Estimation of pore-type distribution utilizing petrophysical data and rock physics modeling on an Iranian carbonate reservoir

Abstract

Pore types in carbonate reservoirs are more complex than their sandstone counterparts due to the wide spectrum of their depositional environments and their more complicated post-depositional processes. This means that a good knowledge of pore types is vital in determining carbonate formation’s elastic and reservoir properties. This study aims to develop a multi-physics approach to determine pore-type variations in a carbonate reservoir using well log information from one of the oilfields of the Abadan Plain in southwest Iran. Firstly, we determined lithology, porosity, and fluid content by interpreting conventional well logs (gamma ray, resistivity, density, neutron, photoelectric, and P-wave sonic). Then, nuclear magnetic resonance data were used to determine different pore types within the Main Ilam and Sarvak formations. We distinguished between clay, micro, meso, and macro pore types. We confirmed our interpretation results using thin sections, scanning electron microscopy photographs, and pore-size distribution on the available core plugs. Finally, a carbonate rock physics model was employed to model sonic velocities using petrophysical interpretation along with pore-type determination results. A good match between modeled and measured sonic velocities confirmed that using nuclear magnetic resonance data for pore-type determination can reasonably estimate pore-type variations needed for rock physics modeling. The standard industry procedure for carbonate rock physics modeling uses sonic logs, core data, or thin sections to determine pore types. We offer a substitute approach with reasonable accuracy for pore-type modeling needed for carbonate rock physics modeling. We modeled pore types independently from sonic velocity and used them to predict P-wave velocity with a correlation coefficient of 92 and 64 percent accuracy in the Main Ilam and Sarvak formations. Graphical abstract