A flow and transport model for simulation of microbial enhanced oil recovery processes at core scale and laboratory conditions

TL;DR

This work presents a general 3D flow-and-transport model for MEOR at core scale, derived from an axiomatic continuum-mechanics framework and implemented with finite elements in COMSOL to capture clogging/declogging and biosurfactant-driven interfacial-tension changes. It validates the flow component against Buckley-Leverett and coreflood benchmarks and validates clogging/declogging against Hendry 1997 data, then demonstrates application to a Berea core MEOR case with field microbes, achieving agreement with recovery histories. The framework integrates dynamic porosity and permeability, Monod microbial kinetics, and a trapping-number based adjustment of residual oil and relative permeabilities, and is designed for easy extension to other EOR scenarios and constitutive laws.

Abstract

A general 3D flow-and-transport model in porous media is derived using an axiomatic continuum-mechanics approach and implemented with the finite element method to simulate microbial enhanced oil recovery (MEOR) at core scale under laboratory conditions. The development pipeline (conceptual -> mathematical -> numerical -> computational) is detailed. The model captures clogging/declogging from biomass, changes in interfacial tension due to biosurfactant, and the resulting impact on relative permeability, capillary pressure, and residual oil saturation via a trapping-number framework. The flow model is validated (Buckley-Leverett and coreflood benchmarks); transport (microbes/nutrients/surfactant) is validated against Hendry et al. 1997 breakthrough data. Finally, the model accurately predicts a Berea-core MEOR case study using field microbes and brine, matching recovery histories with small RMS error. Owing to its generality, the framework can be extended to other EOR scenarios and constitutive laws.

Figures (32)

• Figure 1: Flow diagram of the Modeling Methodology.
• Figure 4: Flow chart of the numerical model
• Figure 5: Numerical solutions of the Buckley--Leverett problem with linear relative permeabilities and viscosity ratio $\mu _{w}/\mu _{o} =1$ for a period of 300 days, varying artificial diffusion coefficient ($\varepsilon$).
• Figure 6: Numerical solutions of the Buckley--Leverett problem with linear relative permeabilities for case (a) and viscosity ratio $\mu _{w}/\mu _{o} =2$ for time periods from 300 to 900 days.
• Figure 7: Numerical solutions of the Buckley--Leverett problem case (b) with linear relative permeabilities and viscosity ratio $\mu _{w}/\mu _{o} =2/3$ for a period of 300 days, varying artificial diffusion coefficient ($\varepsilon$).