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Microbiologically influenced corrosion has been attributed to the activity of sulfate reducing and acid producing bacteria. Advances in DNA isolation and sequencing have revealed that these classes of bacteria often represent only a small portion of the corrosive microbial population present in the oil and gas environment.
Microbiologically influenced corrosion has historically been attributed to the activity of sulfate reducing and acid producing bacteria. Recent advances in DNA isolation and sequencing have led to the realization that these two classes of bacteria often represent only a small portion of the corrosive microbial population present in the oil and gas environment. Numerous different genera from multiple other classes of bacteria and archaea have been found to be associated with failures and are now recognized as contributors to the MIC process. The presence of these microbes while not frequently identified through standard oil and gas industry culturing techniques is now readily discernable through the use of next-generation DNA sequencing platforms. This workbuilds on a paper from CORROSION 2014that introduced a database with speciation results from over 4000 oilfield samples. However the current paper discusses analyses that were performed on this database which has grown to over 6000 samples to discern the global distribution and relative incidence of several classes of these newly recognized contributors to MIC; bacteria and archaea capable of iron reduction and oxidation sulfur/sulfide oxidation as well as methanogenesis. This new understanding of the MIC-related oilfield microbial population will allow us to design better monitoring and treatment strategies that do not simply focus on sulfate reducers and acid producers.
Key words: conference papers, 2015 conference papers, downloadable, microbiology, bacteria, archaea, DNA sequencing, MIC, methanogen
We describe the advancement of an activity-based quantitative polymerase chain reaction (qPCR) assay which can distinguish live from dead corrosion influencing microorganisms in oil and gas pipeline environments. We discuss the limitations and possible future optimization methods for Propidium monazide-qPCR techniques in the industry.
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The objective of this paper is to provide a review of various models and methods that have been developed and applied by both researchers and industry professionals to better understand and predict MIC.