Enhancing Carbonate Reservoir Permeability Using a Novel Porosity Model

Carbonate reservoirs hold a significant portion of the world’s hydrocarbon resources. However, they present a significant challenge in determining reservoir permeability utilizing standard evaluation techniques. Previous studies estimated the permeability of carbonate reservoirs based on well logs using artificially intelligent techniques. Nevertheless, to estimate the permeability of a carbonate reservoir with intergranular and vuggy porosity, an evaluation method that includes pore size distribution information is required. In this study, the permeability of a carbonate reservoir with intergranular and vuggy porosity was enhanced by integrating standard resolution log data with pore size distribution-sensitive log data and augmented with carbonate pore size distribution information from borehole resistivity images. Porosity partitioning and permeability analysis results were validated by comparing the calculated permeability with permeability data from a modular formation dynamics tester (MDT) permeability. The results showed a good correlation between carbonate permeability and MDT permeability. The integration of the NMR-based porosity partitioning method into standard petrophysical workflow has improved the permeability estimation in Well B. Neutron and density cross plot over the water zone identifies calcite and dolomite as the two main minerals. Pickett plot over the water zone provided the value for formation water resistivity as 0.097 at 102 °C and salinity of 22,000 ppm. Hence, the enhanced workflow provided a better permeability estimation for Astaka carbonate compared to the classical approach, which assumes porosity proportional to permeability. Therefore, it can be concluded that the improved carbonate evaluation workflow can provide a more reliable and accurate permeability estimate without using core data.