Generalized network modelling of two-phase flow in a water-wet and mixed-wet reservoir sandstone: Uncertainty and validation with experimental data

We use a generalized pore network model in combination with image-based experiments to understand the parameters that control upscaled flow properties. The study is focued on water-flooding through reservoir sandstone under water-wet and mixed-wet conditions. A set of sensitivity studies presented quantify role wettability, geometry, initial boundary conditions as well selection used computation fluid volumes, curvatures electrical conductivities. uncertainty predictions, which match measured relative permeability capillary pressure within experiments. Our results show contact angle, saturation, image quality processing algorithm are amongst introduce largest variance predictions properties for both