Rock typing presents a longstanding challenge in heterogeneous sandstone reservoirs, where geological complexity often obscures the accurate prediction of reservoir behavior. This study aims to advance rock typing methodologies by investigating the relationship between microscopic geological characteristics and pore system architecture. The objective is to enhance rock typing for heterogeneous sandstones and introduce a novel type curve that integrates both geological and engineering perspectives. The research is based on extensive data collected from twenty-one sandstone reservoirs across eight basins. A total of 1,342 core plugs were analyzed, including 289 samples subjected to special core analysis (SCAL), and 660 samples that underwent integrated petrographic thin section analysis, scanning electron microscopy (SEM), and X-ray diffraction (XRD). The well-established Kozeny's equation was employed to link permeability and porosity, focusing on pore geometry and structure. By plotting pore geometry against pore structure on a log-log scale, a pore geometry structure (PGS) cross-plot was constructed to facilitate the identification of relationships across different rock types. Results demonstrate that within each sandstone dataset, data points consistently group into three to thirteen distinct clusters, each displaying unique microscopic geological features, including variations in grain size, sorting, and cementation. Each cluster’s fitting line shows a high correlation coefficient, highlighting the systematic nature of the relationships within the dataset. Additionally, a key finding is that all fitting lines converge at a single point when extended, corroborated through mathematical validation. This convergence enabled the development of a new type curve for heterogeneous sandstones. To ensure robustness, the proposed type curve was tested against two independent sandstone datasets, both of which validated the model's applicability across different reservoir settings. Moreover, the study compares the accuracy of rock groupings from SCAL data using this methodology with the hydraulic flow unit (HFU) approach, showing that this new method outperforms HFU in terms of accuracy and consistency of the capillary pressure distribution. This research stands apart from previous studies by recognizing both geological and engineering factors that shape pore architectures. It highlights how depositional environments and diagenetic processes contribute to distinct pore structures, as captured in the PGS plot. The resulting type curve provides a practical and efficient tool for rock typing, offering new insights into how diagenetic processes influence reservoir properties and contributing to improved reservoir characterization and prediction. This research integrates depositional environments and diagenetic processes with engineering principles to explain the development of distinct pore architectures on the PGS plot. The proposed type curve offers a simplified yet effective tool for rock typing, enhancing the understanding of how diagenetic processes influence rock properties.
Musu et al. (Sat,) studied this question.