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A laboratory flow loop is used to evaluate the ability of an on-line, electrochemical, biofilm-activity probe to monitor biofilm activity in synthetic oilfield brine and correlate its activity to localized pitting corrosion. In addition, bio-traps containing porous polymer beads for trapping biomass are evaluated as a rapid means to evaluate biofilm community structure.
A laboratory flow loop is used to evaluate the ability of an on-line, electrochemical, biofilm-activity probe to monitor biofilm activity in synthetic oilfield brine and correlate its activity to localized pitting corrosion. In addition, bio-traps containing porous polymer beads for trapping biomass are evaluated as a rapid means to evaluate biofilm community structure using phospholipid fatty acid (PLFA) and DNA analysis. Results suggest that applied current as measured by the electrochemical probe can be used to detect biofilm activity in produced oilfield brine and can be used to evaluate the effectiveness of biocide treatments. However, biofilm activity did not always correlate with pitting corrosion conditions. Biofilms collected by biotraps during periods of pitting and non-corrosive conditions, however, displayed distinctly different microbial communities as determined by PLFA and DNA analysis. Furthermore, the biofilm microbial communities in bio-traps and on metal coupons were similar, except during biocide application, suggesting that bio-traps could be used as a rapid means to evaluate biofilm community structure on metal surfaces.
Keywords: Monitoring, electrochemical, on-line, bio-traps, MIC, oilfield brine
An analytical approach that can discriminate between various forms of microscopic corrosion initiation has been employed in natural gas gathering and storage facilities. Information provided by the analysis of electron microscope coupons has led toward the better understanding and diagnosis of the initial stages of internal corrosion in natural gas gathering and storage facilities.
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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.