A new model to estimate permeability using mercury injection capillary pressure data: Application to carbonate and shale samples

Estimating permeability of carbonate rocks using mercury injection capillary pressure (MICP) data has been carried out by many researchers in the past few decades. However, a major issue with almost all of the existing models is that they focus on a single aperture value from the capillary pressure curve. This study builds a new model to extract permeability from the entire pore throat sizes. Fermic-Dirac function was applied to fit the MICP curve to obtain some critical parameters such as R-1 (the large curvature value) and R-2 (the small curvature value). Afterwards, the partial least squares regression method was employed to develop a new permeability model. To verify the new model and check other models, we studied ten carbonate rock samples from an Iranian oil reservoir. The results showed that the R-1 values vary from 1.00 to 2.73 while R-2 values are found between 0.23 and 1.00. The new model performed better than the published models. The idea of building the model for the carbonates can be used in developing the permeability estimating model for shale samples, which could be a new model for the shale permeability estimation.