Sulphate-reducing prokaryotes (SRP) have been identified in oil field fluids since the 1920s. SRP reduce sulphate to sulphide, a toxic and corrosive species that impacts on operational safety, metallurgy and both capital and operational cost. Differences in water cut, temperature, pressure and fluid chemistry can impact on the observed H2S concentration, meaning that an increase in H2S concentration does not always correlate with activity of SRP. However it wasn’t until the 1990s that SRP activity was accepted as the leading cause of reservoir souring (i.e. an increase in H2S concentrations) in water flooded fields. The process of sulphate-reduction has been well documented at the genetic, enzymatic and physiological level in pure cultures under laboratory conditions. DNA sequencing has also identified new groups of microorganisms, such as archaea which are capable of contributing to reservoir souring. This has led to some recent advances in microbial control and detection, however, despite this, many of the methods used routinely for microbial control and detection are over a century old. We therefore look towards emerging and novel mitigation technologies that may be used in mitigating against reservoir souring, along with tried and tested methods Modelling and prediction is another important but often under-used tool in managing microbial reservoir souring. To be truly predictive, models need to take into account not only microbial H2S generation but also partitioning and mineral scavenging. The increase in ‘big data’ available through increased integration of sensors in the digital oil field and the increase in the DNA sequencing capabilities through next-generation sequencing (NGS) therefore offer a unique opportunity to develop and refine microbial reservoir souring models. We therefore review a number of different reservoir souring models and identify how these can be used in the future. With this comprehensive overview of the current and emerging technologies we will highlight areas where significant development effort could generate rewards that can improve detection, prediction and control of microbial reservoir souring.
Copyright © 2017. Published by Elsevier B.V.