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This manuscript provides case study data from subsea crude oil pipelines that addresses the questions of how to obtain the best quality samples from pig returns for microbiological testing, and what are the relative merits of different test methodologies.
Monitoring pipelines for microbial corrosion can be challenging because obtaining samples is difficult.
This is particularly true of subsea pipelines where the only available samples are oil samples and pig returns. Oil samples do not provide reliable data regarding microbial concentrations in biofilms on internal pipe surfaces and the heterogeneous nature of pig returns further complicates the situation by making it difficult to obtain representative samples. Moreover, there is no consensus regarding the best testing method to be used. Microbial growth tests have the longest history of use in the industry, but have more recently been questioned for being too slow, and for not providing comprehensive microbiological data. Test methods other than microbial growth tests, such as ATP (adenosine triphosphate) quantification and genetic testing (quantitative polymerase chain reaction or qPCR), can be used to monitor microbial populations in oilfield samples. This manuscript provides case study data from subsea crude oil pipelines that addresses the questions of how to obtain the best quality samples from pig returns for microbiological testing, and what are the relative merits of different test methodologies.
Key words: MIC, microbiologically influenced corrosion, subsea, pipeline, internal corrosion, genetic, qPCR, ATP, microbial growth tests, biofilm
A risk assessment model developed as part of a holistic study conducted to evaluate the condition of subsea pipelines. A systematic semi-quantitative risk-based model was developed to identify, analyze and evaluate risk associated with each subsea pipeline.
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A comprehensive test program is described quantifying the HISC performance of retrieved superduplex stainless steel subsea components and, comparing the actual performance against the limits derived following DNV RP F112: 2008.