This study highlights the modeling of an expert system for the classification of internal microbiologically influenced corrosion (MIC) failures related to pipelines in the upstream oil and gas industry. The model is based on artificial neural networks (ANNs) and involves the participation of 15 MIC experts. Each expert evaluated a number of model case studies ranging from MIC- to non-MIC-driven upstream pipeline failures. The model accounts for variations in microbiological testing methods, microbiological sample types, and degradation morphology, among other variables. It also accounts for missing datasets, which is commonly the case in actual failure assessments. The outcome is an expert system model whose outputs are classes (classification ANN) which comprises MIC potential and data confidence. The performances of two approaches are contrasted in this study. One classifies the output in 5 classes, a 5-output classification (5OC) model; the other in 3 classes, a 3-output classification (3OC) model. The 5OC model had an accuracy of 62.0% while the simpler 3OC model had a better accuracy of 74.8%. This modelling exercise has demonstrated that knowledge from experts can be captured in a reasonably effective model to screen for possible MIC failures. It is hoped that this study not only may contribute to a better understanding of the prevalence of MIC in the oil and gas sector, but also may highlight the key areas necessary to improve the diagnosis of MIC failures in the future.

Microbiologically influenced corrosion (MIC) is a phenomenon of increasing concern that affects various materials and sectors of society. MIC describes the effects, often negative, that a material can experience due to the presence of microorganisms. Unfortunately, although several research groups and industrial actors worldwide have already addressed MIC, discussions are fragmented, while information sharing and willingness to reach out to other disciplines are limited. A truly interdisciplinary approach, which would be logical for this material/biology/chemistry-related challenge, is rarely taken. In this review, we highlight critical non-biological aspects of MIC that can sometimes be overlooked by microbiologists working on MIC but are highly relevant for an overall understanding of this phenomenon. Here, we identify gaps, methods, and approaches to help solve MIC-related challenges, with an emphasis on the MIC of metals. We also discuss the application of existing tools and approaches for managing MIC and propose ideas to promote an improved understanding of MIC. Furthermore, we highlight areas where the insights and expertise of microbiologists are needed to help progress this field.

Biofilms are widely recognised as a contributing factor in significant problems currently facing human health and industry. The following paper summarises a round table forum held at the 2021 International Biodeterioration and Biodegradation Symposium which discussed the potential role of standards in biofilm research and industry innovation. Standards and other forms of best-practice guidance are reviewed in an academic research context as well as in relation to industry impacts and product development. The understanding of fundamental aspects of biofilms is rapidly evolving, driven in part by new analytical methods. However, the complex and multidisciplinary nature of biofilm-associated problems and typically limited training available for industry personnel tackling the associated issues often reduces the ability to provide best-practice solutions. As such it is argued that more effort needs to be made by both academia and industry experts to provide consensus and associated documentation on standard test methods or guidance documents related to studying and combating biofilms.

Microbiologically influenced corrosion (MIC) is an integrity threat to engineered assets in many sectors, including drinking water, waste water treatment, industrial cooling water, chemical processing and energy production, transmission, and distribution systems in which water is present. Management of corrosion threats, including MIC, is best addressed through the use of a corrosion management system that comprehensively serves to identify and mitigate threats, as described by NACE International and ISO standards. In the last decade, the use of molecular microbiological methods (MMM) has helped asset owners and operators gain new insights into MIC susceptibility and improve their ability to manage MIC. Industry consensus standards have guided the implementation of MMM in various assets, particularly the oil and gas industry. Several new standards are currently being developed that further help advance the use of MMM, and other international initiatives are underway to broaden the exposure of these tools to more end users. These molecular tools and standards will help achieve the goals of increasing sustainable use of resources and development of clean energy to reduce the carbon emissions. To achieve these goals, asset managers will require young smart minds and well-developed, state-of-the-art consensus standards to drive reduction of operating risk, help extend asset life, and move the engineered environment toward greater sustainability.

Introducing water into pipelines for various applications, such as hydrotesting, long term layup, hydraulic fracturing, water injection, and other production related activities poses the threat of microbiologically influenced corrosion (MIC) when conditions are favorable. The focus of this paper is to outline a test method to evaluate the potential for MIC with untreated waters and subsequently assess the effectiveness of biocides to inhibit biofilm growth and mitigate MIC. The changes in the microbial activity, abundance, and diversity in the biofilm along with pitting and general corrosion rates on the carbon steel are used as evaluation techniques in this laboratory test method. The results of this work demonstrate the importance of using biofilms for biocide evaluations and could be used to support new industry standards for evaluating the effectiveness of biocides for MIC control, rather than basing performance on planktonic kill studies.

The NACE IMPACT study published in 2016 determined that the annual global costs associated with corrosion are $2.5 trillion USD. Reducing corrosion costs can be achieved with effective corrosion management procedures and programs. Conducting root cause analysis on corrosion failures is a crucial aspect for effective corrosion management. Root cause analysis of corrosion failures involves three steps: (1) identification and confirmation of the corrosion mechanism that caused the failure; (2) identification of the contributing factors that led to the failure and highlighting the barriers to prevent the failure and mitigate the consequence of failure; and (3) review of the management systems in place to identify systematic issues so as to prevent reoccurrence. In this chapter, the framework for root cause analysis of corrosion failures was discussed in detail with an emphasis on MIC as the corrosion mechanism. This framework can be applied when investigating the root cause of any corrosion-related failure. A case study on root cause analysis of a corrosion failure on injection well tubing in an oilfield was also presented to demonstrate the application of the framework for root cause analysis.

Hydrotesting, long-term layup (i.e., wet parking), hydraulic fracturing, water injection for enhanced oil recovery, and other oilfield-related activities involving water may pose the threat of microbiologically influenced corrosion (MIC) when conditions are favorable. Laboratory testing using biofilms can provide an effective and reliable means to evaluate the potential for MIC, and subsequently, to assess the effectiveness of biocides to inhibit biofilm growth and mitigate MIC during hydrotesting and wet parking. Industry best practices have advanced such that today, more emphasis is being placed on using biofilms for biocide evaluations, rather than basing performance on planktonic kill studies.

In the past decade, molecular microbiological methods (MMM) have significantly expanded the understanding of the microbial populations in several environments, including oilfields and associated infrastructure. These methods are now highly regarded as accurate, comprehensive, and useful to aid the optimization of microbial control strategies. The resulting information has helped operators and service companies to better assess the threat of microbiologically influenced corrosion (MIC) and act upon it. Nonetheless, despite finding acceptance in the industry, the results from these methods can greatly vary from lab to lab, due to the lack of a standardized protocol. In this study, we describe the joint effort of an initiative between operators, service companies, 3rd party labs and universities to establish a consensus on how to properly collect and preserve samples for molecular analysis, and agree on a set of lab protocols to allow comparable results. We show how all the stakeholders used science-based conclusions to decide on the most comprehensive protocols that balances easiness of use in the field and accuracy of results. This industry-wide effort to standardize these methods will have a profound impact on data collection, quality of data and assessment of microbiological threats in the field.

MIC is a multidisciplinary subject that draws upon various analytical methods to characterize the roles of chemistry, microbiology, materials and metallurgy, and corrosion science when investigating the cause of corrosion damage. Every analytical method has strengths/limitations and produces results that must be interpreted in the correct context. The use of multiple analytical methods for MIC investigation can provide complementary information on the different dimensions of sample characterization, for example, enumeration, diversity, and activity of microorganisms. Further, a robust diagnosis of MIC relies upon the integration of results from different methods of analysis. This chapter introduces many of the analytical methods used in MIC failure investigation today.

Corrosion coupons are one of the most frequently used methods to measure the severity of corrosion in oil and gas pipelines. Typically, operators use weight loss coupons to determine rates of general corrosion and occasionally pitting. Extended analysis (EA) coupons are less frequently used but can provide additional information such as rate of pitting and the corrosion mechanism which are critical when evaluating the need for additional information or considering the most effective course for mitigation. Improper mitigation can result in wasted time, resources, or worsened corrosion rates in some instances; therefore, proper understanding of corrosion rates and mechanisms is a critical step in the corrosion management process. Examples of analysis methods that are frequently applied to EA coupons include optical profilometry, scanning electron microscopy (SEM), energy dispersive x-ray spectroscopy (XRD), and biological characterization methods such as quantitative polymerase chain reaction (qPCR) and adenosine triphosphate (ATP). This paper discusses these different analysis methods and the significance of the data obtained and presents a case study where a mitigation plan was developed based in part on the active corrosion mechanism identified using EA coupons.

These SOPs were developed as part of geno-MIC (Managing Microbial Corrosion in Canadian Offshore and Onshore Oil Production Operations), a large-scale applied research project funded by Genome Canada, Genome Alberta, Alberta Innovates, InnoTech Alberta, Government of Newfoundland and Labrador, and Mitacs, with in-kind support from Natural Resources Canada (CanmetMATERIALS), Genome Atlantic, Baker Hughes, BP, Brenntag, CRC, DNV GL, Dupont, Enbridge, Husky Energy, LuminUltra, Marathon, Microbial Analysis, Nalco Champion, OSP, Promega, Schlumberger, Shell, Suez, TransMountain, and United Initiators.

Elemental sulfur is a mechanism of internal corrosion, similar to microbiologically influenced corrosion, that can result in extremely aggressive and rapid attack of carbon steels in the oil and gas industry. The typical morphology of the attack associated with elemental is characterized by small, isolated pits with narrow openings. Environmental factors that influence this corrosion mechanism include the presence of oxygen, chloride content, and the ratio of carbon dioxide to hydrogen sulfide in the transported media. This chapter presents a case study where elemental sulfur was attributed to the unexpected corrosion experienced within a newly constructed pipeline. The case study outlines the metallurgical evidence and operational history that was used to identify the mechanism and how microbiological analyses were key in identifying the corrosion mechanism. Deficiencies in the mitigative and preventative measures applied to the line and recommendations to address these deficiencies are also discussed.

Failure analysis and root cause analysis (RCA) of corroded pipelines and piping system components can provide operators with valuable information to help prevent future failures while optimizing mitigation costs. If a corroded pipe sample is not handled or preserved properly because of inadequate planning, the ability to diagnose the corrosion mechanism(s) is lost. Using some basic steps for preparation and investigation, operators can determine the applicable corrosion mechanism(s) causing the corrosion and implement or adjust the measures taken to mitigate the corrosion. Collecting multiple lines of evidence about chemical and microbiological conditions, corrosion products, and operating parameters is essential. Further, with the increasing use of molecular microbiological methods (MMM), the role of microorganisms can be determined with greater certainty than has been possible in the past. Targeting mitigation measures to only the applicable corrosion mechanism(s) can support mitigation cost optimization, such as by applying only the correct chemical treatments rather than an all-encompassing “security blanket” approach.

This chapter highlights a review and analysis of MIC-related pipeline incidents in the province of Alberta, Canada, over a three-year period (2017–2019). The intent of this work was to quantify the occurrence of MIC failures relative to other corrosion mechanisms, and to conduct a gap analysis of MIC failure investigation techniques being used relative to the current state of the art. Over this three-year period, MIC was found to be responsible for 13.6% and 4.8% of all pipeline leak incidents due to internal and external corrosion, respectively, either as the main failure mechanism or as a contributing factor. Most of these failures were seen to occur in small diameter upstream pipelines (with less than or equal to 220.3 mm outside diameter) carrying mainly multiphase fluids (oil-water emulsions) or produced water. In terms of the failure investigation methods currently being used, it was noted that there was some inconsistency among reports and a number of important gaps were identified. Various assessments lacked microbiological test data, in particular, tests which specifically identify microbial functional groups or speciation, which is critical to confirm observed corrosion mechanisms. Furthermore, a number of these assessments identified MIC primarily on the basis of corrosion morphology, which has been shown to be an incorrect assumption and approach without additional evidence. Details related to sampling methods were also lacking in these assessments, which created some uncertainty as to the quality of data obtained. Overall, most assessments did a reasonable job in characterizing and including chemical (solids, fluids and corrosion products), metallurgical, and operating data. However, the integration of these various layers of evidence (i.e., connecting corrosion to microbiological activity, and eliminating possible abiotic corrosion mechanisms) was missing in many reports and would have significantly strengthened the final assessment conclusions. It is hoped that this analysis contributes to a better understanding of the prevalence of MIC in the oil and gas sector, and highlights the key areas necessary to improve the diagnosis of MIC failures in the future.

The investigation of pipeline corrosion failures, including those caused by microbiologically influenced corrosion (MIC), requires multiple lines of evidence to identify causative mechanisms and contributing factors. The types of evidence needed for the corrosion analysis include information about the design and history of operation of the asset; the physical, environmental, and metallurgical conditions present where corrosion is observed; and microbiological conditions. Next, this information is integrated and analyzed to assess whether biotic or abiotic processes were responsible for the failure. While the ability to diagnose MIC in the oil and gas industry is improving, practical limitations associated with sample collection in remote locations or from inside pipelines still present challenges to conclusively determine the cause.

Studies in microbiologically influenced corrosion (MIC) have reported on the effects of pre-corrosion surface deposits on the localized pitting which occurs on metals. But due to the complexity and heterogeneity of these deposits, which include biofilms, it is necessary to investigate how the components of these deposits and the conditions therein influence the formation of pits on the metal surfaces. To gain a better understanding of the occurrence and growth of pits under these deposits, it is imperative to consider their interactions with the metal surface at the atomistic level. In this work, molecular modelling is used to study these interactions, with the focus being on parameterizing the role of HS− in microbiologically influenced pitting. The bond length of HS− is used as a predictive parameter in the molecular model to study the MIC interface. It is observed that changes in the HS− bond length denote HS− reactivity and the subsequent production of sulfides which are the main by-products of MIC. This study also shows how changes in temperature impact HS− reactivity and thus MIC activity.