Microbial Sulfate Reduction in Underground Reservoirs: Learnings from Full-Field Modeling and Field Data

Abstract

Summary Sulfate-reducing microorganisms are found in various environments, such as shallow marine and freshwater sediments, groundwater, hydrocarbon reservoirs, hydrothermal vents, and mud volcanoes. The reduction of sulfate to hydrogen sulfide (H2S) by sulfate-reducing microorganisms, usually during and after flooding oil reservoirs with seawater (SW), is known as microbial reservoir souring. H2S is a hazardous and corrosive gas, which increases the treatment costs of the produced fluids. Other than the microbiological aspect of this phenomenon, the interplay among the physical aspects of the multiphase flow and (bio)chemical reactions at various scales in the porous media of the subsurface can significantly contribute to the complexity of the problem. This study investigates real field data of several wells in an oil field in the Danish North Sea and presents a modified reservoir souring model coupled with a full-field reservoir model. The effect of various parameters on the production composition data is investigated, and, under various sets of assumptions, the model is matched against the history of the production data. The results demonstrate that sulfate concentration data in the produced water can be a useful compliment to the more common H2S concentration data in the produced gas when tuning the model, thus predicting the future of souring in the field. Moreover, it is shown that the production data can be used to infer the activity of various microbial communities in different locations of the reservoir. Interestingly, the data suggest that the change in the near-wellbore environment during drilling and the completion or the production wells may activate or introduce strains of sulfate-reducing microorganisms, which are responsible for the increase in H2S content in the produced gas during the early stages of production. Microbial souring in the waterflooded regions, on the other hand, corresponds to the increase in H2S production in the later stages of production. Furthermore, it is shown how different sectors of the same field show different souring behaviors and macroscale growth rates (GRs), which are attributed to different elements that affect flow patterns, such as the presence of darcy-scale heterogeneity and fractures. Additional Keywords sulfate reducing microorganisms; microbial reservoir souring; history matching; reactive transport modeling; reservoir simulation