Modeling the Formation of Fluid Banks During Counter-Current Flow in Porous Media

Abstract

Fluid banks sometimes form during gravity-driven counter-current flow in certain natural reservoir processes. Prediction of flow performance in such systems depends on our understanding of the bank-formation process. Traditional modeling methods using a single capillary pressure curve based on a final saturation distribution have successfully simulated counter-current flow without fluid banks. However, it has been difficult to simulate counter-current flow with fluid banks. In this paper, we describe the successful saturation-history-dependent modeling of counter-current flow experiments that result in fluid banks. The method used to simulate the experiments takes into account hysteresis in capillary pressure and relative permeabilities. Each spatial element in the model follows a distinct trajectory on the capillary pressure versus saturation map, which consists of the capillary hysteresis loop and the associated capillary pressure scanning curves. The new modeling method successfully captured the formation of the fluid banks observed in the experiments, including their development with time. Results show that bank formation is favored where the p c -versus-saturation slope is low. Experiments documented in the literature that exhibited formation of fluid banks were also successfully simulated.

Nonmonotone Saturation Profiles for Hydrostatic Equilibrium in Homogeneous Porous Media

“…Although the qualitative agreement is encouraging, it is not conclusive because it is not clear to what extent the experimental conditions agree with the theoretical approximations. Recent attempts to model these observations based on the traditional theory require history matching, a complicated hysteresis model, and advance knowledge of multiple capillary pressure and relative permeability (boundary and scanning) curves (see Li et al, 2006; Schaerer et al, 2006). Contrary to this, our theory seems to be able to reproduce all experimentally observed profiles from a single parameter set.…”