Integration of Well Logging and Seismic Data for the Prognosis of Reservoir Properties of Carbonates

Abstract

Due to the complex nature of the pore system and the diversity of pore types, carbonate rocks pose a challenge in terms of their spatial characterization. Unlike sandstones, permeability in carbonates is often not correlated conclusively with porosity. A methodology for preliminary qualitative spatial characterization of reservoirs in carbonate rocks is presented in this article, with a focus on interparametric relationships. It endeavors to apply this methodology to a reservoir situated within the Main Dolomite formation in the Polish Lowlands. Fundamental analyses rely on data plotted within rock physics templates (RPT), specifically, cross-plots of acoustic impedance as a function of the product of compressional and shear wave velocities in well log profiles. The analysis of interparametric relationships was conducted on well log profiles and subsequently integrated with seismic data using neural network techniques. Areas with the greatest potential for hydrocarbon accumulation and areas potentially exhibiting enhanced reservoir properties were identified based on the outcomes of the well log profile analysis and parametric models. The qualitative assessment of the reservoir, rooted in interparametric dependencies encompassing lithofacies characteristics and elastic and petrophysical parameters, together with reservoir fluid saturation, forms the basis for further, more detailed reservoir analysis, potentially focusing on fracture modeling.