytical Methods

2.2.1. Sulfide Analysis

Dissolved hydrogen sulfide was analysed for aqueous samples and solid sample extracts (10 g of solid sample + 10 ml of deionized water) using a colorimetric method (Truper and Schlegel,

1964). Reagents used for the analysis were zinc acetate solution (24 g/L zinc acetate and 1 ml/L

20% acetic acid), diamine reagent (200 ml/L concentrated H2SO4, 2 g/L 4-amino-N, N- dimethylaniline), and iron alum solution (10 g/L NH4Fe(SO4)212H2O and 2 ml/L concentrated

H2SO4) (Truper and Schlegel, 1964). The principle is that the water soluble sulfide in the sample will react with zinc acetate to precipitate out zinc sulfide which is then dissolved in N,N- dimethyl-phenylenediamine solution. This solution is finally reacted with iron alum solution to give methylene blue, which is measured by absorbance at 670 nm (A670) (Fogo and Popowsky,

1949; Cline, 1969). The results from samples were compared with a standard curve to measure the concentration of dissolved hydrogen sulfide. To measure dissolved hydrogen sulfide 30 µl of the aqueous phase of samples were added to 200 µl of zinc acetate and 600 µl of water. Then

200 µl of diamine solution was added to this mixture and mixed gently. Finally 10 µl of iron alum solution was added, the mixture was vortexed and allowed to stand at room temperature for 10 to 15 minutes, after which the A670 was measured.

2.2.2. Volatile fatty acid analysis

Organic acids were analysed in field samples and lab incubations, using high performance liquid chromatography (HPLC). The organic acids analysed included lactate, acetate, propionate and butyrate. The samples were pretreated if solids or oil were present. Pre-treatment included centrifugation to remove solids and separate oil and aqueous phases, diluting the samples if they had high salt concentration (≥ 1 M) and filtration through a 0.22 µm filter (Merck Millipore

Ltd.). Once the samples were pretreated, 300 µL of sample was mixed with 20 µL of 1M phosphoric acid prior to HPLC. Organic acids (lactate, acetate, propionate and butyrate) were determined using an HPLC equipped with a Waters 2487 UV detector set at 210 nm and an organic acids column (Alltech, 250 x 4.6 mm) eluted with 25 mM KH2PO4 buffer at pH 2.5.

Samples were run with known standards and a standard curve (ranging from 2 mM to 20 mM) was made to find the concentration of unknown sample concentrations.

2.2.3. Inorganic anion analysis

Inorganic anions were analysed in field sample and lab incubations, using HPLC. The anions analysed included sulfate, nitrate and nitrite. The samples were pretreated if solids or oil were

present. Pre-treatment included centrifugation to remove solids and separate oil and aqueous phases, diluting the samples if they had high salt concentration (≥ 1 M) and filtration through a

0.22 µm filter. HPLC buffer was prepared by adding 120 ml of acetonitrile, 20 ml of butanol and

20 ml of borate/gluconate concentrate with 840 ml of MilliQ water. The borate/gluconate concentrate was prepared by adding 16 g of sodium gluconate, 18 g of boric acid and 25 g sodium tetraborate decahydrate with 250 ml of glycerol to a final volume of 1 L with MilliQ water. The HPLC buffer was filtered with an 0.45 µm filter (Merck Millipore Ltd.). Prior to the

HPLC run 400 µL of sample was mixed with 100 µL of HPLC buffer. Sulfate was analyzed by ion chromatography using a conductivity detector (Waters 2487 Detector) and IC-PAK anion column (4 x 150 mm, Waters) with borate/gluconate buffer at a flow rate of 2 ml/min. Nitrate and nitrite was analyzed by ion chromatography using a UV 220nm (UV/VIS-2489, Waters) and

IC-PAK anion column (4 x 150 mm, Waters) with borate/gluconate buffer at a flow rate of 2 ml/min. Samples were run with known standards and standard curve was made to find the concentration of unknown sample concentrations.

2.2.4. Ammonium

Ammonium was analysed using the indo-phenol method (Koroleff et al., 1969). The principle is that in alkaline solution (pH 10.5 – 11.5) ammonium ions will react to form monochloramine, which in the presence of phenol, an excess of hypochlorite and nitroprusside will form a blue coloured compound measured at 635 nm. The samples were pretreated if solids or oil were present. Pre-treatment included centrifugation to remove solids and separate oil and aqueous phases, diluting the samples if they had high salt concentration (≥ 1 M) and

filtration through a 0.22 µm filter. Reagent A was prepared by dissolving 2.9 g of phenol with 91 ml of MilliQ water and 6 ml of sodium nitroprusside (0.5 g/L). Reagent B was prepared by dissolving 2 g of sodium hydroxide in some MilliQ water in a 100 ml volumetric flask, then 1 ml of sodium hypochlorite solution (10-15%) was added and the solution was made up with MilliQ water to 100 ml. To analyse ammonium, 30 µL of aqueous sample was added to 950 µL of

MilliQ water at pH 3.0. Then 100 µl each of reagents A and B was added, the solution was vortexed and kept at room temperature in the dark for 1 hr, after which samples were measured at A635 against water. Values for A635 of samples were compared with those for known standards.

2.2.5. Methane analysis

Methane from methanogenic incubations was measured using a gas chromatograph (GC,

Hewlett Packard 5890) equipped with a flame ionization detector (FID) (Fowler et al., 2014).

The standards used were ranged from 0.5% CH4 to 10% CH4. FID detects ions formed from the combustion of gases in the sample, using a hydrogen flame, which is integrated to give a peak area value for data analysis. The operating parameters for the GC were oven temperature of

100°C, injector A at 150°C, detector B at 200°C. Helium was used as the carrier gas. The retention time for methane was usually around 90 sec. So to measure methane from methanogenic incubation, 0.2 ml from the headspace of the incubation was injected into the

GC. The peak area was compared with that of known standards (v/v) of methane.

2.2.6. Light oil composition analysis (GCMS)

The composition of light oil and diluent were analysed using a gas chromatograph mass spectrometer (Agilent GC-MS). 1 ml of sample (light oil or diluent) was added to 10 ml of dichloromethane (DCM) and shaken well. 1 µL of the DCM phase was then injected by an autoinjector (7683B series, Agilent Technologies) into the gas chromatograph (7890N series,

Agilent) which was connected to a mass selective detector (5975C inert XL MSD series, Agilent)

(Agrawal et al., 2012). The gas chromatograph had an HP-1 fused silica capillary column (length

50 m, inner diameter 0.32 mm, film thickness 0.52 µm; J&W Scientific), and helium was used as inert carrier gas (Agrawal et al., 2012). Utilization of oil components as a function of time was determined as the decrease in ratio of the peak area for a given component to that of the internal standard (Agrawal et al., 2012).

2.2.7. pH and conductivity determination

The pH of the samples were analysed using an Orion pH meter (model 370), calibrated before each analysis. Roughly 2 ml of sample was taken into a microfuge tube to measure the pH. The conductivity of the samples was measured to determine the salt concentration of the sample as molar equivalent (Meq) of NaCl by comparing with the conductivity of known NaCl concentrations. The conductivity (salinity) for samples was also analysed using the Orion pH meter (model 370) with a conductivity probe, calibrated before the analysis. Approximately 10 ml of sample was taken in to a 50 ml Falcon tube to measure the salinity of the samples.

2.3. Microbial counts and most probable number

Counts of viable SRB and APB in each sample or sample extract were assayed by inoculating commercial growth media for SRB and APB (DALYNN, Calgary) in a single dilution series up to

10-9 for each sample. Samples (1 ml) were inoculated into stoppered bottles containing 9 ml of medium and used to generate the dilution series. The count was estimated from the highest dilution showing growth after incubation for 14 days (APB) or one month (SRB) at 32˚C.

The most probable number (MPN) of SRB and APB in field samples were enumerated by a miniaturized three well MPN method, using 48 well cell culture plates (Shen and Voordouw,

2015). For MPN of SRB, 0.1 ml of sample was inoculated into 0.9 ml of Postgate B medium (Jain,

1995), and then serially diluted 10-fold to 10-8 in the same medium in triplicate wells. The plate was immediately covered with a Titer-Tops membrane (Cellstar, greiner bio-one) and incubated at 32°C inside the anaerobic hood. Wells were scored as positive when a black FeS precipitate was evident. For MPN of APB, the sample was serially diluted in Phenol Red Dextrose medium

(ZPRA-5, DALYNN Biologicals) using the same procedure as described for SRB. Growth of APB results in a color change of the medium from orange-yellow to a yellow. The MPN value was calculated by comparing the positive pattern to a probability table for MPN tests done using triplicate series of dilutions.

2.4. Corrosion Analysis

2.4.1. Coupons and beads treatment

Coupons and beads were cleaned and polished prior to corrosion experiments as per NACE protocol (NACE RP0775-2005). The coupons were A366 carbon steel (C 0.15 % max, Mn 0.06 %

max, P 0.035 % max, and S 0.04 % max). The beads were grade 200 carbon steel, diameter 3/32 inch and weight 0.055 g (Thomson Precision Ball). The coupons or beads were first polished with 400 grit sandpaper and then placed in a dibutyl-thiourea HCl solution (10 g of dibutyl- thiourea/L of 37% HCl, the solution was diluted with a equal volume of dH2O before use) for two minutes. The coupons or beads were neutralized by placing them in a saturated NaHCO3 solution for two minutes. The saturated bicarbonate solution was prepared by adding 103 g of

NaHCO3/1 L of MilliQ water. The coupons or beads were then washed with MilliQ water and then with acetone. The coupons or beads were then dried in a stream of air. After the treatment coupons or beads were either used directly for the experiment or were stored in a plastic container.

2.4.2. Weight loss method

The weight loss technique is a popular method used to determine the corrosion rate as the loss of metal with time under specific conditions. This method can be performed by using either carbon steel coupons or carbon steel beads. Typically two corrosion coupons or five corrosion beads were added per serum bottle. The coupons or beads were pretreated as per NACE protocol (NACE RP0775-2005). Once the coupons or beads were pretreated they were weighed three times using an analytical balance, and their average weight was considered as their starting weight. The coupons or beads were then used for corrosion incubations. At the end of corrosion incubations the coupons or beads were again pretreated as per NACE protocol (NACE

RP0775-2005), and weighed three times using the analytical balance to measure the weight loss

of metal over the period of time. The corrosion rate was calculated from the weight loss (ΔW in g) of the metal over the period of time.

Corrosion rate (mm/yr) = 87,600 x ΔW/(AxDxT),

Where A = area in cm2, D = density of the steel (7.85 g/cm3), and T = incubation time in hr.

2.4.3. Linear polarization resistance method

Electrochemical measurements of the corrosion rate were carried out by the linear polarization resistance (LPR) method. LPR corrosion rate measurements were taken with a portable corrosion monitoring tool (AquaMate® Portable CORRATER® LPR Corrosion Rate

Instrument). The instrument had two electrode probe (carbon steel, UNS Code – K03005). “A high-frequency a.c. voltage signal is applied between the electrodes short-circuiting Rp through the double-layer capacitance, thereby directly measuring the solution resistance. The state-of- the-art, patented SRC technology also eliminates the need for a third electrode, even in low conductivity solutions” (Rohrback Cosasco System, AquamateTM User Manual, 1999). To measure the corrosion rate of the sample, the sample was placed in a beaker or in a Falcon tube and the portable corrosion probe was inserted into the sample. The portable LPR tool will instantly give the corrosion rate measurement in (mpy) which was converted into mm/year.

3. Chapter Three: MIC in a diluent transporting pipeline

3.1. Introduction

Pipeline corrosion is influenced by physical, chemical and microbiological factors and can be divided into external and internal corrosion. The latter is influenced by the nature of the gas or fluid transported in the pipeline. There are some microbes that can influence corrosion, and the major players are considered to be sulfate-reducing bacteria (SRB), methanogens and acid-producing bacteria (APB) (Rajasekar et al., 2007). In the presence of hydrogen and/or iron,

SRB can reduce sulfate to sulfide (eq. 1) (Dinh et al., 2004). Sulfide, the product of SRB activity, contributes to corrosion. Methanogens use the proton from iron and CO2 to produce methane

(eq 2), but their product, methane, is not corrosive. APB produces organic acids, which can contribute to corrosion.

2- + 2+ 4Fe +SO4 +8H → FeS+3Fe +4H2O (eq. 1)

+ 2+ 8H + 4Fe + CO2 →CH4 + 4Fe + 2H2O (eq. 2)

For growth microorganisms require a carbon source (CO2 or an organic compound), an

2- organic or inorganic electron donor, an electron acceptor (usually SO4 or CO2 under anaerobic conditions), water and nutrients (e.g. phosphate, ammonium and trace elements). The environment inside a diluent transporting pipeline is likely anaerobic. One of the key components needed for anaerobic, methanogenic degradation of hydrocarbon is water, e.g. hexadecane can be degraded by methanogenic consortia according to equations 3 (Zengler et al., 1999; Lovley, 2000). The presence of water in diluent transporting pipelines is less than 1%, so the important question is whether growth is possible with such a low availability of water.

− + 4C16H34 + 30H2O → 49CH4 + 15CO2, 4C6H6 + 27H2O → 15CH4 + 9HCO3 + 9H (eq. 3)

Diluent is a low density; low viscosity hydrocarbon used to dilute bitumen and is produced from natural gas liquids. Diluent is dominated by light end components (≤C9). These may be difficult to degrade by microbes as such light hydrocarbons are toxic to microbes in concentrated form. The cytoplasmic membrane of a microorganism has a low permeability for polar and charged molecules, but apolar hydrocarbons can penetrate the lipid bilayer (Sikkema et al., 1995). The transfer of such molecules across the membrane is likely by diffusion (simple or facilitated), as a result these molecules would accumulate inside the cells leading to light oil toxicity. Light hydrocarbons that are toxic to microorganisms also include BTEX (benzene, toluene, ethylbenzene and xylene) and other lipophilic molecules, which may accumulate in cells leading to loss of integrity of the cell membrane (Sikkema et al., 1995). Microorganisms can utilize BTEX molecules as a carbon and energy source at low concentration, but high concentrations are toxic. Diluent or light oils can have 10- to 100-fold higher concentrations of

BTEX compared to heavy oils. Despite this potential toxicity and low water availability, microbial activity can be observed in pipelines transporting diluent as is demonstrated in the current chapter. So the purpose of this chapter is to understand whether microorganisms can survive in diluent transporting pipeline or not, if yes then how?

3.2. Materials and methods

3.2.1. Field samples

Nine samples were received from the inside of a pipeline transporting diluent (Table 3.1,

Figure 3.1), these samples were sent for microbial analysis. The dry diluent transporting line contained mostly low molecular weight alkanes (e.g. C5-C9) and some low molecular weight aromatics (e.g. toluene). The water-content of the diluent was not reported but the

specification is typically ˂1% (v/v). Samples 1 to 8 (Table 3.1, Figure 3.1) were shipped in 100 ml plastic bottles, whereas sample 9 was shipped in two Ziploc bags. Samples 1 to 7 and 9 were pigging solids; sample 8 was the transported diluent. Samples 1 to 7 represented material that was scraped from the pipe walls with a loosely fitting pig, which was easily moved through the line. Sample 9 represented material that was scraped from a section of pipe that was cut-out for repairs. This material included crusty nodules, which were tightly associated with the inside pipe surface.

3.2.2. Sample handling

Once the samples were received, they were immediately placed in an anaerobic hood containing an atmosphere of 10% CO2 and 90% N2. For solids samples 1 to 7 and 9, 10 g was mixed vigorously with 10 ml of sterile deionized water with a vortex apparatus. Following settlement by gravity, 1 ml of supernatant was taken for SRB and APB counts. The rest of the sample extracts were centrifuged and the supernatant used for chemical analysis (pH, ammonium, sulfate, sulfide, nitrate, nitrite and VFA).

3.2.3. Water chemistry

For water chemistry analyses please refer to chapter 2 (2.2.1, 2.2.2, 2.2.3, 2.2.4, and 2.2.7).

Table 3.1: Identification numbers and a brief description of the pipeline samples

Sample Description 1 Dry and very black oily solids; loose deposit 2 Dry and brown/black oily solids; loose deposit 3 As sample 2 4 As sample 2 5 As sample 2 6 As sample 2 7 Wet, black solids; loose deposit 8 Transported diluent; no visible water layer; some sediment at the bottom. Sample evaporated during anaerobic storage 9 Dry and brown solids; crusty nodules

1 2 3 4 5 6 7 8 9

Figure 3.1: Samples from the inside surface of a pipeline (1-7 and 9) and diluent (8).

3.2.4. Microbial counts

For microbial counts please refer to chapter 2 (2.3).

3.2.5. Corrosion rate measurements

The electrochemical corrosion rates of all the sample extracts were measured using the portable corrosion monitoring tool indicated in the results section. Fresh sample extracts were prepared by mixing 15 g of sample with 15 ml of deionized water. The LPR corrosion rates were then measured by submerging the duplicate cylindrical carbon steel probe ( = 4.76 mm; h =

31.92 mm) in the sample extracts. This instrument gives corrosion rates directly in mm/yr.

The corrosion rate was also determined as the weight loss of metal over the time of incubation under specific conditions. Duplicate carbon steel coupons (1.87x1.04x0.09cm) were used per experiment. The coupons were placed in 22 ml (1.5x15 cm) Hungate tubes, together with 1 g of sample and either 5 ml of CSBK medium (NaCl 1.5 g/L, KH2PO4 0.05 g/L, MgCl2.6H2O

0.54 g/L, KCl 0.1 g/L, CaCl2.2H2O 0.21 g/L, NH4Cl 0.32 g/L and resazurin 0.1 ml/L) or 5 ml of H2O.

Once the tubes were closed with butyl rubber stoppers and crimped, the headspace was flushed with 90% N2, 10% CO2. For coupons pre and post treatment refer to weight loss method chapter 2 (2.4.2).

3.2.6. Methanogenesis

The possible formation of methane was monitored in the tubes with corrosion coupons, described above. In addition, methanogenesis was monitored in Hungate tubes containing 1 g of sample and 5 ml of either CSBK medium or H2O, with a head space of 80% H2 and 20% CO2.

Hungate tubes were incubated at 30˚C and readings were taken every 7 days using Gas

Chromatography (GC). For further details refer to chapter 2 (2.2.5).

3.2.7. Community analysis by pyrosequencing

For details of DNA extraction and 16S rDNA amplification and 454 sequencing refer to chapter 2 (2.1.1.) and (2.1.2).

In some samples if enough DNA (>2 ng) was not extracted from the samples using the

FastDNA® SPIN Kit, 12- 15 mg of skim milk powder (Fluka Analytical) was added per 0.5 g of sample for improved DNA extraction. DNA was also extracted from the skim milk powder itself to act as a control. DNA sequences observed in control skim milk samples were removed from sequencing results for the samples.

3.3. Results

3.3.1. Water chemistry

The pH of all the aqueous extracts of the samples was near neutral (Table 3.2). The sulfate concentrations of the sample extracts varied from 0.05 to 1.3 mM, being lowest for sample 9 encrusted nodule (EN). Sulfide concentrations of all samples were low, with the exception of samples 3 and 5 (oily solids; 2.28 mM and 3.15 mM respectively). All the samples showed marginal presence of nitrate and no nitrite. Ammonium was present in the sample extracts at

0.02 to 1.0 mM.

Analyses of volatile fatty acids were also performed (Table 3.3). Samples contained 1.0 to 6.9 mM acetate, with the exception of sample 1 (0.18 mM). There was propionate present in most of the samples, ranging from 0.12 to 1.67 mM, except for sample 1, which was below the detection limit. Butyrate was below the detection limit for all of the samples.

3.3.2. Microbial counts

Counts for SRB were low in all samples (≥101/ml) (Table 3.4). Counts for APB were also low (Table 3.4) except for samples 7 and 9 (103/ml and 104/ ml, respectively). The low counts in the loosely associated pipe solids (samples 1 to 7), may be caused by exposure to diluent. The higher counts in sample 9 (encrusted nodules) may indicate that these are shielded from the diluent.

3.3.3. Corrosion rates by LPR

The LPR corrosion rates of aqueous extracts of the samples, measured using an

AquaMate® portable LPR device, ranged from 0.114 mm/yr to 0.290 mm/yr (Table 3.5).

Corrosion rates of this magnitude are considered good (low) (NACE, 2005), indicating that these extracts do not have high instantaneous chemical corrosion rates.

Table 3.2. Chemical analyses of aqueous sample extracts.

Sample pH Ion analyses [Concentrations are in mM] + Number Sulfate (HPLC) Sulfide (Chemical) Nitrate (HPLC) NH4 (Chemical) 1 6.83 0.104 0.099 0.014 0.88 2 6.66 0.66 0.67 0.03 0.26 3 6.74 1.17 2.28 0.06 0.02 4 6.75 1.23 0.50 0.06 0.03 5 6.87 1.29 3.15 0.07 0.02 6 6.84 0.85 1.78 0.03 0.33 7 7.35 0.165 0.13 0.01 1.01 8 NA* NA* NA* NA* NA* 9 6.75 0.05 0.09 0.02 0.40 *Not applicable, as this was a diluent sample.

Table 3.3. VFA analyses of aqueous extracts.

Sample VFA - mM Number Acetate Propionate Butyrate 1 0.18 0 0 2 3.95 0.49 0 3 6.38 0.77 0 4 6.90 0.97 0 5 6.09 0.88 0 6 4.05 0.60 0 7 1.01 1.67 0 8 NA* NA* NA* 9 4.68 0.12 0 Note NA* = Not applicable, as this was a diluent sample.

Table 3.4. Microbial counts for aqueous extracts.

Sample Number APB counts/ml SRB counts/ml 1 0 0 2 101 101 3 101 0 4 101 101 5 0 101 6 101 0 7 103 0 8 NA NA 9 104 101 Note: NA* = Not applicable, as this was a diluent sample.

Table 3.5. Corrosion rates of aqueous sample extracts by portable LPR.

Sample CR (mm/yr) Number Portable LPR 1 0.116 ± 0.011 2 0.290 ± 0.037 3 0.204 ± 0.017 4 0.139 ± 0.007 5 0.196 ± 0.022 6 0.117 ± 0.01 7 0.114 ± 0.004 8 NA 9 0.159 ± 0.022

3.3.4. Methane production during incubation of samples

Samples (1 g) were incubated in 22 ml Hungate tubes, containing 5 ml of either H2O or

CSBK medium (please refer to a detailed description of this medium) and closed with butyl rubber stoppers. Tubes also containing two carbon steel coupons were flushed with 90% N2,

10% CO2, whereas tubes without coupons were flushed with 80% H2, 20% CO2. In these tubes iron and H2 could serve as electron donor for reduction of CO2 to methane, respectively.

Methane production was only observed in the headspace of incubations with sample 9

0 (dry, brown solids, containing crusty nodules). This was irrespective whether H2 or Fe was present as electron donor for CO2 reduction or whether the tubes were amended with H2O or

CSBK. A headspace methane concentration of up to 2.0 or 2.4 mmol/L (almost 5% by volume) was observed in incubations with sample 9 with H2O or CSBK and a H2/CO2 headspace (Fig.

3.2A, B). Similarly there was significant production of methane in incubations of sample 9 with coupons and CSBK, whereas only 0.12 mM of methane was formed in incubations of sample 9 with coupons and H2O (Fig. 2C, D).

3.3.5. Weight loss corrosion rates of samples incubated in methane incubations

Weight loss was estimated at the end of incubations after 72 days (Fig. 3.2). The average weight loss for all sets of 2 coupons was 0.0040 g. The weight loss was highest for sample 9

(encrusted nodules) with CSBK (0.0158 g). This was also the only incubation condition for coupons, which gave production of significant methane (Fig. 3.2C). A significantly higher than average weight loss was also observed for sample 2 with H2O (0.0130 g). The average corrosion rate for all incubations was 0.0002 mm/yr. Those for sample 9 with CSBK and sample 2 with

H2O were 0.0011 and 0.0009 mm/yr, respectively (Table 3.6).

2500 2500

(A) H2, CO2 (B) H2, CO2 sample 1 2000 2000 sample 2 sample 3 1500 1500 sample 4 sample 5 1000 1000 sample 6

sample 7

500 500 sample 9 M)

µ control 0 0 0 50 100 0 50 100 3000 600

Methane ( (C) N2, CO2 (D) N2, CO2 2500 500

2000 400

1500 300 Coupon Coupon 1000 200

500 100

0 0 0 50 100 0 50 100

Time (Days)

Figure 3.2. Methane in the headspace of incubations of sample solids with CSBK (A, C) or H2O

(B, D). (A) and (B) had a headspace of H2 and CO2 and no coupons. (C) and (D) had a headspace of N2 and CO2; carbon steel coupons were added after 21 days as indicated (). Sample numbers are indicated.

Table 3.6. Corrosion rates of duplicate coupons incubated with samples. Corrosion rate was estimated by the weight loss method.

Sample (1 g) weight before weight after weight loss CR (mm/yr) medium (5ml) (2 coupons) (2 coupons)

sample 1 + H20 2.7426 2.7399 0.0027 0.0002

sample 2 + H20 2.6666 2.6536 0.0130 0.0009

sample 3 + H20 2.6946 2.6912 0.0034 0.0002

sample 4 + H20 2.6375 2.6332 0.0043 0.0003

sample 5 + H20 2.6377 2.6343 0.0034 0.0002

sample 6 + H20 2.6313 2.6286 0.0027 0.0001

sample 7 + H20 2.5779 2.5755 0.0024 0.0001

sample 9 + H20 2.6062 2.6028 0.0034 0.0002

control H20 2.6186 2.6121 0.0065 0.0004 Sample 1 + CSBK 2.6645 2.6617 0.0028 0.0001 Sample 2 + CSBK 2.5821 2.5803 0.0018 0.0001 Sample 3 + CSBK 2.7445 2.7425 0.0020 0.0001 Sample 4 + CSBK 2.5346 2.5327 0.0019 0.0001 Sample 5 + CSBK 2.6637 2.6619 0.0018 0.0001 Sample 6 + CSBK 2.6704 2.6683 0.0021 0.0001 Sample 7 + CSBK 2.6257 2.6242 0.0015 0.0001 Sample 8 + CSBK 2.607 2.6059 0.0011 0.0001 Sample 9 + CSBK 2.6637 2.6479 0.0158 0.0011 control CSBK 1.2899 1.2876 0.0023 0.0001 Average 2.6427 2.6387 0.0040 0.00025

3.3.6. Community composition

DNA extraction was done for all samples with the addition of skim milk powder. DNA was also extracted from skim milk powder, which contains bacteria. The most prominent taxa

(at the genus level) in skim milk powder were Streptococcus, Anoxybacillus, Pseudomonas and

Thermus. Following correction for reads representing skim milk powder, low numbers of reads remained for most sample extracts (50 – 191), except for extracts from samples 4 and 7 (3781 and 2123 reads, respectively). These reads were compared with each other and with a sequence library to determine their phylogenetic affiliation, referred to as taxa (kingdom; phylum; class; order; family; genus). A convenient way of comparing the microbial communities in the aqueous extracts of the samples is through a dendrogram (phylogenetic tree) shown in

Figure 3.3A. Samples 4 and 7 appeared related and treed separately from samples 1-3, 5, 6 and

9. At the phylum level (Fig. 3.3B) the communities consisted mostly of Proteobacteria (38-99%),

Euryarchaeota (0.3-29%) and Firmicutes (0.2-19.8%). The phylum Proteobacteria consisted of classes (Fig. 3.3C) Betaproteobacteria (8.4-99%), Gammaproteobacteria (0.3-47%) and

Alphaproteobacteria (0-1.7%). Deltaproteobacteria, the class to which most SRB belong, were absent explaining the low SRB counts observed for the samples (Table 3.4).

The Betaproteobacteria in samples 4 and 7 consisted of high fractions of the genera

Ralstonia and Pelomonas. Extracts from samples 1-3, 5, 6 and 9 all had a significant fraction

(>5%) of the phylum Euryarchaeota, genus Methanobacterium. This methanogenic taxon has a high potential of biocorrosion. Extract from sample 9, which showed methane production with

0 H2 and CO2 (Fig. 3.2A, B) and with Fe and CO2 (Fig. 3.2C), had 14% of Methanobacterium, as well as lower fractions of Methanoculleus and Methanosaeta. Members of the genus

Acinetobacter of the class Gammaproteobacteria were also present in sample extracts 1, 2, 3, 5,

6, and 9 and can also contribute to biocorrosion (Oliveira et al., 2011).

3.4. Discussion

Microbial community analyses of samples obtained from the inside of a diluent- transporting pipeline point to methanogens as possibly contributing to corrosion. Even though there was some SRB activity observed in MPNs, the presence of SRB was not significantly observed in the microbial community analysis of the samples suggesting that SRB might not be playing active role in MIC in diluent transporting pipeline. Although methanogens were present as a significant community component in most samples, active methanogenesis was only found in sample 9 (encrusted nodules). This suggests that methanogens were possibly able to survive in the encrusted nodules and proliferate (Fig. 3.4).

Hydrogenotrophic methanogens can contribute to anaerobic conversion of diluent components, provided water is present. These microbes can also use iron (Fe0) as an electron donor (Eq. 2). So in a diluent transporting pipeline microbes can survive in a nodule, which gives a favourable environment for microbial growth which shields from the harsh environment in presence of diluent (Figure 3.4). It would be interesting to know more about the composition and location of crusty nodules, which were tightly associated with the metal surface, i.e. to which extent did these protrude into the steel wall and were these composed of iron carbonate

(Figure 3.4)? Their water content and the possibility that these shield resident microbes from the toxic nature of diluent also needs to be investigated.

The weight loss corrosion rates found were very low (<0.02 mm/yr). However, it is significant that the encrusted nodules (sample 9) had the highest corrosion rate and were also

the only sample with active methanogens. It is conceivable that much more active nodule may be found on the pipe surface in situ and that these contribute to localized corrosion of the pipe wall. Further study on understanding the composition of these nodules and their location within the pipe would give a better idea of the mechanism of these nodule formations.

(A) Dendrogram (B) Phylum (C) Class

Sample 9 Sample 1 Sample 6 Sample 3 Sample 5 Sample 2 Sample 7 Sample 4

0 20 40 60 80 100 0.4 0.3 0.2 0.1 0.0 0 20 40 60 80 100 Proteobacteria Euryarchaeota Betaproteobacteria Gammaproteobacteria Firmicutes Actinobacteria Methanobacteria Bacilli Bacteroidetes Planctomycetes Actinobacteria Methanomicrobia Other phyla Alphaproteobacteria Sphingobacteria Flavobacteria Other classes

Figure 3.3. Pyrosequencing analysis of 16S rRNA genes showing (A) a dendrogram comparing community compositions, and relative abundances of (B) major phyla and (C) major classes.

Nodule

methanogens Pipe wall

Pit

Figure 3.4: Depiction of how microbes survive in diluent transporting pipeline under nodule formation.

4 Chapter Four: Potential of biocorrosion and souring in a light oil producing field in

Papua New Guinea

4.1. Introduction and samples received

Papua New Guinea (PNG) is a country that is located north of Australia. The economy of

PNG is dominated by natural resource projects which include mining, oil and gas (APEC, 2013).

Often in oil extraction operations, water is injected into subterranean petroleum reservoirs to enhance the oil recovery (Sharif, 2011). Secondary oil recovery by injecting water to extract oil can lead to souring, as sulfate from injection water could be reduced to sulfide by SRB (Callbeck et al., 2013). Souring can cause an increase in the sulfide level of produced oil, water and gas, which may eventually lead to increase in corrosion risk in the pipeline transporting these products (Okoro et al., 2014). Both souring and corrosion can lead to catastrophic effects on pipelines transporting these products, as well as the oil and gas extraction operations in general.

To prevent souring in oil reservoirs, biocide is often added to injection water (Myhr et al., 2002). However this kind of practice could be quite expensive and biocide could be inactive after reaction with biofilms and minerals (Widdel, 1988). Also, biocide may decompose after a certain amount of time, which could yield additional substrate for SRB (Sunde et al., 1990).

Sulfate removal from the injection water by various filtration methods is an option, but again this technology is very expensive. To mitigate souring in water injected oil extraction, nitrate injection is the most commonly used method. Nitrate addition in injection water may stimulate a competing group of microorganisms, nitrate reducing bacteria (NRB), which may result in reduction of sulfide production (Myhr et al., 2002). Again whether nitrate injection is a feasible

option or not would depend on the organic composition of the oil. We received samples from an on-shore conventional oil field operation in Papua New Guinea to study the potential for souring and corrosion problems.

Previous work was done in 2011 on six samples from the Kutubu and Gobe oil fields in

Papua New Guinea with the objective to determine the cause of souring (the production of H2S by reduction of sulfate by SRB) in these fields (Agrawal et al., 2011).

The samples had low sulfate (0 to 1 mM) and high acetate (5 to 14 mM) concentrations.

Significant activity of heterotrophic nitrate-reducing bacteria (hNRB) was observed when waters were amended with nitrate, both in the presence or absence of added oil. These hNRB used the acetate in these waters as electron donor for reduction of added nitrate. Reduction of added sulfate was not observed either in the presence or absence of added oil. Souring was only observed after addition of heptamethylnonane (HMN), which was added to remove water dissolved oil components. Experiments suggested that light oil might be inhibiting SRB activity.

Microbial community analyses indicated high fractions of (i) the Gammaproteobacteria

Pseudomonas or Stenotrophomonas (fermentative bacteria or hNRB), of (ii) Clostridia (acetic acid-producing, fermentative bacteria), and of (iii) the Deltaproteobacteria Desulfovibrio or

Desulfobulbus (fermentative bacteria or SRB). Methanogens were absent. In view of the high acetate concentrations in all field waters, souring control by addition of nitrate was not considered feasible, as hNRB would rapidly oxidize the available acetate.

Since this initial work, seventeen samples were received from PNG fields on December

6, 2013 and three samples were received from PNG fields on January 3, 2014 (Figure 4.1, Table

4.1). Of these, 15 were received in 1 L glass bottles (PNG1-PNG10, PNG12-PNG15 and PNG17).

PNG5 and PNG10 broke during transport and the remaining contents were transferred to 1 L plastic bottles (Figure 4.1). PNG11 was sent in a 500 ml glass jar, PNG16 in 3 separate plastic bottles (200 ml), PNG18 in a 1 L amber coloured bottle, PNG19 in a 500 ml plastic bottle, and

PNG20 in a 1 L metal container. Once they were received, the samples were stored in an anaerobic hood with an atmosphere of 90% N2 and 10% CO2 (N2-CO2). The samples, when received, were filled to the rim of the 1 L bottle to avoid any exposure to oxygen.

The samples were collected from an on-shore conventional light oil producing field in

Papua New Guinea (PNG). The sampling locations have been divided into two major parts (i)

Agogo processing facility (APF) and Central processing facility (CPF), and (ii) Gobe processing facility (GPF). The samples collected include produced water (PW) samples (PNG1 and PNG2) from Agogo and Moran field (Appendix: Figure S1) which gets transported to APF (PNG3 and

PNG4). PW samples were also collected from Kutubu fields (PNG6 and PNG7, Figure S1); these waters along with APF waters get transported to CPF for processing. Samples were also collected from CPF, which includes facility water (FW, PNG8 and PNG18), injection water (IW,

PNG9 and PNG10), sludge solids (SS, PNG11) and filtered solids (FS, PNG19). PW samples were also collected at Gobe Main (PNG12) and South East Gobe fields (PNG13 and PNG14)

(Appendix: Figure S2). The PW from Gobe field gets transported to Gobe processing facility

(GPF) for treatment. Samples were also collected from GPF, which include IW (PNG15 and

PNG17) and pigging solids (PS, PNG16). A detailed survey of these samples has been provided by the Company (Appendix: Table S1), together with a field diagram indicating where samples were taken (Appendix: Figures S1 and S2). Corrosion damage hotspots were also indicated in these field diagrams.

As shown in the Appendix: (Figures S1 and S2), PNG fields experience corrosion problems in their above ground operations, both in processing facilities as well as in pipelines near production wells. The objective of this study is to understand whether this corrosion was influenced by microbial activity or not. These lines are also treated with biocides, so it will be interesting to study whether there is any microbial activities in these lines. PNG oil fields are light oil producing oil fields (46˚ API), so another aspect which will be explored in this chapter is whether this light oil has any toxic impact over biogenic sulfide production.

Based on the information provided, the samples received were divided in four groups:

(I) 10 PW samples with oil; (II) 4 IW or FW samples from the CPF, the difference being that IW will likely flow, whereas FW may be stagnant; (III) 2 IW samples from the GPF; (IV) 4 solid samples of various kinds including SS, PS and FS. Tables with results for these samples will be presented for these groups to facilitate interpretation of the results.

1 2 3 4 5 6 7 8 9 10

11 12 13 14 15 16 17 18 19 20

Figure 4.1. Picture of samples received for this study, on December 2013 (1-17) and January 2014 (18-20) [Note: The pictures for the samples were taken on later date, the sample when received were filled to the rim reduce the exposure to oxygen.]

Table 4.1: Name, label and appearance for 2013/2014 samples.

Sample Group Sample Label Transcription Sample Appearance (Fig. 1) Name Clear water sample with oil layer on I PNG1_PW ADD1 top I PNG2_PW Moran 9 Same as PNG1_PW Brown water sample with oil layer I PNG3_PW Upstream Agogo Separator (APF) on top I PNG4_PW Upstream Moran Separator (APF) Same as PNG1_PW I PNG5_PW APF-CPF Trunkline Same as PNG1_PW I PNG6_PW IDT15 Same as PNG1_PW I PNG7_PW IDD4 Same as PNG1_PW I PNG12_PW GM4 Same as PNG1_PW I PNG13_PW SEG11 Same as PNG1_PW I PNG14_PW SEG12 Same as PNG1_PW Water sample with yellow color; no II PNG8_FW CPF Slop oil Tank oil II PNG9_IW CPF Injection Water Tank Clear water sample; no oil II PNG10_IW CPF Re-injection water (IDT3) Same as PNG8_FW II PNG18_FW CPF Skim Tank Water Outlet Same as PNG9_IW III PNG15_IW GPF reinjection water Same as PNG8_FW III PNG17_IW G3X Same as PNG8_FW IV PNG11_SS CPF Sludge Storage Tank Black solids with oil and water G3X reinjection line (pigged IV PNG16_PS Black solids with oil and water solids) IV PNG19_FS IDT3/IDT19, Filter Pod Wet solids, grey coloured Kumul Pig Receiver (Marine IV PNG20_PS Black oily solids Terminal) Note: A more extensive description of these samples provided by the company is given in Table S1 (Appendix).

4.2. Materials and methods:

4.2.1. Sample handling

Once the samples were received at the University of Calgary, they were immediately placed in an anaerobic hood containing a 10% CO2 and 90% N2 atmosphere. The liquid samples were analysed by taking the aqueous portion of the sample. Solid samples (15 g) were mixed vigorously with 15 ml of sterile deionized water and the supernatants (the solid sample extracts) were used for the analysis.

4.2.2. Water chemistry

For water chemistry analyses please refer to chapter 2 (2.2.1, 2.2.2, 2.2.3, 2.2.4, and

2.2.7).

4.2.3. Most probable numbers (MPNs)

For method details for MPN please refer to chapter 2 (2.3).

4.2.4. Corrosion rate measurements

The corrosion rate was measured by the weight loss method. Samples (20 ml) were placed in 50 ml serum bottles together with 20 acid pre-treated iron beads (1102 mg, 3.55 cm2).

For samples PNG11_SS and PNG16_PS 20 ml of mixed solids, oil and water were used. Acid pretreatment was as per NACE protocol RP0775-2005. The beads were weighed three times using an analytical balance and the average weight was used as the initial weight of the beads.

Sodium sulfide (20 l of 1M Na2S) was added and the serum bottles were then closed with butyl rubber stoppers. This procedure was done in a Forma anaerobic hood with an atmosphere of

85% N2, 10% N2 and 5% H2. The samples were then incubated for 15 to 18 days at room temperature while lying flat on the platform of an orbital shaker, shaking at 150 rpm. At the end of the incubation beads were taken out of serum bottle were treated as NACE protocol

RP0775-2005. The beads were then weighed to determine weight loss. The determined value for beads incubated in acid for 10 min (W10) was corrected for weight loss during the 10 min acid treatment, by using the formula: W0= W10 x A562,0/A562,10. The corrosion rate (mm/yr) was then calculated as CR = 87,600 * W0/ATD, where A was the surface area of the beads

(3.55 cm2), T was the incubation time (h) and D was the density of iron (7.85 g/cm3).

4.2.5. Methanogenesis and acetogenesis

The concentrations of methane in the headspace and of acetate in the aqueous phase of serum bottles with iron beads were measured at the end of the incubations described in the previous section. In addition, separate measurements of methane and acetic acid formation from H2 and CO2 were done by incubating 20 mL of each sample in 50 mL serum bottles with a headspace of 80% (vol/vol) H2, 20% CO2. Samples were incubated at room temperature while shaking on the orbital shaker at 150 rpm. Periodically, 0.7 mL of the aqueous phase was sampled to measure acetate using HPLC and 0.2 mL of the gaseous phase was sampled to measure methane production using GC. Gas consumption was measured by replacing the headspace of the serum bottles with a known volume of 90% N2, 10% CO2 gas at atmospheric pressure. For further method details please refer to chapter 2 (2.2.5).

4.2.6. Microbial community composition

For details of DNA extraction and 16S rDNA amplification and sequencing refer to chapter 2 (2.1.1 and 2.1.2).

4.3. Results and discussion

4.3.1. Water chemistry

The produced water samples (Table 4.2: Group I, N= 10) had similar water chemistries with an average pH = 7.2, a salinity of 0.24 Meq NaCl, an average sulfate concentration of 0.80 mM (range 0 to 1.77 mM), no sulfide (with the exception of PNG3_PW) and an average acetate concentration of 5.85 mM (range 2.1 to 13.2 mM). The injection waters from the Gobe field

(Table 4.2: Group III, N=2) had near identical properties (average pH = 7.2, salinity 0.2 Meq

NaCl, 0.88 mM sulfate, 0.5 mM sulfide and 5.7 mM acetate). In contrast, injection and facility waters from the CPF (Table 4.2: Group II, N=4) had a higher average sulfate concentration (3.3 mM, range 1.9 to 6.2 mM). The high value was for PNG8_FW Slop Oil Tank (Appendix Table S1).

These samples also had a very high average acetate concentration of 40.2 mM (range 7.2 to

67.7 mM, the high value being again for PNG8_FW Slop Oil Tank). Propionate concentrations were not elevated (average values of 0.84, 0.52 and 0.55 mM for Groups I, II and III). The solids samples (Table 4.2, Group IV, N=4) were quite diverse. The aqueous extracts from PNG11_SS,

PNG16_PS and PNG19_FS had low salinity (0 Meq NaCl), whereas that from PNG20_PS had a high salinity (1 Meq NaCl). The latter solids must thus have included salt precipitates. These also had an exceptionally low pH of 5.0. Sulfate (0.9 mM) and sulfide (0.5 mM) were only found in extracts from PNG19_FS (filtered solids). The average acetate concentration was only 2.7 mM.

Because the average sulfate concentration in produced waters (0.8 mM) was much lower than CPF waters (3.3 mM), the data suggest influx of sulfate in the CPF. The source of this sulfate influx is unknown.

4.3.2. MPNs

Determination of MPNs for APB and SRB indicated the presence of 1.5x103/ml to

4.3x106/ml of APB in all produced waters, except PNG6_PW. In contrast, no SRB were found in any of the produced waters, except in PNG_14PW, which had 2.4x105/ml. No SRB or APB were found in injection or facility waters (Table 4.2 groups II and III). For the SRB these results are in agreement with observations for the 2011 samples, that no sulfate reduction occurred at 30 or

60oC, when produced or injection waters were incubated with PNG oil and sulfate. The absence of APB in injection and facilities waters, which were present in produced waters, can likely be credited to the use of biocides in above ground operations (Appendix Figures. S1 and S2: CPF and GPF).

Sludge solids (PNG11_SS) and pigging solids (PNG16_PS) had significant numbers of APB

(9.3x104/ml and 2.4x106/ml) and even higher numbers of SRB (2.3x108/ml and 4.3x107/ml, respectively), as indicated in Table 4.2. However, filtered solids removed from injection water

(PNG19_FS) were devoid of APB or SRB. This is likely in agreement with the fact that waters upstream and downstream from the filter (Fig. S1: PNG9_IW and PNG10_IW) were also devoid of these. Pigging solids from the Kumul Pig Receiver Marine Terminal (PNG20_PS) also lacked

APB and SRB (Table 4.2). The APB found in produced waters can clearly ferment glucose to organic acids (e.g. acetic acid), as this is the basis for the APB assay. This can include bacteria

from the class Clostridia, which were abundant in PNG samples as observed by earlier pyrosequencing surveys.

4.3.3. Corrosion rates

The corrosion rates (CRs) were measured by incubating 20 ml of sample with 20 iron beads

(55.1 mg each) under shaking for 14 to 18 days under a head space of 85% N2, 10% CO2 and 5%

H2. CRs were determined from the measured weight loss.

The average of the weight loss CRs for produced waters (Table 4.3: Group I) was

0.0220.006 mm/yr. The average values were somewhat lower for injection and facility waters

(Table 3: Groups II and III, 0.0040.001 and 0.0180.007 mm/yr). The highest average corrosion rates were observed for the solids samples (Group IV: 0.0360.004) mm/yr. This group also had the highest MPNs for SRB (Table 4.2).

Table 4.2: Water chemistry and MPN analysis of 2013/2014 PNG samples; PW is produced water, FW is facility water, IW is injection water, SS is sludge solids, PS is pigging solids, FS is filtered solids. A negative MPN result (no growth in any of the wells) is indicated as “<30”.

Ion analysis – Grp NaCl VFA – mM MPNs Sample pH mM (Meq) Sulfate Sulfide Acetate Propionate APB/ml SRB/ml I PNG1_PW 7.45 0.25 0.93 0 4.23 0.56 1.5x103 <30 I PNG2_PW 7.67 0.23 0.55 0 7.97 1.02 2.4x105 <30 I PNG3_PW 5.81 0.49 1.77 2.68 4.44 3.21 4.3x103 <30 I PNG4_PW 6.51 0.25 0.58 0 13.19 0.94 4.3x106 <30 I PNG5_PW 7.11 0.3 0.87 0 6.82 0.6 2.4x107 <30 I PNG6_PW 7.4 0.17 0.74 0 5.68 0.46 < 30 <30 I PNG7_PW 7.75 0.1 1.01 0 2.11 0.28 4.3x105 <30 I PNG12_PW 7.47 0.18 0.82 0 5.22 0.75 4.3x105 <30 I PNG13_PW 7.46 0.21 0.68 0 4.51 0.6 2.4x106 <30 I PNG14_PW 7.35 0.2 0 0 4.34 0 4.3X103 2.4x105 II PNG8_FW 6.54 0.18 6.29 0 67.67 0.39 <30 <30 II PNG9_IW 6.92 0.15 2.45 0 33.98 0.57 <30 <30 II PNG10_IW 6.92 0.2 2.72 0 52.15 0.61 <30 <30 II PNG18_FW 7.29 0.16 1.89 0 7.15 0.49 <30 <30 III PNG15_IW 7.01 0.2 0.84 1.07 6.37 0.54 <30 <30 III PNG17_IW 7.33 0.21 0.91 0 5.09 0.56 <30 <30 IV PNG11_SS 7.08 0 0 0 0.65 0.17 9.3x104 2.4x108 IV PNG16_PS 6.8 0 0 0 6.09 0 2.4x106 4.3x107 IV PNG19_FS 7.39 0.001 0.89 0.5 3.81 0.08 <30 <30 IV PNG20_PS 4.96 1.06 0 0 0.1 0 <30 <30

Table 4.3: Corrosion rates for PNG samples.

Group Sample CR (mm/yr) I PNG1_PW ND I PNG2_PW ND I PNG3_PW 0.032 I PNG4_PW 0.024 I PNG5_PW 0.014 I PNG6_PW 0.022 I PNG7_PW 0.026 I PNG12_PW 0.017 I PNG13_PW 0.025 I PNG14_PW 0.017 Av ± SD 0.022±0.006 II PNG8_FW 0.003 II PNG9_IW 0.005 II PNG10_IW 0.003 Av ± SD 0.004±0.001 III PNG15_IW 0.021 III PNG17_IW 0.019 Av ± SD 0.020±0.001 IV PNG11_SS 0.137 IV PNG16_PS 0.098 Av ± SD 0.119±0.028

Table 4.4: Methane and acetic acid production in incubations of 2013/2014 PNG samples in the presence of iron beads.

Methane Samples Initial Acetate (mM) Final acetate (mM) Change (mM) (µM) PNG1_PW 13 4.23 6.41 2.18 PNG2_PW 35 7.97 7.71 -0.26 PNG3_PW 9 4.44 0 -4.44 PNG4_PW 32 13.19 16.9 3.71 PNG5_PW 36 6.82 7.81 0.99 PNG6_PW 23 5.68 5.75 0.07 PNG7_PW 2 2.11 2.05 -0.06 PNG12_PW 0 5.22 5.23 0.01 PNG13_PW 1 4.51 4.44 -0.07 PNG_14PW 18 4.34 5.98 1.64 PNG8_FW 0 67.67 54.61 -13.06 PNG9_IW 0 33.98 32.43 -1.55 PNG10_IW 0 52.15 36.96 -15.19 PNG15_IW 32 6.37 6.26 -0.11 PNG1_IW7 25 5.09 4.87 -0.22 PNG11_SS 275 0.65 - - PNG16_PS 3 6.09 2.83 -3.26

4.3.4. Methanogenesis and acetogenesis

Methane was recorded in the headspace of serum bottles (85% N2, 10%, CO2, 5% H2), containing samples incubated with iron beads for corrosion rate analysis. The aqueous acetate concentrations of these samples before and after incubation were also determined (Table 4.4).

Methane production was insignificant, except for sample PNG11_SS, which produced

275 µM (Table 4.4). More acetate was used than was formed during these incubations, especially in samples PNG8_FW and PNG10_IW, which saw a decrease in acetate concentration of 13 and 15 mM, respectively.

The formation of methane and acetic acid was also determined for incubations of 20 ml of sample without iron beads but with a headspace of 80% H2 and 20% CO2. The use of head space gas, which was replaced with 90% N2 and 20% CO2, was also recorded. Again only sample

PNG11_SS produced up to 200 µM of methane following 22 days of incubation (Figure 4.2).

Nevertheless, although no methane was formed from the headspace H2 and CO2, samples PNG4_PW, PNG5_PW, PNG7_PW , these used significant headspace gas, as did sample

PNG11_SS. Samples PNG14_PW and and PNG16_PS also showed significant gas uptake (Figure

4.3). All of these samples, except PNG14_PW, showed significant production of acetic acid, which can also be formed from H2 and CO2 by acetogens like the Clostridia (Table 4.5). Note that significant gas uptake and acetogenic activity did not correlate with the presence of high acetate in the samples, which was observed for PNG8_FW, PNG9_IW and PNG10_IW (Table

4.2).

250

PNG 1 PNG 2

200 PNG 3

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( PNG 5

o PNG 6 i

t 150

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t PNG 7

n e

c PNG 8

n o

C PNG 9

e 100

n PNG 10

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e PNG 11 M PNG 12 50 PNG 13 PNG 14 PNG 15 0 PNG 16 0 5 10 15 20 25 30 35 40 PNG 17 Time (Days)

Figure 4.2: Methane production of samples incubated with an 80%H2/20%CO2 head space at room temperature over time. Data shown are for single incubations

O 35

, 30

% 0

9 25

e 20

e 15

s d

a 10

m 5

1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7

1 1 1 1 1 1 1 1

G G G G G G G G G

G G G G G G G G

N N N N N N N N N

P P P P P P P P P

N N N N N N N N

P P P P P P P P

Fig. 4.3: Volume of headspace used during incubation of samples with 80% H2/20% CO2, as measured by adding 90% N2, 10% CO2 (ml) from a syringe until a pressure of 1 atm was restored.

Table 4.5: Acetate formation by 2013/2014 samples incubated with 80%H2 and 20%CO2 in the headspace. The samples indicated in bold showed significant uptake of headspace gas (Fig. 4.3). Final acetate was determined after 35 days.

Group Sample Initial Acetate (mM) Final acetate (mM) Change (mM) I PNG1_PW 6.5 6.2 -0.3 I PNG2_PW 7.9 7.6 -0.3 I PNG3_PW 7.4 7.2 -0.2 I PNG4_PW 20.3 32 11.7 I PNG5_PW 8 27.8 19.8 I PNG6_PW 6 7.1 1.1 I PNG7_PW 2.7 12.4 9.7 I PNG12_PW 5.6 6.8 1.2 I PNG13_PW 4.6 5.6 1 I PNG14_PW 7.3 9.1 1.8 II PNG8_FW 50.1 56.9 6.8 II PNG9_IW 29.4 30.1 0.7 II PNG10_IW 32.5 32.4 -0.1 III PNG15_IW 6 8 2 III PNG17_IW 6.5 6.2 -0.3 IV PNG11_SS 25.8 37.3 11.5 IV PNG16_PS 6.1 16.6 10.5

4.3.5. Microbial community compositions

DNA extractions were done for all the samples followed by PCR amplification. The 16S amplified sequences were sent for pyrosequencing to the Genome Quebec and McGill

University Innovation Centre, Montreal, Quebec. The reads obtained following pyrosequencing were compared with each other and with a sequencing library to determine their phylogenetic affiliation, referred to as taxon (Table 4.6: phylum or class; genus). A convenient way of comparing the microbial communities in the aqueous extracts of the samples is through a dendrogram (phylogenetic tree) shown in Fig. 4.4. Sample PNG 5 appears to be separated from rest of the samples in phylogenetic tree. At the phylum level, the communities consist mostly of

Proteobacteria (1.8-99.2%), Euryarchaeota (0-71.9%) and Firmicutes (0-96%). The phylum

Proteobacteria consisted of classes Gammaproteobacteria (1.5-99.1%), Deltaproteobacteria (0-

19%) the class to which most SRB belong, Betaproteobacteria (0-21%) and Alphaproteobacteria

(0-6.1%).

The Gammaproteobacteria in most of the samples were dominated by Pseudomonas, with exception for PNG18, PNG19 and PNG20 which also showed some Escherichia (Table 4.7).

Samples PNG6, PNG8, PNG9 and PNG10 all had high fractions of the phylum Euryarchaeota, genus Methanoculleus, Methanosarcinales, Methanobacterium and Methanosaeta, whereas the phylum Euryarchaeota was prominently present in PNG14 (genus: Methanolobus) and

PNG11 (genus: Methanobacterium and Methanosaeta). Methanogenic taxa have high potential for biocorrosion (Dinh et al. 2004). Sample PNG11, which showed methane production with H2

0 and CO2 (Fig. 4.2) and with Fe and CO2 (Table 4.4), had 10% of Methanobacterium and 11% of

Methanosaeta. Members of the genus Thauera of the class Betaproteobacteria were also present in samples PNG6, PNG8, PNG9 and PNG10. Members of the genus Thauera are able to degrade toluene anaerobically (Leuthner et al. 2000). Members of the class Paracoccus of the genus Alphaproteobacteria showed some presence in samples PNG6, PNG8, PNG9, and PNG10.

Members of the genus Paracoccus are known for their nitrate reducing properties, and are also able to metabolise compounds like hydrogen and sulfur (Baker et al. 1998). Genus

Acetobacterium of the class Firmicutes was rare in most of the samples with an exception of sample PNG5, where it was dominating by 96%. Members of genus Acetobacterium are known for producing acetic acid anaerobically as their metabolic by-product. Perhaps as a result sample PNG5 showed the highest increase in acetate concentration when it was incubated with

H2-CO2 atmosphere (Table 4.5). Sample PNG14 showed significant presence of genus

Desulfobulbus (16%), and it also showed significant presence of genus Methanolobus (29%).

Members of genus Desulfobulbus are sulfate-reducing bacteria known for oxidizing propionate, whereas Methanolobus are methanogenic archaea.

(A) (B) (C)

Figure 4.4: Pyrosequencing analysis of 16S rRNA genes showing (A) a dendrogram comparing community compositions, and relative abundances of (B) major sub-phyla and (C) major classes for 2013/2014 samples.

Table 4.6: Distribution of sequences over taxa for 2013/2014 samples. The numbers are fractions (%) of the numbers of pyrosequencing reads for each taxon. The distributions of individual samples are presented in the order (left to right) of Fig 4.4.

4.4. Conclusions:

Twenty samples were obtained from oil fields in Papua New Guinea producing light oil.

These represented produced water with oil (PNG1–PNG7, PNG12-PNG14), injection water

(PNG9, PNG10, PNG15 and PNG17), processing facility water (PNG8 and PNG18), storage tank sludge solids (PNG11), injection water filtered solids (PNG19) and pigging solids from an injection water line (PNG16) and from the oil export line ending in the marine terminal

(PNG20).

The samples had low ionic strength (0-0.49 Meq of NaCl) with the exception of the pigging solids from the marine terminal (1 Meq of NaCl). The produced water samples (all with oil) had a lower sulfate concentration (0.80.4 mM; N=10) than the injection and facility water samples (all without oil) from the Central Processing Facility (CPF), which had (2.32.0 mM;

N=4). Injection water samples from the Gobe Processing Facility (GPF) had (0.90.05 mM; N=2).

These data indicate an input of sulfate into the CPF waters and the source of this sulfate is unknown. It is important to find the source of the sulfate as this could cause souring in the above ground operations. Produced waters had high acetate concentrations (5.83.0 mM;

N=10), similar to injection waters of the GPF (5.70.9 mM; N=2). Injection and facility water samples from the CPF had very high acetate concentrations (40.226.0 mM; N=4), whereas solids samples had low acetate concentrations (2.72.8 mM; N=4). It was observed that CPF water had high sulfate and high acetate concentrations which could lead to souring as well as high corrosion risk, provided there were acetate utilizing SRB present in these waters. The microbial community data did not show the presence of any acetate utilizing SRB in CPF waters.

Produced water samples had most probable numbers (MPN) of acid-producing bacteria

(APB) from 103/ml to 107/ml. Sulfate-reducing bacteria (SRB) were below detection (<30/ml), except in PNG14_PW (SE Gobe Iagifu C, 2.4x105/ml). Injection and facility waters from the CPF and the GPF had no detectable APB or SRB, indicating that biocide dosing was working. Sludge solids from the CPF sludge solids storage tank (PNG11_SS) and pigging solids from the G3X injection line (PNG16_PS) had high MPNs of SRB (2.4x108/ml and 4.3x107/ml). low numbers of

SRB in PW could be due to light oil toxicity and high SRB in sludge could be due to being shielded from the toxic effect of the light oil. It is hard to predict that the low numbers of SRB are due to light oil toxicity or biocide treatment. Toxicity effects of light oil will be explored in chapter 6. General weight loss corrosion rates were 0.0230.006 mm/yr for produced waters

(N=10), 0.0080.001 mm/yr for injection and facility waters from the CPF (N=3), and

0.0200.001 mm/yr for injection waters from the GPF (N=2). The highest rates were observed for sludge solids sample PNG11_SS (0.038 mm/yr) and for pigging solids sample PNG16_PS

(0.033 mm/yr). These also had the highest MPNs for SRB. So, based on the corrosion rate results, it could be conceivable to say that there could be MIC in these pipelines and microbes surviving in sludge could be shielded from biocide as well as light oils toxic effects.

No methanogenic activity was found to be associated with weight loss corrosion, except for PNG11_SS. This was also the only sample producing methane from added H2 and CO2. From the microbial community data it was observed that methanogens were present in most of the samples, but there was no active methanogenesis observed expect in this one sludge sample.

So it is possible that methanogens in sludge could be shielded from the toxic effect of light oil and would proliferate. Acetogenic activity from H2 and CO2 was observed in 5 samples; it did

not correlate with high acetate concentrations in the samples. The sample PNG5_PW with the highest acetogenic activity had a high fraction (96%) of Firmicutes/Acetobacterium. Again, it’s hard to say whether the high acetate concentration found in CPF water could be cause of the high acetogenic activity of the PW. But the acetogenic activity of PW was not hindered by the presence of light oil.

Overall, the results showed that SRB numbers were low in waters but can be significant in tank sludges and pipeline solids. These also had the highest weight loss corrosion rates, suggesting that control measures, which are successful in the flowing parts of the operation, may not reach these deposits. Again it’s hard to predict the distinct culprit of MIC, whether SRB were the key players or acetogens. More work is required in understanding the mechanism of

MIC in the PNG field.

5. Chapter Five: Is THPS a possible source of sulfate for the growth of SRB in oil processing

facilities in Papua New Guinea?

5.1. Introduction

Souring can cause increases of sulfide concentration in PW as well as corrosion problems in pipeline transporting these PW. Souring can lead to negative effects like precipitation of metal sulfide, which are corrosive on pipe surfaces. Suspended metal sulfide could also stabilize the oil-water emulsion resulting in less efficient oil-water separation

(Grigoriyan et al., 2009). To protect the pipelines in above ground operation from corrosion and adverse effects of souring, biocide, corrosion inhibitors and sulfide scavengers are often injected into the pipelines (Voordouw, 2011). Many of these added chemicals could contain components, which may serve as substrates for increased microbial growth, and increased corrosion risk (Sunde et al., 1990). In a study conducted on a brackish water transporting pipeline, it was observed that the oxygen scavenger (sodium bisulfite) could be causing an increase in microbial activity post injection and could eventually be leading to pipeline failure down the line (Park et al., 2011). So the selection of additives to above ground operational pipelines could be quite crucial in souring and corrosion control.

PNG above ground field operations are also subjected to biocide treatment to control the SRB population and to avoid any corrosion failures. The biocide used at PNG above ground field operation is tetrakis hydroxymethyl phosphonium sulfate (THPS). THPS is used in pipelines to solubilize iron sulfide and as a biocide to kill SRB (Trahan, 2014). THPS is able to reduce the iron sulfide deposits from the pipe surface by solubilizing the deposit and forming a water soluble THP iron aluminium complex (Trahan, 2014). In the oil and gas industry, THPS is widely

used as a biocide, but it has been observed that THPS can react with calcium carbonate and form calcium sulfate (Wang et al., 2015). Also, THPS in the presence of aluminium chloride can increase the corrosion rate by three times (Wang et al., 2015). So it will be interesting to observe how THPS behaves in above ground operations of the PNG field.

Sampling in the field is a good option to save time as well as maintain the microbial integrity of the sample as the microbial community in samples may change over the period of transportation time. One option to maintain the microbial integrity of a sample is to freeze it at the sampling site by liquid nitrogen or dry ice and keep it frozen until microbial analysis (Wang et al., 2014). In this chapter, weight loss corrosion incubations will be inoculated on site to understand whether it impacts the corrosion rate of sample as compared to inoculations done in the lab after samples are shipped. This data will be compared with 2013/2014 corrosion incubations. Evaluation of samples from 2013/2014 showed high presence of acetate in CPF waters, so there will be further study (water chemistry and microbial community analysis) conducted in this chapter to understand this increase. Another objective that will be explored in this chapter is to understand whether THPS can account for the increase in sulfate levels of

CPF waters.

To achieve the objectives of the study, fifteen samples were received from PNG fields, thirteen on December 16, 2014 and two on February 6, 2015. Unfortunately, the bottles containing 4 liquid samples of the December 16 shipment had broken. Of the eleven remaining samples that we received in good condition, six water samples were received in 1 L glass bottles, filled to the rim, four solid samples were received in plastic jars and one solid sample was received in a 1 L glass bottle. Once the samples were received they were stored in the

anaerobic hood with an atmosphere of 90% (v/v) N2 and 10% CO2 (N2-CO2). We also shipped eight serum bottles to the field, containing iron beads or carbon steel coupons, bisulfite and an

N2-CO2 atmosphere, for inoculations on-site for corrosion incubations. These were also received on December 16, 2014 with one serum bottle having broken during transport. The samples were named according to sample location with the number indicating the sampling location point on the PNG field schematics (Appendix: Figures S3 and S4). For details on sampling location refer to chapter 4, 4.1. There were four PW collected, of which one was collected from

Agogo field (9_UAS, broken), one was collected from Moran field (10_UMS, broken) and two from Kutubu field (7_IDD4, broken and 8_ IDT15). There were six CPF waters collected which includes two IW (1_WIT and 2_IDT3, broken), and four FW (3_OSW, 4_SDP, 5_IS and 6_CSTF).

There were five solid samples collected as well, one PS from CPF (14_CPR) and four SS from GPF

(11_FH, 12_PSVD, 13_IWS and 15_GPS).

Based on the information provided for the received samples these were divided into three groups: (I) 4 PW samples without oil (3 broken); (II) 6 IW or FW samples from the CPF (1 broken), the difference being that IW will likely flow, whereas FW may be stagnant; (IV) 5 solid samples which included SS and PS. Tables with results for these samples will be presented for these groups to facilitate interpretation of the results.

6-CSTF 4-SDP 3-OWS 1-WIT 5-IS 11-FS, 12-PSVD and 13-IWS

3-OWS 7-IDD4 7-IDD4 9-UAS 9-UAS 2-IDT3 2-IDT3 Beads Coupons Beads Beads Coupons Beads Coupons

8-IDT15 14_CPR 15_GPS

Figure 5.1: Images of samples as received in 2014/2015. Numbers reflect the locations in Figures. S3 and S4. More detailed descriptions are given in Tables 5.1 and 5.2.

Table 5.1: Names and descriptions for 2014/2015 samples. Groups I-IV were as described in the chapter 4.

Sample Description Group1 Name Water Solid Sampling Date Central Processing Facility Samples CPF Water Injection Tank II 1_WIT √ − 30/11/2014 CPF Re-injection Water (IDT3) II 2_IDT3 Broken − 30/11/2014 Oily Water Sump II 3_OWS √ − 30/11/2014 Sand Dump Pit II 4_SDP √ − 30/11/2014 CPF Inlet Seperator II 5_IS √ − 30/11/2014 Crude Storage Tank F Dewatering II 6_CSTF √ − 28/11/2014 APF_CPF Line Pigging IV 14_CPR − √ 09/01/2015 Kutubu Field Samples IDD4 I 7_IDD4 Broken − 30/11/2014 IDT15 I 8_IDT15 √ − 30/11/2014 Agogo Processing Facility Samples Upstream Agogo Separator I 9_UAS Broken − 01/12/2014 Upstream Moran Separator I 10_UMS Broken − 01/12/2014 Gobe Processing Facility Samples Separator C Flare Header IV 11_FH − √ 10/11/2014 Separator C PSV Discharge Header IV 12_PSVD − √ 11/11/2014 Injection Water Surge Tank 4-T-2400 (x2)IV 13_IWS − √ 11/11/2014 GOBE SEPC_PSV Discharge Header IV 15_GPS − √ Nov-14 1Groups are: (I) produced waters, (II) CPF waters, (IV) solids and sludges

Table 5.2: Samples received in 120 ml serum bottles with either carbon steel coupons or iron

beads and an N2-CO2 atmosphere.

Sample Location Group1 Name Bottle with Bottle with Sampling beads coupons Date Central Processing Facility Samples CPF Re-injection Water (IDT3) II 2_IDT3 √ √ 25/11/2014 Oily Water Sump II 3_OWS √ Broken 25/11/2014 Kutubu Field Samples IDD4 I 7_IDD4 √ √ 25/11/2014 Agogo Processing Facility Samples Upstream Agogo Separator I 9_UAS √ √ 01/12/2014

5.2. Materials and Methods

5.2.1. Sample handling

Once the samples were received at the University of Calgary, they were immediately placed in an anaerobic hood containing an N2-CO2 atmosphere. The liquid samples were analysed by transferring 10 ml into 15 ml Falcon tubes. For the solid samples, 15 g of sample was mixed vigorously with 15 ml of deionized sterile water in a 50 ml Falcon tube and the supernatant was transferred to a 15 ml Falcon tube and used for the analysis.

5.2.2. Water chemistry

Samples were analyzed as described in section 4.2.2.

5.2.3. Most probable numbers (MPNs) of SRB and APB

For method details of MPN, please refer to chapter 2 (2.3).

5.2.4. Corrosion rate measurements

General corrosion rates were measured by the weight loss method. Eight 120 ml serum bottles were sent to the field with either five iron beads (∅=2.4 mm; 55.0 mg) or two carbon steel coupons (3.94x1.04x0.087 cm). The beads and coupons were pre-treated as per NACE protocol RP0775-2005 and weighed. Sodium bisulfite (10 mg) was added to the serum bottles to serve as oxygen scavenger and the head space of the serum bottles was changed to N2-CO2.

Syringes (60 ml), needles, gloves and sampling instructions were sent together with the serum bottles to assure aseptic sampling. Field personnel added 50 ml of sample to each of the 120 ml serum bottles and these were sent back to Calgary. The serum bottles had a backpressure of

around 50 ml of gas upon arrival confirming the injection of 50 ml of liquid sample and the integrity of the stopper seal. Once the samples were received at the University of Calgary they were placed on a shaker at 30°C. All samples were incubated for 45 days from the day of inoculation in the field except sample 9_UAS with was incubated for 40 days, because it had a later sampling date. For further details on weight loss method please refer to chapter 2 (2.4.2).

5.2.5. Methanogenesis

The presence of methane was measured in the serum bottles as described in section 5.2.1;

0.2 mL of the gas phase was sampled to measure methane concentration using gas chromatography. For details on methanogenesis method please refer to chapter 2 (2.2.5).

5.2.6. Microbial community analyses

For details on DNA extraction, PCR amplification and Illumina sequencing, please refer to chapter 2 (2.1.1 and 2.1.3).

5.3. Results

5.3.1. Water chemistry:

The pH for liquid samples and for extracts from solid samples ranged from 6.8 to 8.1.

The salt concentrations for liquid samples were 0.01-0.15 M Meq of NaCl (Table 5.3). Those of

group IV were lower, because solids were suspended in deionized water. Ammonium

concentrations were also low, except for produced water 8_IDT15 (0.33 mM) and CPF water

5_IS (0.23 mM), which are in close proximity in the operational diagram (Appendix: Figure S3).

Sulfate was predominantly observed in CPF waters 1_WIT (1.2 mM), 3_OWS (6.6 mM), 5_IS

(1.4 mM), and 6_CSTF (2.6 mM). No sulfate was observed in produced water 8_IDT15, in

injection water 4_SDP and in the solids extracts (Table 5.3). Sulfide was not present in any of

the samples. Nitrate for the samples was below the detection limit. Some nitrite was detected

in CPF water 6_CSTF (0.18 mM). Acetate was present in most of samples, with very high

acetate concentration found in CPF samples 1_WIT (16.6 mM) and 6_CSTF (23.4 mM).

Propionate was below detection for most samples with the exception of CPF samples 6_CSTF

(3.4 mM) and 3_OWS (10.1 mM).

5.3.2. MPNs of SRB and APB

SRB were only observed in Group IV solids and sludge samples 14_CPR (>1.1x108/ml), 12_PSVD

(9.3x103/ml) and 13_IWS (2.4x108/ml), but not in 11_FH and 15_GPS (Table 11). No SRB were observed in Group I and II samples. In contrast, significant numbers of APB were found in CPF water 1_WIT (9.3x105/ml) and 4_SDP (9.3x105/ml), but not in CPF waters 3_OWS, 5_IS and

6_CSTF. High APB numbers of CPF waters were not observed in the 2013/2014 samples (Table

4.2), when all were zero. All of the solids and sludges had high APB numbers (average

4.6 x 106/ml of extract). Produced water 8_IDT15 of Group I had an only 23 APB/ml. Overall the results indicate that SRB and APB are more active in solids and sludges than in the planktonic phase, due to biocide (THPS) treatment in the CPF. This conclusion is same as before.

Table 5.3: Water chemistry results for 2014/2015 samples; groups I and II are liquid, group IV are solid samples Group Samples pH NaCl Ammonium Ion analysis - mM VFA – mM (Meq) (mM) Sulfate Nitrite Acetate Propionate I 8_IDT15 7.97 0.15 0.33 0.00 0.00 6.22 0.45 II 1_WIT 6.78 0.15 0.02 1.15 0.03 16.62 0.00 II 3_OWS 7.14 0.14 0.00 6.56 0.01 8.74 10.13 II 4_SDP 6.76 0.01 0.00 0.00 0.00 5.26 0.00 II 5_IS 7.22 0.14 0.23 1.37 0.03 6.25 0.00 II 6_CSTF 8.13 0.15 0.00 2.63 0.18 23.40 3.35 IV 11_FH 8.05 ND2 ND 0.84 0.00 1.71 0.00 IV 12_PSVD 7.67 ND ND 0.00 0.00 0.00 0.00 IV 13_IWS 7.16 0.00 0.00 0.00 0.00 0.89 0.00 IV 15_GPS 8.10 0.00 0.00 0.00 0.01 0.00 0.00 IV 14_CPR 8.01 0.00 0.00 0.00 0.02 0.71 0.00 1Groups are: (I) produced waters, (II) CPF waters), (IV) solids and sludges 2Not determined because of insufficient sample to conduct the test

Table 5.4: MPNs of APB and SRB for 2014/2015 samples; groups I and II are liquid, group IV are solid samples Group1 Sample ID APB MPN/ml Log MPN SRB Log MPN APB/ml MPN/ml2 SRB/ml2 I 8_IDT15 23 1.36 < 3 <0.48 II 1_WIT 9.3x105 5.97 < 3 <0.48 II 3_OWS < 3 <0.48 < 3 <0.48 II 4_SDP 9.3x105 5.97 < 3 <0.48 II 5_IS < 3 <0.48 < 3 <0.48 II 6_CSTF < 3 <0.48 < 3 <0.48 IV 11_FH 9.3x106 6.97 < 3 <0.48 IV 12_PSVD 4.3x106 6.63 9.3x103 3.63 IV 13_IWS 9.3x106 6.97 2.4x108 8.38 IV 15_GPS 2.4x106 6.38 < 3 <0.48 IV 14_CPR 2.4x106 6.38 > 1.1x108 8.04 1Groups are: (I) produced waters, (II) CPF waters), (IV) solids and sludges 2Note that <3 or <0.48 means that no APB or SRB were identified in the volume of 0.1 ml tested. For simplicity of representation these MPNs will be indicated as zero in the text.

MPN Results for PNG Samples

Group I Group II Group IV 10.00

8.00

6.00

4.00

Log MPN Log perml 2.00

0.00 8_1DT15 1_WIT 3-OWS 4_SDP 5_IS 6_CSTF 11_FH 12_PSVD 13_IWS 15_GPS 14_CP Log MPN APB/ml Log MPN SRB/ml

Figure 5.2: Graphic representation of MPNs for APB and SRB for 2014/2015 samples.

5.3.3. Corrosion rate measurements

Capped and crimped serum bottles (120 ml) with 2 carbon steel coupons or 5 iron beads, bisulfite and a headspace of N2-CO2 were shipped to the field, where they were filled with 50 ml sample. When the serum bottles were received at the UofC a backpressure of 32-51 ml was measured (Table 5.5), indicating that the crimped rubber stoppers provided a good seal.

The serum bottle containing sample 3_OWS and coupons had broken during transport. In case of injected samples 9_UAS, 7_IDD4 and 2_IDT3, the 1 L sample was lost due to breakage during shipment (Table 5.1). Some of the properties indicated in Tables 5.3 and 5.4 could have been determined for the serum bottle incubations, but that was not done.

It was observed that in some cases the corroded iron beads had stuck together at the bottom of the serum bottle. At the end of the incubation period the samples were pre-treated as per NACE protocol (RP0775-2005) and weighed to measure corrosion rates.

The corrosion rates of carbon steel coupons for all the samples were between 0.011 and

0.018 mm/yr. The lowest rate was measured for produced water 7_IDD4 and the highest corrosion rate was measured for CPF reinjection water 2_IDT3. The corrosion rates of iron beads were significantly higher between 0.089 and 0.155 mm/yr. The lowest corrosion rate of iron beads was measured for CPF oily water sump 3_OWS and the highest corrosion rate of iron beads was measured for produced water 9_UAS. The corrosion rate for 9_UAS for 2013/2014 samples using iron beads was 0.032 mm/yr, which increased to 0.155 mm/yr in the 2014/2015 data set. The corrosion rate for 2_IDT3 in 2013/2014 was 0.003 mm/yr which increased to

0.122 mm/yr in the 2014/2015 data set. These increases may have been caused in part by sampling on site, as conducted in the 2014/2015 study.

Individual masses of iron beads were also measured to determine the unevenness of the corrosion, which may indicate pitting corrosion of the sample. A smaller standard deviation (SD) could suggest less and a higher standard deviation could suggest more pitting corrosion. SD for beads from the 9_UAS incubation (SD = 0.415 mg) was 13-fold higher than for non-incubated, pre-treated control beads (SD = 0.030 mg) indicating possible pitting corrosion (Table 5.6).

Corrosion rates calculated from the weight loss of individual beads are indicated in Table 5.7.

The increase in SD with increased average weight loss indicated in Table 5.6 is shown in Figure

5.3. Based on the data (Table 5.6, Figure 5.3) 9_UAS and 2_IDT3 appear to have the highest generalized and pitting corrosion rates.

Table 5.5. Survey of data collected for serum bottles used for corrosion rate measurements

Sample Weight Weight Weight Corrosion Methane Sulfide Back before after loss rate (M) (mM) pressure (mm/yr) (ml) 9_UAS coupon 2.695 2.684 0.011 0.014 149.70 0 51 7_IDD4 coupon 2.743 2.733 0.011 0.011 361.93 0 33 2_IDT3 coupon 2.523 2.508 0.015 0.018 284.72 0 24 9_UAS beads 0.276 0.264 0.012 0.155 176.17 0 42 7_IDD4 beads 0.276 0.267 0.009 0.108 219.06 0 32 2_IDT3 beads 0.276 0.266 0.011 0.122 355.68 0 37 3_OWS beads 0.276 0.268 0.008 0.089 92.72 0 48

Table 5.6: Mass of individual beads (mg) following incubation to determine corrosion; the average (mg) and standard deviation (SD in mg) are also given.

9_UAS 3_OWS 2_IDT3 7_IDD4 Control

B1 52.2 53.6 52.8 53.3 55.1 B2 53 53.4 52.7 53.1 55.2 B3 52.6 53.7 53.2 53.3 55.2 B4 53.2 53.6 53.4 53.2 55.1 B5 53.1 53.5 52.8 53.2 55.1 SD 0.415 0.114 0.303 0.084 0.054 Average 52.82 53.56 52.98 53.22 55.15 Av wt loss 2.33 1.59 2.17 1.93 0

Table 5.7: Corrosion rate (mm/yr) calculated for weight loss of individual beads in Table 5.1.

9_UAS 3_OWS 2_IDT3 7_IDD4 Control

B1 0.194 0.097 0.153 0.118 NA1 B2 0.139 0.111 0.160 0.132 NA B3 0.167 0.090 0.125 0.118 NA B4 0.125 0.097 0.111 0.125 NA B5 0.132 0.104 0.153 0.125 NA SD 0.029 0.008 0.021 0.006 NA Average 0.151 0.100 0.140 0.124 NA

1NA, as these beads were not incubated

) 0.45

g m

( 0.4

h 0.35

g i

e 0.3

d 0.25

e b

0.2

l a

u 0.15

d i

s 0.1

f 0.05

D 0 S 0.00 0.50 1.00 1.50 2.00 2.50

Average weight loss (mg)

Figure 5.3. Plot of standard deviation of residual bead weights versus average weight loss. Data are in Table 5.6. The increasing SD indicates increasing unevenness of the corrosion (i.e. pitting corrosion).

5.3.4. Methane in corrosion incubations

Methane was recorded in the headspace of serum bottles containing sample and carbon steel coupons or iron beads for corrosion rate analysis at the end of the 45 day incubation period. Methane was found in all the incubations in concentrations indicated in Table 5.5 and

Figure 5.4. However, because two time points were not measured, it cannot be concluded whether methane increased (e.g. as a result of corrosion), decreased or remained the same.

The methane concentration weakly correlated with the measured weight loss (Table 5.5), i.e. sample 3_OWS_beads had the smallest weight loss (0.008 g) and the smallest headspace methane concentration (93 M), as indicated in Table 5.5. However, it is also possible that the methane was introduced as part of the sample in which case Group I samples (produced waters) may have higher concentrations than Group II samples (CPF waters), which was not seen (Figure 5.4). No firm conclusions can be drawn.

Group I Group II 400

350

300 M) µ 250 beads 200 coupons 150

Concentration( 100

0 9_UAS 7_IDD4 2_IDT3 3_OWS

Figure 5.4: Methane concentration (μM) in the headspace of corrosion incubations, containing either beads or coupons as indicated.

5.3.5. Microbial community data of PNG samples

DNA extractions were done for all the samples followed by PCR amplification (Illumina primers). The 16S amplified sequences were sent for pyrosequencing to the Genome Quebec and McGill University Innovation Centre, Montreal, Quebec. The reads obtained following pyrosequencing were compared with each other and with a sequencing library to determine their phylogenetic affiliation, referred to as taxon (Table 5.8: phyla; genus).

Acetobacterium (in the Firmicutes phylum) was abundant in many of the samples (Table

5.8). Acetobacterium are anaerobic, gram positive bacteria, their major by-product as a result of anaerobic metabolism is acetic acid, which is found is high quantity in PNG samples (Balch et al., 1977). Other major community members found in the samples were Shewanella and

Pseudomonas, these were predominantly found in samples 15_GPS, 11_FH, and 12_PSVD. One of the common Shewanella species isolated from oil field strains is Shewanella putrefaciens, which has metabolic characteristics of iron reduction and sulfide production using thiosulfate

(Semple et al., 1989). Samples 1_WIT, 4_SDP and 5_IS were dominated by Tatumella species.

Tatumella species are facultative anaerobes (APB); their metabolic characteristics include nitrate reduction and acid production from glucose (Boone et al., 2001; Holt et al., 1994).

Proteiniphilum species were another community component observed in significant fractions in samples 14_CPR, 8_IDT15 and 12_PSVD. Proteiniphilum acetatigenes is an anaerobic bacterial strain which produces acetic acid (Chen and Dong, 2005). Spirochaeta was significantly present in 12_PSVD, Spirochaeta smaragdinae can reduce thiosulfate to sulfide by oxidizing glucose to acetate (Magot et al., 1997).

Hence, the community data analysis indicated that, there are abundant acetate producing bacteria which could explain the high acetate concentrations observed in the samples (Table 5.3). There were also community members observed that were associated with sulfate reduction and iron reduction.

5.3.6. Microbial community data of corrosion incubations

DNA was extracted from corrosion incubation samples, which includes both, samples incubated with metal coupons as well as samples incubated with metal beads. From metal coupons DNA was extracted from coupon scrapings as well as the planktonic cells in the samples that were incubated, whereas from metal beads DNA was only extracted from the planktonic cells in the samples. The extracted DNA was subjected to PCR amplification followed by pyrosequencing. The reads obtained following pyrosequencing were compared with each other and with a sequencing library to determine their phylogenetic affiliation. Table 5.9 shows the microbial communities found in the corrosion incubations.

The most significant community components observed in the incubations were

Pseudomonas and Aquabacterium which were present in all the samples. Aquabacterium species are found in water systems and are in abundant in water system biofilms (Kalmbach et al., 2000). Enterobacteriaceae were another community component that was found in abundance in planktonic cells of both 2_IDT3 sample incubation with beads as well as coupons and also was found in sample 3_OWS with beads. Interesting even though Enterobacteriaceae were present in planktonic cells for both 2_IDT3 incubations with beads and coupons, it was not present in coupon scrapings (2_ITD3-CS), suggesting that Enterobacteriaceae were not able to form biofilms on coupons. Enterobacteriaceae have been associated with crude oil

degradation; some species of Enterobacter were able to degrade aromatic compounds in crude oil (Ahmed et al., 2014). Also Anaerovorax species were present in abundance only in sample

2_IDT3 with coupons, it was mostly absent from 2_IDT3 incubations with beads or from coupon scrapings. Anaerovorax species are strict anaerobes which are able to ferment putrescine

(organic chemical produce during the breakdown or animal tissue) to acetate, butyrate, molecular hydrogen and ammonia (Matthies et al., 2000). Caulobacter species, which were present in most of the incubations, are able to degrade crude oil, and can break down polyaromatic hydrocarbons (PAHs) and also play critical role in degrading alkanes (Zhang et al.,

2003). The community composition also showed the presence of methanogens

(Methanocalculus) and acetogens (Acetobacterium) in all of the samples. Methanocalculus is associated with MIC (Zhang et al., 2003; Suflita et al., 2012). SRB were absent from all of the samples.

The community compositions indicated abundant biofilm formers, and the presence of acetogens and methanogens, suggesting that these could play a role in MIC. There was no presence of SRB suggesting that SRB are not active players in MIC in these samples.

Table 5.8: Distribution of sequence over taxa. The numbers are fractions (%) of the number of pyrosequencing reads for each taxon. #Taxonomy 1_WIT 3_OWS 4_SDP 5_IS 6_CSTF 8_IDT15 11_FH 12_PSVD 13_IWS 14_CPR 15_GPS Total Number of Good reads 7584 1994 2146 1771 10821 16081 23268 25114 5820 22678 10848 Bacteria;Firmicutes;Acetobacterium; 0.1 47.6 2.1 11.6 46.3 88.0 27.7 7.6 8.1 44.6 17.8 Bacteria;Proteobacteria;Shewanella; 0.0 0.0 0.0 0.0 0.1 0.0 43.7 12.3 0.8 0.0 10.1 Bacteria;Proteobacteria;Pseudomonas; 0.0 0.9 1.6 0.5 7.8 0.3 9.2 28.0 11.9 0.0 26.5 Bacteria;Proteobacteria;Tatumella; 98.8 9.0 79.3 67.3 1.3 0.0 0.3 0.1 0.1 0.1 0.0 Bacteria;Bacteroidetes;Proteiniphilum; 0.0 0.2 0.0 0.0 0.2 11.5 0.4 16.1 3.6 5.6 3.4 Bacteria;Spirochaetae;Spirochaeta; 0.0 0.0 0.0 0.0 0.0 0.0 1.0 14.7 0.8 0.4 2.1 Bacteria;Firmicutes;Alkalibacter; 0.0 0.0 0.0 0.0 17.6 0.0 2.3 1.5 0.1 0.0 5.7 Bacteria;Firmicutes;Proteiniclasticum; 0.0 1.5 0.0 0.0 0.3 0.0 0.2 1.0 0.2 10.6 0.8 Bacteria;Firmicutes;Erysipelothrix; 0.0 0.1 0.0 0.0 0.0 0.0 0.3 0.4 0.8 8.3 0.4 Bacteria;Firmicutes;Tissierella; 0.0 0.0 0.0 0.0 0.0 0.0 0.2 4.4 0.1 0.0 5.5 Bacteria;Proteobacteria;Alcaligenaceae; 0.0 5.8 0.1 0.0 0.0 0.0 0.0 3.0 0.0 0.0 6.0 Bacteria;Proteobacteria;Acidovorax; 0.0 1.8 3.7 0.0 0.0 0.0 0.1 0.0 7.6 4.0 0.0 Bacteria;Firmicutes;Alkalibacterium; 0.0 0.1 0.0 0.0 3.1 0.0 3.4 1.1 0.0 0.0 0.3 Bacteria;Proteobacteria;Azovibrio; 0.0 0.4 0.3 0.0 0.0 0.0 0.0 0.0 9.4 3.8 0.0 Bacteria;Cyanobacteria;Calothrix; 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 6.2 0.0 Bacteria;Cyanobacteria;Leptolyngbya; 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 4.7 0.0 Bacteria;Firmicutes;Dethiosulfatibacter; 0.0 0.1 0.0 0.0 0.6 0.0 1.3 1.2 0.3 0.1 2.7 Bacteria;Proteobacteria;Geoalkalibacter; 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.9 2.9 0.0 4.2 Bacteria;Firmicutes;Fusibacter; 0.0 0.0 0.0 0.0 0.8 0.0 0.1 0.0 12.1 0.1 0.0 Bacteria;Firmicutes;Clostridiales; 0.0 0.1 0.0 0.0 6.8 0.0 0.0 0.0 0.0 0.1 0.0 Bacteria;Firmicutes;Anoxynatronum; 0.0 0.0 0.0 0.0 1.3 0.0 1.2 0.5 0.0 0.0 1.3 Bacteria;Firmicutes;Soehngenia; 0.0 0.0 0.0 0.0 5.9 0.0 0.0 0.0 0.1 0.0 0.0 Bacteria;Proteobacteria;Aquabacterium; 0.1 1.4 0.2 0.5 0.3 0.1 1.9 0.1 0.0 0.2 0.0 Bacteria;Proteobacteria;Azoarcus; 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 10.3 0.0 0.0 Bacteria;Proteobacteria;Azomonas; 0.1 3.3 6.8 19.9 0.1 0.0 0.0 0.0 0.0 0.0 0.0 Bacteria;Proteobacteria;Desulfobacteraceae 0.0 0.0 0.0 0.0 0.0 0.0 0.1 1.9 0.0 0.0 0.1

Table 5.9: Distribution of sequences over taxa for corrosion incubations. The numbers are fractions (%) of the number of pyrosequencing reads for each taxon found in the corrosion incubation of PNG samples. #Taxonomy 2_IDT3-B 9_UAS-B 7_IDD4-C 2_IDT3-C 9_UAS-C 7_IDD4-CS 2_IDT3-CS 9_UAS-CS 7_IDD4-B 3_OWS-B Total Number of Good reads 6405 6287 37503 41981 26192 34862 36459 25899 35015 10190 Bacteria;Proteobacteria;Pseudomonas; 0.2 40.5 31.7 19.8 31.8 28.4 30.0 34.3 34.7 8.7 Bacteria;Proteobacteria;Aquabacterium; 14.7 24.9 33.3 8.4 31.0 32.7 32.1 30.2 29.0 11.1 Bacteria;Proteobacteria;Enterobacteriaceae; 73.8 0.0 0.0 33.6 0.1 0.3 0.2 0.0 0.1 40.2 Bacteria;Firmicutes;Anaerovorax; 0.0 0.0 0.1 27.7 0.3 0.3 0.0 0.3 0.1 0.0 Bacteria;Firmicutes;Clostridiales;P._palm_C-A_51; 3.3 7.8 3.4 1.1 4.5 3.9 4.7 5.2 6.6 0.0 Bacteria;Proteobacteria;Caulobacter; 0.4 0.8 4.3 1.0 5.3 5.4 4.2 4.5 4.9 1.6 Bacteria;Proteobacteria;Pelomonas; 1.0 3.2 2.9 0.9 3.0 3.8 3.0 1.9 3.1 0.8 Bacteria;Bacteroidetes;Sphingobacteriales;WCHB1-69; 0.9 1.2 3.7 0.7 2.0 2.5 3.2 3.3 3.2 0.4 Bacteria;Actinobacteria;Microbacteriaceae; 0.6 1.0 2.7 0.6 2.9 3.2 3.4 2.4 2.2 0.8 Bacteria;Firmicutes;Tissierella; 0.0 4.8 2.0 0.6 2.0 2.1 1.7 1.7 1.9 0.0 Bacteria;Proteobacteria;Roseateles; 1.2 1.6 1.4 0.4 1.9 2.6 2.1 1.7 2.0 0.5 Bacteria;Firmicutes;Acetobacterium; 1.2 2.3 1.6 0.5 1.2 1.5 1.7 1.2 0.4 10.7 Archaea;Euryarchaeota;Methanocalculus; 0.0 1.2 1.4 0.5 1.2 1.6 1.6 1.7 1.2 0.1 Bacteria;Proteobacteria;Sphingomonas; 0.1 0.2 1.7 0.4 1.8 1.1 1.4 1.1 1.3 0.4 Bacteria;Firmicutes;Fusibacter; 0.1 2.4 0.7 0.4 1.6 1.1 1.3 1.5 1.0 1.0 Bacteria;Actinobacteria;Rhodococcus; 0.3 0.2 1.3 0.3 1.4 1.3 1.1 0.8 1.3 0.3 Bacteria;Spirochaetae;Spirochaeta; 0.2 0.3 0.8 0.4 1.3 1.3 0.9 1.3 1.2 0.4 Bacteria;Proteobacteria;Beggiatoa; 0.4 0.7 0.9 0.3 0.7 0.7 1.1 0.9 0.7 0.3 Bacteria;Proteobacteria;Acinetobacter; 0.1 0.7 0.5 0.2 0.4 0.4 0.6 0.7 0.8 0.8 Bacteria;Bacteroidetes;Proteiniphilum; 0.1 0.1 0.3 0.1 0.6 0.5 0.1 0.5 0.3 3.2 Bacteria;Proteobacteria;Methylobacterium; 0.0 0.0 0.4 0.1 0.6 0.2 0.6 0.6 0.5 0.4

Note: Suffix B indicates beads, C indicates coupons and CS indicates coupon scrapings; B and C are planktonic samples; CS are biofilm samples.

5.4. Conclusions

The corrosion incubations with the metal beads showed higher corrosion rates than with metal coupons. There could be multiple reasons, which include surface structure of iron beads or crevice or galvanic corrosion which could be contributing to the increase in corrosion rate. The speculations haven’t been confirmed with experimental evidence. The corrosion incubations showed higher corrosion rates for samples from 2014/2015 compared to the samples from 2013/2014. The corrosion incubations with metal beads for 9_UAS showed corrosion rate of 0.032 mm/yr in 2013/2014 and 0.155 mm/yr in 2014/2015, and 2_IDT3 showed corrosion rate of 0.003 mm/yr in 2013/2014 and 0.122 mm/yr in 2014/2015. This might suggest that field inoculated incubations are more effective and maintain the sample integrity. Also, on conducting DNA analysis of corrosion incubations, it was observed that acetogens and methanogens could be playing a more vital role in MIC than SRB in this particular field. The results obtained for the 2013/2014 samples also showed presence of methanogens in the samples. Also sample PNG11_SS, which showed the highest corrosion rate in the 2013/2014 samples, was the only one to show active methanogenesis as well.

The acetate concentration of PW and CPF waters were high as observed in samples from

2013/2014. The highest acetate concentration was observed in 6_CSTF (23.4 mM) whereas the lowest acetate concentration was observed in 4_SDP (5.26 mM) for CPF waters. The microbial community analysis of the samples showed presence of high percentage of acetogens in most of the water samples, which explains high acetate concentration in most of the water samples.

The results obtained for the 2014/2015 samples confirm the conclusions for the

2013/2014 samples that waters from the CPF have an input of sulfate increasing the average

sulfate concentration from 0.62 mM (the concentration in produced waters) to 2.78 mM (the concentration in CPF waters). Because THPS is routinely added to these waters, this can serve as a potential source of sulfate. THPS could dissolve iron sulfide deposited on the metal surface by forming water soluble THP iron aluminium complex and releasing sulfate (Trahan, 2014). In this chapter experimental evidence is not provided for sulfate release, but the literature supports THPS releasing sulfate (Wang et al., 2015; Trahan, 2014).

Addition of THPS to CPF waters causes these to have zero counts of APB and SRB in all of four 2013/2014 samples and in three of five 2014/2015 samples (Table 4.2 and 5.4). Hence,

THPS addition gave control of planktonic bacteria. However, there was poor control of microbial populations in solids and sludges, which had high APB (seven out of nine samples) and high SRB (five out of nine samples) (Table 4.2 and 5.4), indicating failure of added THPS to reach these populations.

Evaluation of whether THPS addition contributes 2 mM (200 ppm) of sulfate to CPF waters must include careful accounting of THPS inputs and measured sulfate concentrations as a function of time. If this evaluation confirms the suggestion made in this study that THPS represents a major source of sulfate for growth of SRB in CPF waters, then an evaluation whether this is the best biocide for this field is needed. Also, more work is required in understanding whether sulfate released from THPS can be degraded by microbes or not.

6. Chapter six: Impact of light oil toxicity on souring

6.1. Introduction:

Souring is a major concern in the oil and gas industry and is most commonly caused by

SRB, which reduce sulfate to sulfide by oxidizing oil organics. The source of sulfate or SRB in a reservoir could be from the water injected for secondary oil recovery or they could be present indigenously (Gieg et al., 2011). The electron donor required to drive the reduction of sulfate can be the oil organics itself. An important question is whether crude oil components can be easily used for sulfate reduction.

Crude oil can be classified as light, medium, or heavy based on its American Petroleum institute (API) gravity, and its viscosity. Oil with API gravity higher than 31.1° is considered light oil. Light oils produced from oil reservoirs can be hard to degrade by microbes as light hydrocarbon fractions in the oil can be toxic (Sherry et al., 2014). The inhibitory effect of light oil depends on the solubility of light oil in water as it makes them more bioavailable which causes toxic effects by accumulation of light oil component within the cell leading to swelling in cell membrane and cell lysis (Sherry et al., 2014). The influence of light oil on SRB activity will therefore be explored in this chapter. Previously some experiments were performed to understand souring in samples collected in 2011 from a light oil producing field in Papua New

Guinea (Agrawal et al., 2011). No SRB activity was observed in the presence of light oil, SRB activity in water samples was only observed after the addition of 2,2,4,4,6,8,8- heptamethylnonane (HMN) to the incubations (Agrawal et al., 2011). This was interpreted as meaning that the water samples contained dissolved light oil components, which were toxic to

SRB and which were removed by addition of HMN. This showed the potential impact of light oil toxicity on SRB. Also Formation water from Norwegian continental shelf has shown high acetate

(upto 20 mM) (Barth and Riis, 1992), these fields are flooded with seawater having high sulfate concentration. A field with high acetate and sulfate concentration would have high potential for souring, but acetate often accumulates in the PW. So the objective of this chapter will be to study the light oil toxicity on SRB, specifically on acetate utilizing SRB. The study will focus on whether different light oils differ in their toxicity towards acetate utilizing SRB and what component of these oils will show higher toxicity.

6.2. Methods and materials:

6.2.1. Samples

To understand light oil toxicity SRB activity experiments were performed with various light oils, light hydrocarbons and heavy oil (Table 6.1). Table 6.2 describes the types of cultures used for incubations in these experiments.

6.2.2. Water chemistry

Sulfate was analyzed by ion chromatography using a conductivity detector (Waters 423) and IC-PAK anion column with borate/gluconate buffer at a flow rate of 2 ml/min (4 x 150 mm,

Waters). Organic acids (lactate, acetate, propionate and butyrate) were determined using an

HPLC equipped with a UV detector (Waters 2487 Detector) and an organic acids column

(Alltech, 250 x 4.6 mm) eluted with 25 mM KH2PO4 buffer at pH 2.5. The concentration of dissolved sulfide was measured using the diamine method (Truper and Schlegel, 1964).

Table 6.1: Types of crude oil used in light oil toxicity experiments. Name Description CPM Light oil with API 41°, produced from a shale oil field in the Bakken formation near Estevan, Saskatchewan. Diluent Natural gas condensate used to dilute bitumen, consisting mostly of C1-C9 MHGC Heavy oil with API 16°, produced from conventional heavy oil field in Medicine Hat, Alberta. PNG Light oil with API 46°, produced from conventional light oil field in Papua New Guinea. Tundra Light oil with API 38°, produced from conventional light oil field in Bakken formation near Virden, Manitoba.

Table 6.2: Types of cultures used as inoculum SRB activity experiments:

Culture Description 3 PW Produced water sample from a shale oil field in the Bakken formation near Virden, Manitoba, producing light oil. Desulfobacter postgatei Pure culture ordered from the Deutsche Sammlung von Mikroorganismen und Zellkulturen (DSMZ) SW Enrichment Source water taken from a fresh water storage lagoon from a shale gas field in the Montney formation, British Columbia, Canada. The enrichments were done by incubating SW with sulfate and acetate.

6.2.3. Microbial community analysis

DNA was isolated from the SW enrichment sample. 70 ml of SW enrichment sample was centrifuged to collect biomass. For details on DNA extraction, PCR amplification and sequencing please refer to chapter 2 (2.1.1 and 2.1.3).

6.2.4. Experimental setup

To understand the impact of light oil toxicity on souring, incubations were done in 120 ml serum bottles with 70 ml of CSBK medium wherein sulfate, lactate or acetate was added.

Sulfate, sulfide, lactate and acetate were measured as a function of time.

6.3. Results and Observations

6.3.1. Experiment with 3-PW

To determine SRB activity, 3.5 ml of 3-PW was inoculated in 70 ml of CSBK medium with

1 M NaCl, 10 mM sulfate and either 3 mM of volatile fatty acid or 10 mM lactate. The bottles were incubated at 30°C either in the presence or in the absence of 1 ml of Tundra light oil. The concentrations of sulfate, sulfide, lactate and VFA were measured as a function of time.

6.3.2. Results

SRB activity was observed in incubations of 3-PW with lactate and sulfate both, with and without Tundra oil. In the presence of Tundra oil 9 mM of sulfate was reduced to a residual of 3 mM. This corresponded with a decrease in the lactate concentration of 14 mM. The sulfide concentration increased by approximately 4 – 4.5 mM and the acetate concentration by 11 – 13

mM (Figure: 6.1 A, B, D and E). But in the absence of Tundra oil 9 mM of sulfate was completely reduced. This not only corresponded with decrease in the lactate concentration by 14 mM, but once all the lactate had been used, acetate was used to reduce sulfate to sulfide (Figure 6.1 C and F). There was a complete reduction of 9 mM of sulfate to 7-8 mM sulfide by oxidizing approximately 14 mM lactate (to acetate and CO2) and 2 mM acetate (to CO2). The acetate oxidation was only observed in the incubation without the Tundra oil.

SRB activity was also observed in incubations of 3-PW with VFA and sulfate, both with and without Tundra oil (Figure 6.2). With or without Tundra oil 10 mM of sulfate was reduced to 6 mM of residual sulfate (Figure 6.2). This corresponded with a decrease in butyrate concentration of approximately 5 mM. We were also able to see the increase in sulfide concentration at the same time by approximately 2 mM and an increase in acetate concentration of 10 mM (Figure 6.2). So in both instances, with or without light oil, there were no differences in SRB activity.

Figure 6.1: Measurements of samples incubated with 3-PW, lactate and sulfate with or without Tundra oil. (A-C) sulfate and sulfide, (D-F) lactate and acetate.

Figure 6.2: Measurements of samples incubated with 3-PW, VFA, and sulfate with or without Tundra oil; (A,B) sulfate and sulfide, (C,D) butyrate, propionate and acetate.

6.3.3. Observation for experiment with 3-PW

SRB activity by lactate-utilizing bacteria did not seemed to be hindered by the presence of light oil, as the sulfate in the incubations were reduced to sulfide by utilizing lactate in both presence and absence of light oil. But once all the lactate was incompletely oxidized to acetate and CO2 no SRB activity was observed using acetate and sulfate in presence of light oil. In the absence of light oil once all the lactate was used, the SRB activity continued by utilizing acetate to reduce sulfate to sulfide. Therefore acetate-utilizing SRB in the tested environment culture cannot reduce sulfate in the presence of light oil. This leads us to an important question, are acetate utilizing SRB inhibited by the presence of light oil and could light oil toxicity be playing a role in this inhibition?

Although acetate can be used as an electron donor for sulfate reduction by

Desulfobacter and other incompletely-oxidizing SRB along with many other anaerobes, it often accumulates in produced waters of water flooded oil fields. It is therefore hypothesized that light oil components are toxic to these SRB species.

6.3.4. Experiment with Desulfobacter postgatei

Desulfobater postgatei culture (3.5 ml) was inoculated in duplicate bottles with 70 ml of

CSBK medium with 10 mM sulfate, 20 mM acetate, and 1 ml of either CPM oil, diluent, MHGC oil, PNG oil or Tundra oil. Also two bottles were incubated without oil. The twelve bottles were incubated at 30°C for 24 days. The concentrations of sulfate, sulfide, and acetate were measured as a function of time.

6.3.5. Results

In the absence of oil, Desulfobacter was able to reduce 10 mM of sulfate to 8-9 mM of sulfide by utilizing 10 mM of acetate (Figure 6.3 A). Similar results were obtained in presence of the MHGC oil (heavy oil) (Figure 6.3 B). In the presence of light oil (CPM oil, diluent, PNG oil, or

Tundra oil), Desulfobacter was unable to reduce any sulfate to sulfide by utilizing acetate

(Figure 6.3 C-F). The acetate-utilizing SRB activity was only observed in the absence of light oil or in the presence of heavy MHGC oil. There was no acetate-utilizing SRB observed in the presence of light oils.

Figure 6.3: Measurement of incubations with Desulbacter postgatei, 10 mM of sulfate and 20 mM of acetate with no oil (A), with MHGC oil (B), with PNG oil (C), with diluent (D), with CPM oil (E), and with Tundra oil (F).

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6.3.6. Observations for experiment with Desulfobacter postgatei

Acetate-utilizing SRB activity was not inhibited by heavy MHGC oil, but was strongly inhibited by light oils like CPM oil, diluent, PNG oil and Tundra oil. This suggests that some light oil components could be toxic to Desulfobacter. This observation is interesting, but since

Desulfobacter postgatei is a pure culture from a culture collection it remains to be shown that an enrichment of acetate-utilizing SRB from an oil field are also inhibited by light oil.

6.3.7. Experiments with SW enrichment

SW enrichment (3.5 ml) was inoculated in 70 ml of CSBK medium with 10 mM sulfate,

20 mM acetate, and 1 ml of CPM oil, diluent, MHGC oil, PNG oil or Tundra oil. Control bottles without oil were also incubated. The twelve bottles were incubated at 30°C for 22 days. The concentrations of sulfate, sulfide, and acetate were measured as a function of time.

6.3.8. Results

In absence of oil, SW enrichment cultures were able to reduce 10 mM of sulfate to 8-9 mM of sulfide by utilizing 10 mM of acetate (Figure 6.4 A). Similar result was also observed in presence of MHGC oil (heavy oil) (Figure 6.4 B). In presence of light oils CPM oil, diluent, PNG oil, or Tundra oil, SW enrichment culture were not able to reduce any sulfate to sulfide by utilizing acetate (Figure 6.4 C-F).

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Figure 6.4: Measurement of samples incubated with SW enrichment, 10 mM of sulfate and 20 mM of acetate with no oil (A), with MHGC oil (B), with PNG oil (C), with diluent (D), with CPM oil (E) and with Tundra oil (F).

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6.3.9. Microbial community data

The microbial community data showed the presence of Desulfobacter species in the SW enrichment, but they were not the dominant component. The enrichment was dominated by

Desulfotomaculum species. Desulfotomaculum acetoxidans is also an acetate oxidizing, sulfate reducing bacterium (Widdel and Pfennig, 1977). Another sulfate reducer that was observed in the SW enrichment was Desulfarculus, Desulfarculus baarsii is also a gram negative sulfate reducer, which can use acetate as an electron donor and widely observed in both fresh water and in sea water (Sun et al., 2010). The other two SRB species present in the microbial community were Desulfuromonas and Desulfovibrio. Desulfovibrio is not capable of reducing sulfate to sulfide by oxidizing acetate (Sun et al., 2000; Pfennig and Biebl, 1976). However,

Desulfuromonas acetoxidans can use acetate as electron donor to reduce S0 (sulphur) to sulfide.

There was also a presence of methanogens, of these Methanosaeta is an acetate-utilizing methanogen (Ma et al., 2006).

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Table 6.3: Microbial community composition of SW enrichment1).

#Taxonomy # of reads %Reads Bacteria;Firmicutes;Clostridia;Clostridiales;Peptococcaceae;Desulfotomaculum; 806 36.4 Bacteria;Spirochaetae;Spirochaetes;SHA-4; 485 21.9 Archaea;Euryarchaeota;Methanomicrobia;Methanosarcinales;Methanosaetaceae;Methanosaeta; 408 18.4 Bacteria;Firmicutes;Erysipelotrichia;Erysipelotrichales;Erysipelotrichaceae;Erysipelothrix; 87 3.9 Bacteria;Bacteroidetes;Bacteroidia;Bacteroidales;Rikenellaceae;vadinBC27_wastewater-sludge_group; 77 3.5 Bacteria;Proteobacteria;Deltaproteobacteria;Desulfarculales;Desulfarculaceae;Desulfarculus; 40 1.8 Archaea;Euryarchaeota;Thermoplasmata;WCHA1-57; 33 1.5 Bacteria;Spirochaetae;Spirochaetes;Spirochaetales;Spirochaetaceae;Spirochaeta; 31 1.4 Bacteria;Bacteroidetes;Bacteroidia;Bacteroidales;Porphyromonadaceae;Proteiniphilum; 26 1.2 Bacteria;Bacteroidetes;SB-1; 26 1.2 Bacteria;Proteobacteria;Deltaproteobacteria;Desulfuromonadales;21f08; 26 1.2 Bacteria;Bacteroidetes;Sphingobacteriia;Sphingobacteriales;CMW-169; 25 1.1 Bacteria;Firmicutes;Clostridia;Clostridiales;Family_XIII;Anaerovorax; 25 1.1 Bacteria;Chloroflexi;Anaerolineae;Anaerolineales;Anaerolineaceae;Leptolinea; 23 1.0 Bacteria;Proteobacteria;Deltaproteobacteria;Desulfuromonadales;Desulfuromonadaceae;Desulfuromonas; 15 0.7 Bacteria;Proteobacteria;Deltaproteobacteria;Desulfovibrionales;Desulfovibrionaceae;Desulfovibrio; 14 0.6 Bacteria; 12 0.5 Bacteria;Spirochaetae;Spirochaetes;Spirochaetales;Spirochaetaceae;Treponema; 12 0.5 Bacteria;Bacteroidetes;Bacteroidia;Bacteroidales;Rikenellaceae;Blvii28_wastewater-sludge_group; 11 0.5 Bacteria;Proteobacteria;Deltaproteobacteria;Desulfovibrionales;Desulfovibrionaceae;Desulfocurvus; 10 0.5 Bacteria;Bacteroidetes;vadinHA17; 9 0.4 Bacteria;Proteobacteria;Deltaproteobacteria;Desulfobacterales;Desulfobulbaceae;Desulfocapsa; 9 0.4 Bacteria;Bacteroidetes;Sphingobacteriia;Sphingobacteriales;WCHB1-69; 7 0.3 1) Data were obtained from Illumina sequencing; total number of good reads was 2217

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6.3.10. Observation for experiments with SW enrichment

The activity of acetate-utilizing SRB in SW enrichment was not inhibited by the presence of MHGC oil (heavy oil), but was inhibited by the presence of light oils like CPM oil, diluent, PNG oil and Tundra oil. This suggests that light oil components maybe toxic to acetate utilizing SRB.

Microbial community data showed that not just Desulfobacter species, but other acetate- utilizing SRB present in SW enrichment are also unable to utilize acetate and reduce sulfate to sulfide in the presence of light oils. Therefore both acetate-utilizing SRB in SW enrichment as well as in pure culture (Desulfobacter postgatei) are affected by the presence of light oil. This leaves the important question, what volume or concentrations of light oils are toxic to acetate- utilizing SRB and whether these differ, for different oils.

6.3.11. Minimum inhibitory volumes (MIVs) of light oils

SW enrichment (3.5 ml) was inoculated in 70 ml of CSBK medium with 10 mM sulfate,

20 mM acetate, and different volumes of oil and HMN to a total of 1 ml (Table 6.4.). The oils used included CPM oil, diluent, PNG oil and Tundra oil. Control incubations included those with

1 ml of HMN only (Table 6.4). The duplicate bottles were incubated at 30°C for 22 days.

Concentrations of sulfate, sulfide, and acetate were measured as a function of time.

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Table 6.4: Volumes of oil and HMN used in experiments to determine the minimum inhibitory volume (MIV)

Light oil volume (µL) HMN volume (µL)

0 1000*

50 950

100 900

200 800

400 600

800 200

1000 0

* This can be regarded as a control incubation, as no oil was added.

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6.3.12. Results

The toxicity of different oils varied at different concentrations. After 10 days of incubation both diluent 50 (50 µl diluent + 950 µl HMN) and diluent 100 (100 µl diluent + 900 µl

HMN) started showing acetate oxidizing SRB activity. Diluent 50 showed reduction of 7-8 mM sulfate (Figure 6.5 A), increase in sulfide by 7 mM (Figure 6.5 B) and acetate oxidation by 14 mM (Figure 6.5 C). Diluent 100 showed sulfate reduction of 6 mM, increase in sulfide of 6 mM and acetate oxidation of 12 mM. For CPM oil after 7 days of incubation, CPM 50 (50 µl CPM oil

+ 950 µl HMN) and after 10 days of incubation, CPM 100 (100 µl CPM oil + 900 µl HMN) started showing acetate oxidizing SRB activity. CPM 50 showed sulfate reduction by 10-11 mM (Figure

6.5 D), increase in sulfide by 10 mM (Figure 6.5 E) and acetate oxidation by 17 mM (Figure 6.5

F). CPM 100 showed sulfate reduction by 11 mM, increase in sulfide by 9 mM and acetate oxidation by 18 mM. For PNG oil after 7 days of incubation both PNG 50 (50 µl PNG oil + 950 µl

HMN) and PNG 100 (100 µl PNG oil + 900 µl HMN) started showing acetate oxidizing SRB activity. PGN 50 showed sulfate reduction by 9 mM (Figure 6.5 G), increase in sulfide by 9 mM

(Figure 6.5 H) and acetate oxidation by 16 mM (Figure 6.5 I). PNG 100 showed sulfate reduction by 9 mM, increase in sulfide by 9 mM and acetate oxidation by 16 mM. For Tundra oil after 7 days of incubation Tundra 50 (50 µl Tundra oil + 950 µl HMN), Tundra 100 (100 µl Tundra oil +

900 µl HMN), Tundra 200 (200 µl Tundra oil + 800 µl HMN) and Tundra 400 (400 µl Tundra oil +

600 µl HMN) started showing acetate oxidizing SRB activity. Tundra 50, Tundra 100, and Tundra

200 showed sulfate reduction by 6 Mm (Figure 6.5 J), increase in sulfide by 6 mM (Figure 6.5 K) and acetate oxidation by 12 mM (Figure 6.5 L). Tundra 400 showed sulfate reduction by 8 mM, increase in sulfide by 8 mM and acetate oxidation by 14 mM

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diluent CPM PNG Tundra

Time (Days)

Figure 6.5: Sulfate, sulfide and acetate for diluent (A, B and C), CPM oil (D, E and F), PNG oil (G, H and I), and Tundra oil (J, K and L), measurement of samples incubated with SW enrichment, 10 mM of sulfate and 20 mM of acetate with different concentration of oil and HMN.

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6.3.13. Observation for MIV experiment with different oils

Light oil toxicity on acetate utilizing sulfate reducing bacteria differed for different light oils. Diluent was the most toxic with a MIV between 200-400 µl, where SRB activity was only observed after 10 days of incubation. CPM oil was second most toxic with an MIV between 200-

400 µl, where SRB activity was observed after 7 days of incubation. It was followed by PNG oil with MIV being between 400-800 µl, where SRB activity was observed after 7 days of incubation. The least toxic of the four was Tundra oil with a MIV between 800-1000 µl, where

SRB activity was observed after 7 days of incubation. Heavy oil like MHGC oil from previous experiments showed no toxic effect on acetate-utilizing SRB activity. Different oils have different MIV, this leads up to an important question, why do these oil differ in their MIV and how different are these oil in their compositions.

6.3.14. Oil compositions

Diluent, CPM oil, PNG oil and Tundra oil were analysed on gas chromatography mass spectrometry (GCMS) to determine their composition. It was observed that PNG oil was the richest in both BTEX molecules as well as low molecular weight (LMW) alkanes; this was followed by CPM oil which also showed presence of BTEX molecules as well as LMW alkanes.

CPM oil showed higher presence of alkanes than BTEX molecules (Figure 6.6 A and B). CPM oil was followed by MHGC oil and Tundra oil. MHGC oil (heavy oil) showed presence of BTEX molecules, but was not rich in LMW alkanes. Tundra oil show presence of LMW alkanes, but was not rich in BTEX molecules. Finally we had diluent which did not showed significant presence of both BTEX molecules as well as LWM alkanes. This could be due to the GCMS

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analysis parameter set from C7 and above, whereas literature has shown that diluent has highest concentration of C5 and C6 (Blackmore et al., 2014).

6.3.15. Observations for oil compositions

PNG oil showed presence of significant BTEX molecules as well as LMW alkanes; still it was not the most toxic oil on acetate utilizing SRB, whereas diluent showed very little presence of BTEX molecules as well as LMW alkanes; still it was the most toxic on acetate utilizing SRB.

Diluent, though on GCMS analysis of C7 and higher did not show lot of LMW alkanes, but is rich in LMW alkanes (Table 1.1) (Blackmore et al., 2014). The GCMS analysis with the current parameters only showed results of C7 and higher carbon numbers, whereas diluent has more than 50% of C6 and less (Table 1.1) (Blackmore et al., 2014). So diluent rich in LMW alkanes has showed high toxicity towards acetate utilizing SRB. This leads to the question, which component of light oil is more toxic to microorganisms, BTEX molecules or LMW alkanes?

6.3.16. MIV of different light oil components

SW enrichment (3.5 ml) was inoculated in 70 ml of CSBK medium with 10 mM sulfate,

20 mM acetate, and different concentration of light oil components and HMN, as in Table 6.4.

The light oil components used for the experiment included pentane, heptane and toluene

(added as pure compounds). Control incubations were also established with HMN only. The bottles were incubated at 30°C for 22 days. Concentrations of sulfate, sulfide, and acetate were measured as a function of time.

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BTEX molecules composition (A) 350

300

Toluene 250 o-xylene 200 m/p-xylene Ethylbenzene 150

100 Concentrations(mM) 50

0 PNG CPM MHGC Tundra Diluent

LMW alkanes composition (B) 200 180 PNG

160 CPM 140 MHGC 120 Tundra 100 80 Diluent 60

Concentrations(mM) 40 20 0 C7 C8 C9 C10 C11 C12

Figure 6.6: BTEX molecule compositions (A) and Light molecular weight (LMW) alkane compositions (B) of different oils.

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6.3.17. Results

The toxicity of different oil components varied and toxicity of different concentrations also varied. For pentane after 12 days of incubation P50 (50 µl pentane + 950 µl HMN) started showing acetate oxidizing SRB activity. P50 showed sulfate reduction of 6 mM (Figure 6.7 A), increase in sulfide of 6 mM (Figure 6.7 B) and acetate oxidation of 14 mM (Figure 6.7 C). For heptane after 12 days of incubation, H50 (50 µl heptane + 950 µl HMN) and after 26 days of incubation, H100 (100 µl heptane + 900 µl HMN) started showing acetate oxidizing SRB activity.

H50 showed sulfate reduction of 9 mM (Figure 6.7 D), increase in sulfide of 9 mM (Figure 6.7 E) and acetate oxidation of 9 mM (Figure 6.7 F). H100 showed sulfate reduction of 2 mM, increase in sulfide of 2 mM and acetate oxidation of 2 mM. In presence of toluene there was no acetate- utilizing SRB activity observed in any of the incubations. Control HMN only showed almost immediate sulfate reduction of 8 mM (Table 6.7 G), increase in sulfide of 8 mM (H), and acetate oxidation of 10 mM (Table 6.7 I).

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Figure 6.7: Sulfate, sulfide and acetate for pentane (A, B and C respectively), heptane (D, E and F respectively) and toluene (G, H and I respectively) measurements for samples incubated with SW enrichment, 10 mM of sulfate and 14 mM of acetate with different concentration of oil components and HMN.

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6.3.18. Observations for MIV experiment with different light oil components

Light oil toxicity for acetate utilizing SRB varied with different light oil components.

Toluene (one of the BTEX molecules) show significantly higher toxicity compared to pentane and hexane, with no acetate-utilizing SRB activity observed in any of toluene incubations. This was followed by pentane which showed acetate utilizing SRB activity in only P50 (50 µl pentane

+ 950 µl HMN), and finally the least toxic component among the three was heptane which showed acetate utilizing SRB activity in H50 (50 µl heptane + 950 µl HMN) as well as H100 (100

µl + 900 µl HMN). This suggests that toluene is more toxic to acetate utilizing SRB than LMW alkanes. Also water solubility of toluene (5.6 mM) is higher than both pentane (0.55 mM) and heptane (0.3 mM), which makes them more bioavailable and more toxic. The observation that diluent containing a lot of pentane and hexane was more toxic than PNG oil containing a lot of toluene could be due to dissolved concentration of these components.

6.4. Conclusion

From the above experiments it is evident that light oils have toxic properties towards acetate-utilizing SRB. This toxicity was not restricted to a single acetate-utilizing SRB species, but applied to a wide range of acetate-utilizing SRB. It is hard to say whether this toxicity can be generalized for all acetate utilizing SRB, but it is evident that certain species of acetate utilizing

SRB are affected by light oil toxicity which may extend to other species as well. There are certain components which seem to be more toxic than other, toluene seemed to be more toxic than pentane and heptane, which suggests that BTEX molecule of light oil could be playing a major role towards the toxicity.

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So, in an oil field where the produced waters have high acetate and sulfate concentration (e.g. PNG field, refer to chapter 4), there is the potential for acetate-utilizing SRB activity once oil is separated from these produced water. This may lead to souring in above- ground facilities once oil and water have been separated and sulfate is added as in the PNG CPF waters.

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7. Chapter seven: Conclusion

Light oil (rich in LMW alkanes and aromatic components) compared to heavy oil is the more valuable oil, and light oil can be toxic to certain micro-organisms (membrane toxicity). It is believed that there is little to no growth in diluent (LMW condensate) transporting pipelines, but the microbial community analysis of solids from the inside of pipeline showed the presence of microorganisms. Microbial activity analysis confirmed the presence of these microorganisms can be active. The corrosion rate analysis by weight loss method showed, one of the samples

(encrusted nodule) to be the most corrosive, and this sample also showed high methanogenic activity suggesting that methanogens could be the possible culprit. The encrusted nodule a protruding structure from the inside of the pipe wall was the only sample that showed high microbial activity. So it could be believed that encrusted nodule could be forming a protective cap on the pipe wall under which microorganisms were able to survive and proliferate. So in a low water and toxic environment like a diluent transporting pipeline, microorganisms could be surviving in these encrusted nodules. These methanogens can use iron (Fe0) as an electron

+ + donor, catalyzing iron H + CO2  methane + iron carbonate, H comes from water. Further study is needed in understanding the composition of these crusty nodules and in knowing how far they could protrude into the pipe wall. So this study contradicts the myth of microbial life is not able to survive in diluent transporting pipeline, and shows that they may not only survive but could also cause corrosion of the pipe walls.

The work on samples from a light oil producing field in Papua New Guinea showed the presence of significant sulfate and acetate concentrations in the central processing facility (CPF)

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waters. Produced waters and injection waters of the Gobe processing facility also showed the presence of high acetate. The produced waters had high MPNs of APB, whereas SRB were below the detection limit. CPF waters had low (zero) MPNs for SRB, whereas MPNs for solid samples were high in both APB and SRB, suggesting that biocide treatment was successful in the flowing parts of the operation, but did not reach these deposits. From the DNA analysis of corrosion incubations of 2014/2015 samples, it was observed that acetogens and methanogens might be playing crucial role in MIC. This was in agreement with results for sample PNG11 of

2013/2014 which showed the highest corrosion rate and highest methanogenic activity. High sulfate concentration of CPF waters could possibly be attributed to dosage of the biocide THPS in the CPF. Sulfate from THPS could accumulate in stagnant waters of CPF tanks. More work is needed to prove this definitively.

Another important part of this study was the impact of light oil toxicity on souring. It was observed that even though not all SRB are affected by light oils, but acetate-utilizing SRB activity was definitely inhibited in presence of light oil. This observation was not restricted to one species of acetate-utilizing SRB but to different species of acetate-utilizing SRB in enrichment. Different light oil and LMW condensate varied in their toxicity effect, based on their composition. Certain light oil components were more toxic to microorganisms than other, i.e. toluene was more toxic to acetate-utilizing SRB than pentane or heptanes. The concentrations of these components in light oil determine the toxicity of the oil. The toluene concentration in PNG oil was higher than in diluent, but diluent showed more toxicity towards acetate-utilizing SRB, because it had very high concentrations of pentane and heptane. So in an

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oil field like in Papua New Guinea with high sulfate and acetate in CPF waters, there is a potential for souring once of the oil removed from these waters.

In addition to SRB, methanogens and acetogens were found to be active groups of microorganisms in light oil producing fields. These do not contribute to souring but they can contribute to corrosion.

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Appendix:

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★

★ ★

★ ★ ★ O2 scav ★

O2 scav

Appendix Figure S1: Sampling locations (red circles, numbered) and corrosion hotspots () in the Agogo, Moran and Kutubu fields and the APF and CPF, as indicated.

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★ O2 scav

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Appendix Figure S2: Sampling locations (red circles, numbered) and corrosion hotspots () in the Gobe Main and Gobe SE fields as indicated.

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Appendix Figure S3: Sampling locations (blue circles, numbered) in the Agogo, Moran and Kutubu fields and the APF and CPF, as indicated.

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Appendix Figure S4: Sampling locations (red circles, numbered) in the Gobe Main and Gobe SE fields, as indicated.