Reservoir rock typing and electrofacies characterization by integrating petrophysical properties and core data in the Bangestan reservoir of the Gachsaran oilfield, the Zagros basin, Iran

The super-giant Gachsaran oilfield is situated in the Dezful Embayment of the Zagros basin. The main goal of this study is to characterize the reservoir rock types by integrating the available geological and petrophysical studies in the Bangestan reservoir along with adopting a way to figure out the optimal number of electrofacies codes. At the first step, the types of porosity and geological microfacies were studied by using 163 thin sections from the core samples. The microscopic studies revealed that fractures and intraparticle interstices are the most common porosities types. Also, they resulted in the identification of 4 microfacies in the Bangestan reservoir. In a complementary study, the Velocity-Deviation Log (VDL) was employed to determine the dominant pore types. By comparison of the VDL values and thin section studies' results, it was deduced that high micro-porosities along with hairline fractures are the predominant pore types of the Bangestan reservoir. At the second step, the optimal number of reservoir rock types (RRT) was determined by using the concept of hydraulic flow units. Thus, six flow units were distinguished by utilizing the Flow Zone Indicator (FZI) method in which the reservoir properties were improved from RRT-1 toward RRT-6. In the third step, the data clustering analysis, known as the electrofacies analysis, was employed to identify the accurate petrophysical rock types based on the meaningful segregation of capillary pressure curves within each electrofacies code and then propagated in non-cored intervals and boreholes. In this research, an optimal number of 7 electrofacies were identified by employing the petrophysical curves including effective porosity (PHIE), bulk density (RHOB), sonic (DT), and water saturation (SWE), along with considering the number of reservoir rock types and the defined geological microfacies, as well as the relations of the available capillary pressure data within different electrofacies codes. The validity of the proposed electrofacies was scrutinized through petrophysical results including shale volume, water saturation, and effective porosity. In the end, the electrofacies codes were compared to the defined geological microfacies. Finally, this study shows that the correlation of capillary pressure data and electrofacies codes can be resulted in figuring out the optimal number of electrofacies codes. In addition, by trying to honor the link between geological microfacies, capillary pressure, and petrophysical curves, the constructed electrofacies model, as a suitable practical integrated rock typing method, can be the foundation of property modeling, guide the spatial distribution of reservoir properties in the 3D model, aids to model the dynamics of fluid flow more realistically in reservoir simulation phase, and ultimately be beneficial for further development and production decisions in the Bangestan reservoir of the Gachsaran oilfield.