Shale gas adsorption modeling is essential for accurate gas-in-place estimation and efficient reservoir development. The selection of appropriate gas adsorption models and accurate characterization remains a challenge due to complexity of shale formations and limitations of traditional techniques. While recent advancements in gas adsorption models have predicted the accurate gas-in-place, improved the understanding of shale behavior and helped in making decisions in carbon dioxide sequestration, and enhanced gas recovery. Hence, this review critically examines classical and modified gas adsorption models including Langmuir variants, Brunauer-Emmett-Teller, and Density functional theory based, thermodynamic, multicomponent and supercritical gas frameworks, aimed at capturing the complexity of pore structure and surface heterogeneity in shale formations. The integration of machine learning techniques and molecular simulations is highlighted as a powerful strategy for enhancing predictive capabilities and capturing nanoscale mechanisms. The role of experimental validation, through isothermal adsorption, high-pressure/high-temperature studies, and pore-scale imaging techniques is emphasized as fundamental, though often limited by data inconsistency and lack of standardization. Key challenges, including pore heterogeneity, water effects, and multi-scale data integration, are critically examined. Future directions are proposed to guide the development of robust, hybrid modeling frameworks that combine data-driven, physics-based, and molecular-scale approaches. From this study, it has been revealed that the next generation of shale gas adsorption models (multiscale and hybrid models) has been better equipped to support, accurate, and sustainable exploitation of unconventional resources due to closer integration between theory, computation and experiment. These integrated frameworks will be essential for accurately predicting shale gas behavior under realistic reservoir conditions and advancing the design of optimized recovery and storage strategies. • Shale gas adsorption modeling techniques are comprehensively reviewed. • Key factors influencing gas adsorption behavior are discussed. • Importance of experimental data across three critical domains is emphasized. • Major challenges in shale gas adsorption modeling techniques, including pore structure and moisture effects, are highlighted. • Future research directions for developing next-generation shale gas adsorption models are proposed.
Memon et al. (Fri,) studied this question.