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

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This project aims to develop an efficient multi-scale modelling capability to quantify the effect of two-phase fluid flow within porous material by modelling rock wettability heterogeneity and alteration on two-phase flow performance for heterogeneous rock. Super-resolution methods combined with a deep learning approach will be used to determine a digital representation of reservoir rock, achieving an unprecedented combination of resolution necessary to resolve small-scale fluid connectivity and field of view required to capture heterogeneity. The project expects to develop a workflow to populate a high-resolution model with wettability parameters by combining micro-CT imaging with nuclear magnetic resonance measurements. This improved understanding should provide significant benefits by enhancing our capability to optimise enhanced oil and gas recovery programs.