Integrated Digital Rock Physics and Multi-Scale Rock-Physics Modeling for Reservoir and Pore Structure Characterization

Accurate characterization of pore structure and reservoir properties is central to hydrocarbon exploration, geothermal energy assessment, CO2 storage, and groundwater management. Traditional laboratory measurements, while essential, are often limited by sample availability, cost, and the difficulty of capturing heterogeneity across scales. Digital rock physics (DRP) — combining high-resolution imaging (micro-CT, SEM, FIB-SEM) with numerical simulation — has emerged as a powerful complement, enabling non-destructive, repeatable analysis of pore geometry, mineral distribution, and transport properties directly from 3D digital images.Despite significant progress, key challenges remain in linking pore-scale digital measurements to core- and field-scale reservoir behavior. Discrepancies between simulated and experimental elastic, electrical, and transport properties persist due to resolution limits, segmentation uncertainty, and the multi-scale, multi-mineral complexity of natural rocks. Bridging these gaps requires integrated workflows that combine digital imaging, physics-based and data-driven modeling, and multi-scale upscaling strategies to produce reliable, field-relevant predictions.This Research Topic aims to advance the state of the art in digital and multi-scale rock physics by bringing together contributions on imaging techniques, numerical modeling, and their application to reservoir and pore structure characterization. We welcome studies addressing methodological advances as well as applications across conventional and unconventional reservoirs, carbonate and clastic systems, and emerging applications such as CO2 sequestration and geothermal reservoirs.We invite original research, reviews, and methods articles on topics including, but not limited to:• Digital rock physics workflows integrating micro-CT, SEM, and FIB-SEM imaging• Pore-scale simulation of elastic, electrical, and flow properties• Multi-scale upscaling from pore to core to field scale• Machine learning and data-driven approaches for image segmentation and property prediction• Validation of digital rock physics against laboratory and well-log measurements• Rock physics modeling for unconventional reservoirs (shale, tight sandstone, carbonate)• Applications to CO2 storage, geothermal systems, and reservoir monitoring• Uncertainty quantification in digital rock physics predictionsBy fostering dialogue between imaging scientists, computational modelers, and reservoir engineers, this Research Topic seeks to close the gap between pore-scale characterization and field-scale application, supporting more robust and predictive subsurface characterization Topic editors: Mengqiang Pang, Erik H. Saenger, Martin Balcewicz Source: https://www.frontiersin.org/research-topics/85744/integrated-digital-rock-physics-and-multi-scale-rock-physics-modeling-for-reservoir-and-pore-structure-characterization