ABSTRACT
Quantifying sulfate-reducing microorganisms (SRMs) in oil reservoirs and production systems is important for understanding, predicting, and mitigating reservoir souring and biocorrosion. Monitoring SRM population size as well as understanding the factors that stimulate or inhibit growth contribute to informed management of microbiological control strategies. In recent years, molecular tools like quantitative PCR (qPCR) have gained preference relative to cultivation-based methods such as most probable number enumeration, due to advantages that include standardization, rapid throughput, and labor costs. However, a challenge facing probe- and primer-based oilfield screening is that tools developed based on “known” genetic diversity are used to screen “unknown” extreme environments, despite awareness that new microbial 214diversity is continually being discovered. DNA-based qPCR does not necessarily distinguish industrially relevant subpopulations, for example, active vs. dormant vs. dead cells; or sulfidogenic SRMs vs. SRMs that may be fermentative or reduce nitrate in oilfield environments. Distinguishing between these physiological categories influences decisions by operators, since different tools yield results that can over- or underestimate souring and biocorrosion risks. Here we discuss advantages, caveats, and new developments in SRM quantification by qPCR in order to refresh, update, and broaden the range of alternatives for consideration in the oil and gas sector.
