Review of the adsorption equilibria of CO₂, CH₄, and their mixture on coals and shales at high pressures for enhanced CH₄ recovery and CO₂ sequestration

Producing CH₄ from coal beds and shale reservoirs is an attractive unconventional energy option. Injecting CO₂ into a coal or shale basin can extract more CH₄ and enable the permanent sequestration of CO₂, and this is called CO₂-enhanced coal bed methane (CO₂-ECBM) or CO₂-enhanced shale gas recovery (CO₂-ESGR), respectively. Since the injection of captured CO₂ into geological formations (geological CO₂ sequestration, GCS) is considered a feasible strategy for CO₂ sequestration, CO₂-ECBM and CO₂-ESGR have received great attention for the mitigation of global warming as well as energy recovery. Coals and shales, which are porous solids mainly containing carbons with silica-based materials, can adsorb a large amount of CO₂ and CH₄ depending on their pore structures/geochemical properties. Therefore, to design and practice CO₂-ECBM and CO₂-ESGR, it is important to understand the adsorption of CO₂ and CH₄ on coals and shales. A large number of laboratory experiments have been conducted to estimate the adsorption capacity of CO₂ and CH₄ with the structural characterization of coals and shales. However, the heterogeneous properties of coals and shales make it difficult to develop a prediction model for various types of coals and shales. This study reviews the present state of the adsorption of CO₂, CH₄, and their mixture on coals and shales and suggests a future research direction. The experimental results of adsorption on coals and shales from the literature are introduced, and the properties of coals and shales are discussed to understand their influence on adsorption. Then, thermodynamic models of the adsorption are analyzed to elucidate the correlation between the thermodynamic parameters and structural properties of coals and shales. Applications of machine learning (ML) models, which have received significant attention recently, to the prediction of CO₂/CH₄ adsorption on coals and shales are also reviewed. Finally, the combination of the thermodynamic model and the ML model, known as a hybrid model, is discussed to develop a universal prediction model for CO₂/CH₄ adsorption on various types of coals and shales.