Microbe-induced fluid viscosity variation: field-scale simulation, sensitivity and geological uncertainty

Abstract

Abstract This study is intended to expand the scope of microbial enhanced oil recovery (MEOR) simulation studies from 1D to field scale focussing on fluid viscosity variation and heterogeneity that lacks in most MEOR studies. Hence, we developed a model that incorporates: (1) reservoir simulation of microbe-induced oil viscosity reduction and (2) field-scale simulation and robust geological uncertainty workflow considering the influence of well placement. Sequential Gaussian simulation, co-kriging and artificial neural network were used for the petrophysical modelling prior to field-scale modelling. As per this study, the water viscosity increased from 0.5 to 1.72 cP after the microbe growth and increased biomass/biofilm. Also, we investigated the effect of the various component compositions and reaction frequencies on the oil viscosity and possibly oil recovery. For instance, the fraction of the initial CO2 in the oil phase (originally in the reservoir) was varied from 0.000148 to 0.005 to promote the reactions, and more light components were produced. It can be observed that the viscosity of oil reduced considerably after 90 days of MEOR operation from an initial 7.1–7.07 cP and 6.40 cP, respectively. Also, assessing the pre- and post-MEOR oil production rate, we witnessed two main typical MEOR field responses: sweeping effect and radial colonization occurring at the start and tail end of the MEOR process, respectively. MEOR oil recovery factors varied from 28.2 to 44.9% OOIP for the various 200 realizations. Since the well placement was the same for all realizations, the difference in the permeability distribution amongst the realizations affected the microbes’ transport and subsequent interaction with nutrient during injection and transport.

Keywords

• Artificial intelligence
• Viscosity-reducing microbe
• MEOR
• CMG STARS
• Geological uncertainty
• Enhanced oil recovery