Pore-by-Pore Modelling, Validation and Prediction of Waterflooding in Oil-Wet Rocks Using Dynamic Synchrotron Data

Abstract We predict waterflood displacement on a pore-by-pore basis using pore network modelling. The structure is captured by high-resolution image. then use an energy balance applied to images of the assign average contact angle, and modify local pore-scale angles in model about this mean match observed sequence. Two waterflooding experiments oil-wet rocks are analysed where sequence was imaged time-resolved synchrotron imaging. In both cases capillary pressure matches experimentally obtained values derived from measured interfacial curvature. relative permeability for full saturation range. Using optimised distributed randomly space has little effect predicted pressures permeabilities, indicating that spatial correlation wettability not significant these samples. calibrated can be used properties outside range conditions considered experiment.