Heterogeneous Carbonate Rock

Heterogeneous carbonate rocks pose significant challenges for accurate characterization due to their complex pore structures and mineral compositions. Current research focuses on developing advanced digital rock physics techniques, leveraging machine learning algorithms like Random Forests and novel image processing methods (e.g., incorporating Gaussian algorithms and 3D vision) to analyze high-resolution 3D images from micro-CT and MRI scans. These approaches aim to accurately predict key petrophysical properties such as permeability and porosity, improving reservoir modeling and ultimately enhancing hydrocarbon exploration and production efficiency. The improved accuracy and efficiency offered by these methods are transforming the field of carbonate reservoir characterization.