Pore Network Model Predictions of Darcy‐Scale Multiphase Flow Heterogeneity Validated by Experiments
Christopher Zahasky, Samuel J. Jackson, Qingyang Lin, Samuel Krevor
Abstract
Abstract Small‐scale heterogeneities in multiphase flow properties fundamentally control the flow of fluids from very small to very large scales in geologic systems. Inability to characterize these heterogeneities often limits numerical model descriptions and predictions of multiphase flow across scales. In this study, we evaluate the ability of pore network models (PNMs) to characterize multiphase flow heterogeneity at the millimeter scale using X‐ray micro‐computed tomography images of centimeter‐scale rock cores. Specifically, PNM capillary pressure and relative permeability output are used to populate a Darcy‐scale numerical model of the rock cores. These pore‐network‐derived Darcy‐scale simulations lead to accurate predictions of core‐average relative permeability, and water saturation, as validated by independent experimental data sets from the same cores and robust uncertainty analysis. Results highlight that heterogeneity in capillary pressure characteristics is more important for predicting local and upscaled flow behavior than heterogeneity in permeability or relative permeability. The leading uncertainty in core‐average relative permeability is driven not by the image processing or PNM extraction but rather by ambiguity in capillary pressure boundary condition definition in the Darcy‐scale simulator. This workflow enables characterization of local capillary heterogeneity and core‐averaged multiphase flow properties while circumventing the need for the most complex experimental observations conventionally required to obtain these properties.