Predictive pore-scale modeling of two-phase flow in mixed wet media

Abstract

We show how to predict flow properties for a variety of porous media using pore-scale modeling with geologically realistic networks. Starting with a network representation of Berea sandstone, the pore size distribution is adjusted to match capillary pressure for different media, keeping the rank order of pore sizes and the network topology fixed. Then predictions of single and multiphase properties are made with no further adjustment of the model. We successfully predict relative permeability and oil recovery for water wet, oil wet, and mixed wet data sets. For water flooding we introduce a method for assigning contact angles to match measured wettability indices. The aim of this work is not simply to match experiments but to use easily acquired data to predict difficult to measure properties. Furthermore, the variation of these properties in the field, due to wettability trends and different pore structures, can now be predicted reliably.