IMPROVEMENT OF PERMEABILITY MODELS USING LARGE MERCURY INJECTION CAPILLARY PRESSURE DATASET FOR MIDDLE EAST CARBONATE RESERVOIRS

摘要

In this study, eight permeability models are calibrated to a large mercury injection capillary pressure dataset obtained from the Middle East region. The permeability models are: Purcell, Thomeer, Winland, Swanson, Pittman, Huet, Dastidar, in addition to the Buiting-Clerke permeability models. The coefficients of the models have been determined using three different regression techniques: ordinary nonlinear least-squares regression, weighted nonlinear regression, and multiple regressions of nonlinear models after linearization. Using the original and adjusted coefficients, permeability values were estimated and compared to the actual data. Comprehensive statistical and graphical comparison is made between the different regression techniques. The study indicates that, in general, permeability models with published constants produce high errors. Major improvements in results, however, have been accomplished when using the generalized permeability models with their calibrated coefficients. The modified Winland and Swanson models show the best prediction performance. In addition, the modified Purcell model shows a significant improvement with the updated parameters. This study enhances the estimation of absolute permeability and hence better reservoir description.