An effective approach to generate drainage representative capillary pressure and relative permeability curves in the framework of reservoir electrofacies

Abstract

Representative capillary pressure and relative permeability curves for reservoir rock types are important inputs for a dynamic reservoir simulator. The current study proposes a third-step approach to generate representative capillary pressure and relative permeability curves of reservoir rock types from nuclear magnetic resonance (NMR) log. First, reservoir electrofacies were identified by integration of conventional well logs and NMR log parameters. Employing cluster analysis reservoir rocks were classified into six electrofacies (EF) with reservoir quality being increased from EF1 to EF6. In the second step, the NMR T2-distribution arrays were converted to synthetic drainage capillary pressure curves and the results were validated by available laboratory measured mercury injection capillary pressure curves (MICP). Finally, the relative permeability curves were generated from the NMR-derived MICP data by using the Wyllie and Gardner equations for each individual electrofacies. Comparing the results with laboratory data indicates the effective role of electrofacies control in generating high accuracy capillary pressure and relative permeability curves. The results of this study show that the application of NMR log can further be extended through the generation of drainage capillary pressure and relative permeability data in the framework of electrofacies clustering.