Enhancement of permeability estimation by high order polynomial regression for capillary pressure curve correlation with water saturation

Abstract

Suggesting a cost-effective and straightforward approach is indispensable for obtaining permeability estimates in carbonate reservoirs utilizing available well logs. In this study, several procedures were conducted to reach an optimum approach, primarily by constructing a correlation between capillary pressure and water saturation using core data plotted and utilized a good polynomial regression to obtain a better relationship, which leads to calculating the permeability. The second step is to use different theoretical models which Tixier introduces, Timur, Coats, and Dumanior, which resulted not good matching with the permeability from core analysis and modified Brown and Husseini correlation which used and gave better matching than others correlations by comparing the results with the calculated permeability depending on core data. The proposed approach in this study based on modified Husseini equation using the well logs data by applying Statistical regression techniques within capillary pressure prediction to enhance reservoir characterization can potentially advantage reservoir simulation efforts. Obtained results of permeability prediction based on capillary pressure correlation was examined for a certain well and compared with the measured permeability value of cores. There was a good matching between the predicted and measured permeability.