Detection and Monitoring of Corrosive Oilfield Microorganisms via Novel Biomarker Technologies

Abstract

Abstract Petroleum-transporting infrastructure can experience severe corrosion in the presence of microbial biofilms, a process termed microbially-influenced corrosion (MIC). However, not all microorganisms are corrosive and distinguishing corrosive from benign biofilms remains challenging with current technologies. In recent laboratory tests we identified two biomarkers suitable to discriminate corrosive methanogenic archaea (micH) and sulfate-reducing bacteria (micC) from their noncorrosive counterparts. In this study, we demonstrate suitability of newly developed qPCR assays, that target the specific microbial enzymes micH and micC, for field application. Water samples and pig debris were obtained from various oil-transporting pipelines that with high likelihood experienced MIC at the time of sampling as well as from pipelines without a perceived threat of MIC. Samples were analyzed with existing methods including 16S rRNA gene sequencing to identify the whole microbial community present in the samples and qPCR assays designed to enumerate total bacterial and archaeal populations. These results were compared to those obtained from the use of newly developed targeted qPCR assays for micH and micC. First we tested the novel assays on pig debris samples obtained from a North American pipeline in which active corrosion was suspected from recent in-line inspection (ILI) date. The results showed 5.6·104 gene copies of micH and 7.9·104 gene copies of micC per g of pig debris. In comparison, the micH and micC biomarker were not detected in a pipeline from the same field that did not show active corrosion. Subsequently, we tested the novel biomarker assays on more readily available produced water collected from an African oilfield. On average, 2.4·102 gene copies of micH/ml were measured in MIC-affected pipelines. The MIC biomarker micC, on the other hand, was detected at about 1.2·102 gene copies/ml in only one of the tested pipelines that experienced MIC. Intriguingly, neither micH nor micC were detected in wellhead fluids or other areas where MIC was not suspected. The correlation of micH and micC with active corrosion in oil field settings demonstrated the merit of these novel biomarker to serve as indicators of active MIC. Detection of the MIC biomarkers in water samples from affected pipelines would also allow efficient microbial monitoring independent of biofilm samples. This would allow easier implementation of this new biomarker technologies in the field. Furthermore, the detection of both biomarkers in samples from geographically distinct oil field operations points to global significance of these assays. MIC is notoriously difficult to detect and monitor with current technologies. The development of these novel MIC biomarker technologies enables, for the first time, the targeted detection of highly corrosive microbial communities to develop truly diagnostic and actionable data for MIC detection and mitigation.