X-ray imaging and magnetic resonance approach for enhanced oil recovery

This project aims to develop an efficient multi-scale modelling capability to quantify the effect of wettabilityheterogeneity and alteration on two-phase flow performance for heterogeneous rock. Super-resolution methodscombined with a deep learning approach are utilized to determine a digital representation of reservoir rock,achieving an unprecedented combination of resolution necessary to resolve small-scale fluid connectivity and fieldof view required to capture heterogeneity. We propose a workflow to populate such a high-resolution model withwettability parameters by combining a micro-CT imaging approach with NMR measurements. This would greatlyenhance our capability to optimise enhanced oil and gas recovery programs.