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University of Calgary
PRISM: University of Calgary's Digital Repository
Graduate Studies The Vault: Electronic Theses and Dissertations
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Transporting Light Hydrocarbon (Unpublished master's thesis).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
University of Calgary graduate students retain copyright ownership and moral rights for their
thesis. You may use this material in any way that is permitted by the Copyright Act or through
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Downloaded from PRISM: https://prism.ucalgary.ca
i
UNIVERSITY OF CALGARY
Souring and Corrosion in Light Oil Producing Reservoirs and in Pipelines Transporting Light Hydrocarbon
by
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
© Priyesh Menon 2015
ii
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.
iii
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.
iv
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
v
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
vi
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
vii
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
viii
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
ix
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
x
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
xi
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
xii
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
xiii
PWRI Produced water reinjection
PW Produced water
RNA Ribonucleic acid
SD Standard deviation
SO42- Sulfate
SS Sludge solids
SRB Sulfate reducing bacteria
THPS Tetrakishydroxymethylphosphonium sulfate
VFA Volatile fatty acids
1
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
2
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
3
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
4
be constituted by an electron donor (inorganic or organic substance) and an electron acceptor
like (SO42-, CO2
, 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
5
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).
6
Table 1.1. Light end components for different oils (data from Alberta Innovates, Blackmore et
al., 2014).
Crude Stream
C2 Minus
C3 Minus
C4 Minus
C5 Minus
C6 Minus
C7 Minus
C8 Minus
C9 Minus
Conventional Light Oil
0.03 0.49 4.47 7.78 13.47 20.56 27.70 33.21
Conventional Heavy Oil
0.02 0.09 1.48 5.49 8.60 11.43 14.07 16.27
Condensate (Diluent)
0.03 0.23 3.44 33.60 50.16 65.00 76.50 82.19
Note: Values are cumulative: C5 Minus includes (C1, C2, C3, C4, and C5).
7
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
8
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).
9
4H2 + SO42- + H+ → HS- + 4H2O (eq. 1)
Acetate- + SO42- → 2HCO3
- + HS- (eq. 2)
Propionate- + 0.75 SO42- → Acetate- + HCO3
- + 0.75 HS- + 0.25 H+ (eq. 3)
Butyrate- + 0.5 SO42- → 2 Acetate- + 0.5 HS- + 0.5 H+ (eq. 4)
Lactate- + 0.5 SO42- → 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)
8 e− + SO42− + 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
10
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).
8H+ + 4Fe + CO2 → CH4 + 4Fe2+ + 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
11
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)
12
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
13
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
14
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
15
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.
16
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
17
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
18
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
19
(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,
20
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
21
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
22
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.
23
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.
24
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 %
25
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
26
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.
27
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.
4Fe +SO42-+8H+ → FeS+3Fe2++4H2O (eq. 1)
8H ++ 4Fe + CO2 →CH4 + 4Fe2++ 2H2O (eq. 2)
For growth microorganisms require a carbon source (CO2 or an organic compound), an
organic or inorganic electron donor, an electron acceptor (usually SO42- 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)
28
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
29
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).
30
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
Figure 3.1: Samples from the inside surface of a pipeline (1-7 and 9) and diluent (8).
1 2 3 4 5 6 7 8 9
31
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).
32
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.
33
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.
34
Table 3.2. Chemical analyses of aqueous sample extracts.
Sample
Number
pH Ion analyses [Concentrations are in mM]
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
Number
VFA - mM
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.
35
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
Number
CR (mm/yr)
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
36
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
(dry, brown solids, containing crusty nodules). This was irrespective whether H2 or Fe0 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).
37
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.
0
500
1000
1500
2000
2500
0 50 100
(A) H2, CO2
0
500
1000
1500
2000
2500
0 50 100
(B) H2, CO2 sample 1
sample 2
sample 3
sample 4
sample 5
sample 6
sample 7
sample 9
control
0
500
1000
1500
2000
2500
3000
0 50 100
(C) N2, CO2
0
100
200
300
400
500
600
0 50 100
(D) N2, CO2
Time (Days)
Me
tha
ne
(µ
M)
Coupon Coupon
38
Table 3.6. Corrosion rates of duplicate coupons incubated with samples. Corrosion rate was
estimated by the weight loss method.
Sample (1 g)
medium (5ml)
weight before
(2 coupons)
weight after
(2 coupons)
weight loss CR (mm/yr)
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
39
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
H2 and CO2 (Fig. 3.2A, B) and with Fe0 and CO2 (Fig. 3.2C), had 14% of Methanobacterium, as
well as lower fractions of Methanoculleus and Methanosaeta. Members of the genus
40
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
41
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.
42
(A) Dendrogram (B) Phylum (C) Class
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.
Figure 3.4: Depiction of how microbes survive in diluent transporting pipeline under nodule
formation.
Sample 9
Sample 1
Sample 6
Sample 3
Sample 5
Sample 2
Sample 7
Sample 4
0.00.10.20.30.40 20 40 60 80 100
Proteobacteria EuryarchaeotaFirmicutes ActinobacteriaBacteroidetes PlanctomycetesOther phyla
0 20 40 60 80 100
Betaproteobacteria Gammaproteobacteria
Methanobacteria Bacilli
Actinobacteria Methanomicrobia
Alphaproteobacteria Sphingobacteria
Flavobacteria Other classes
methanogens
Nodule
Pipe wall
Pit
43
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
44
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).
45
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.
46
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.
47
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.]
1 2 3 4 5 6 7 8 9 10
11 12 13 14 15 16 17 18 19 20
48
Table 4.1: Name, label and appearance for 2013/2014 samples.
Group Sample
Name Sample Label Transcription Sample Appearance (Fig. 1)
I PNG1_PW ADD1 Clear water sample with oil layer on
top
I PNG2_PW Moran 9 Same as PNG1_PW
I PNG3_PW Upstream Agogo Separator (APF) Brown water sample with oil layer
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
II PNG8_FW CPF Slop oil Tank Water sample with yellow color; no
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
IV PNG16_PS G3X reinjection line (pigged
solids) Black solids with oil and water
IV PNG19_FS IDT3/IDT19, Filter Pod Wet solids, grey coloured
IV PNG20_PS Kumul Pig Receiver (Marine
Terminal) Black oily solids
Note: A more extensive description of these samples provided by the company is given in Table
S1 (Appendix).
49
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
50
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).
51
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.
52
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
53
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
0.0220.006 mm/yr. The average values were somewhat lower for injection and facility waters
(Table 3: Groups II and III, 0.0040.001 and 0.0180.007 mm/yr). The highest average corrosion
rates were observed for the solids samples (Group IV: 0.0360.004) mm/yr. This group also had
the highest MPNs for SRB (Table 4.2).
54
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”.
Grp Sample pH
NaCl Ion analysis –
mM VFA – mM MPNs
(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
55
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
56
Table 4.4: Methane and acetic acid production in incubations of 2013/2014 PNG samples in
the presence of iron beads.
SamplesMethane(µM)
InitialAcetate(mM) Finalacetate(mM) Change(mM)
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
57
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).
58
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
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.
0
50
100
150
200
250
0 5 10 15 20 25 30 35 40
Meth
an
e C
on
cen
tra
tio
n (
mM
)
Time (Days)
PNG 1
PNG 2
PNG 3
PNG 4
PNG 5
PNG 6
PNG 7
PNG 8
PNG 9
PNG 10
PNG 11
PNG 12
PNG 13
PNG 14
PNG 15
PNG 16
PNG 17
0
5
10
15
20
25
30
35
40
PN
G 1
PN
G 2
PN
G 3
PN
G 4
PN
G 5
PN
G 6
PN
G 7
PN
G 8
PN
G 9
PN
G 1
0
PN
G 1
1
PN
G 1
2
PN
G 1
3
PN
G 1
4
PN
G 1
5
PN
G 1
6
PN
G 1
7
Vo
lum
e o
f headsp
ace
repla
ced
with 9
0%
N2, 10%
CO
2 g
as
59
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
60
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
and CO2 (Fig. 4.2) and with Fe0 and CO2 (Table 4.4), had 10% of Methanobacterium and 11% of
61
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.
62
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.
(A) (B) (C)
63
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.
64
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 (0.80.4 mM; N=10) than the injection and facility water
samples (all without oil) from the Central Processing Facility (CPF), which had (2.32.0 mM;
N=4). Injection water samples from the Gobe Processing Facility (GPF) had (0.90.05 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 (5.83.0 mM;
N=10), similar to injection waters of the GPF (5.70.9 mM; N=2). Injection and facility water
samples from the CPF had very high acetate concentrations (40.226.0 mM; N=4), whereas
solids samples had low acetate concentrations (2.72.8 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.
65
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 0.0230.006 mm/yr for produced waters
(N=10), 0.0080.001 mm/yr for injection and facility waters from the CPF (N=3), and
0.0200.001 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
66
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.
67
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
68
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
69
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.
70
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.
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
71
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
beads
Bottle with
coupons
Sampling
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
72
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
73
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
74
(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.
75
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
(Meq)
Ammonium
(mM)
Ion analysis - mM VFA – 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
76
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
APB/ml
SRB
MPN/ml2
Log MPN
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.
Figure 5.2: Graphic representation of MPNs for APB and SRB for 2014/2015 samples.
0.00
2.00
4.00
6.00
8.00
10.00
8_1DT15 1_WIT 3-OWS 4_SDP 5_IS 6_CSTF 11_FH 12_PSVD 13_IWS 15_GPS 14_CP
Log
MP
N p
er
ml
MPN Results for PNG Samples
Log MPN APB/ml Log MPN SRB/ml
Group I Group II Group IV
77
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.
78
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.
79
Table 5.5. Survey of data collected for serum bottles used for corrosion rate measurements
Sample Weight
before
Weight
after
Weight
loss
Corrosion
rate
(mm/yr)
Methane
(M)
Sulfide
(mM)
Back
pressure
(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
80
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
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).
0
0.05
0.1
0.15
0.2
0.25
0.3
0.35
0.4
0.45
0.00 0.50 1.00 1.50 2.00 2.50
Averageweightloss(mg)
SDofresidualbead
weight(m
g)
81
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.
82
Figure 5.4: Methane concentration (μM) in the headspace of corrosion incubations,
containing either beads or coupons as indicated.
0
50
100
150
200
250
300
350
400
9_UAS 7_IDD4 2_IDT3 3_OWS
Co
nce
ntr
atio
n (
µM
)
beads
coupons
Group I Group II
83
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).
84
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
85
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.
86
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
87
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.
Note: Suffix B indicates beads, C indicates coupons and CS indicates coupon scrapings; B and C are planktonic samples; CS are biofilm 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
88
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
89
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.
90
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
91
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).
92
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.
93
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
94
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.
95
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.
96
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.
97
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.
98
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.
99
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).
100
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).
101
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).
102
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).
103
Table 6.3: Microbial community composition of SW enrichment1).
1) Data were obtained from Illumina sequencing; total number of good reads was 2217
#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
104
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.
105
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.
106
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
107
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.
Time (Days)
diluent CPM PNG Tundra
108
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
109
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.
110
Figure 6.6: BTEX molecule compositions (A) and Light molecular weight (LMW) alkane
compositions (B) of different oils.
0
50
100
150
200
250
300
350
PNG CPM MHGC Tundra Diluent
Co
nce
ntr
atio
ns
(mM
)
BTEX molecules composition (A)
Toluene
o-xylene
m/p-xylene
Ethylbenzene
0
20
40
60
80
100
120
140
160
180
200
C7 C8 C9 C10 C11 C12
Co
nce
ntr
atio
ns
(mM
)
LMW alkanes composition (B)
PNG
CPM
MHGC
Tundra
Diluent
111
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).
112
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.
113
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.
114
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.
115
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)
116
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
117
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.
118
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Appendix:
128
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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★O2scav
O2scav
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129
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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★O2scav
130
Appendix Figure S3: Sampling locations (blue circles, numbered) in the Agogo, Moran and
Kutubu fields and the APF and CPF, as indicated.
131
Appendix Figure S4: Sampling locations (red circles, numbered) in the Gobe Main and Gobe SE
fields, as indicated.