Modeling of capacitance flow behavior in EOS compositional simulation

Abstract

Abstract Gas injection is a widely used method for enhanced oil recovery. Oil bypassing by gas occurs at different scales because of micro and macroscopic heterogeneities, gravity segregation, and front instability. Part of the bypassed oil can be recovered by crossflow between the bypassed and flowing regions. This characteristic of reservoir flow is referred to as capacitance flow behavior in the literature. Modeling of such flow behavior at the sub-grid scale is challenging in the conventional flow simulation since fluids are perfectly mixed and in equilibrium within individual grid blocks under the local equilibrium assumption. This research investigates capacitance flow behavior in compositional reservoir simulation. An efficient two-step method is presented to model bypassed oil recovery in multiphase compositional flow simulation of gas floods. The oil bypassing is first quantified by use of the dual-porosity flow with two dimensionless groups; bypassed fraction and throughput ratio. To represent bypassed oil recovery in single-porosity flow, a new flow-based fluid characterization is applied to part of the heavy fractions of the fluid model used. Properties for pseudo components can be determined based on the throughput ratio estimated in the dual-porosity flow. Case studies for various reservoir/fluid properties show that single-porosity flow with the new method reasonably represents bypassed oil recovery observed in core floods and fine-scale heterogeneous simulations.