Numerical Modeling on the Influence of Effective Porosity, Microbial Kinetics, and Operational Parameters on Enhanced Oil Recovery by Microbial Flooding Within a Sandstone Formation

During the implementation of a microbial-enhanced-oil-recovery (EOR) (MEOR) technique in a sandstone formation, various reservoir physicochemical, microbial kinetic, and operational parameters play major roles in governing the efficiency of crude-oil recovery from a hydrocarbon reservoir. The present study numerically investigates the sensitivity of sandstone formation effective porosity; different injected strains of the species Bacillus under optimal metabolic conditions and possessing distinct values of maximum microbialspecific-growth rate, Monod saturation constant, and yield coefficient; and crucial operational parameters on biomass and biosurfactant production and their effects on microscopic oil-displacement efficiency within the sandstone reservoir, along with prompting modifications in rock physicochemical properties. A black-oil biochemical multispecies reactive transport model in porous sandstone media is developed by coupling the kinetic model with the corresponding transport model involving microbial sorption. The governing equations involve coupled transport of nutrients and microbes by dispersion and convection, growth and decay rates of microbes, chemotaxis, nutrient consumption, and deposition of microbes and nutrients on rock-grain surfaces caused by reversible/irreversible sorption. Coupled empirical equations are used to estimate biosurfactant production, oil/water-interfacial-tension (IFT) reduction, change in the viscosity of injection fluid, and their effects on oil relative permeability and mobility, and thus a decrease in residual oil saturation within the reservoir. The finitedifference-discretization technique is adopted to solve the governing equations. Results of the present model are found to be numerically stable and match very well, when verified, with the previously published analytical, numerical, and experimental results. The model results suggest that at very low reservoir porosity (approximately 10%), an early breakthrough of nutrients, microbes, and biosurfactant leave insignificant concentrations in their respective fronts, which are insufficient for the recovery of the trapped oil. Also, increase in porosity to approximately 30% and beyond causes loss of nutrients, microbes, and biosurfactant because they undergo higher dispersion during their transport within the reservoir. Thus, sandstone formations possessing an intermediate effective porosity value of approximately 20% significantly enhance the efficiency of the overall MEOR process. Further, it is observed that the nature of microbes and nutrients used for MEOR application affect biosurfactant production, and in turn oil recovery, to a large extent. Those microbial species with far lower Monod-saturation-constant values have high affinity toward their substrates. This phenomenon dramatically increases the rates of nutrient consumption and production of biomass and biosurfactant within a reservoir when suitable substrate compounds are used, irrespective of differences in the yield coefficients of the microbes. Further MEOR simulation studies within a sandstone core exhibited maximum oil displacement and recovery at a run time of 5 hours, injected-microbial concentration of 4.32 10 mg/cm, and maximum specific growth rate of 0.35 hours. Bioplugging-induced formation damage negatively affecting the oil-recovery efficiency is also observed with an increase in the process run time. The screened microbe also exhibited the possibility of wettability alteration of sandstone-formation rock from mixed/oil-wet to water-wet. Thus, the present study provides an improved understanding of the combined effects of reservoir porosity, microbial kinetic, and key operational parameters on fundamental MEOR processes, which will better characterize and develop an effective strategy to determine the suitability of an MEOR technique in a typical sandstone reservoir. Moreover, the developed numerical model is easier to implement and produces faster results with relatively lower computational cost, which helps in making a quick decision before applying MEOR processes in the field.