Enhanced permeability estimation in microporous rocks using a hybrid macropore-Darcy approach

This study presents a new implementation for constructing hybrid macropore-Darcy models from micro-CT images of microporous rocks. In our approach, macropore networks are extracted using established methods, while the microporosity is characterised through segmented phase classification and incorporated into the model as Darcy cells. Effectively, Darcy cells capture the micro scale connectivity variations that are missing in the macroscopic networks. This dual-entity model thus incorporates both the conventional macroscopic pore structure and the critical flow pathways present in the under-resolved microporous regions. The proposed workflow is rigorously validated by comparing the permeability estimates with direct numerical simulation results and experimental measurements. Our findings demonstrate that this hybrid approach reliably reproduces fluid flow behaviour in heterogeneous porous media while substantially reducing computational demands, offering a promising tool for advanced groundwater modelling and water resource management. A key advantage and novelty of our work is the application and validation of the modelling framework in numerically large and computationally demanding domains derived from representative images of reservoir rock containing one billion voxels or more.