Advances in CO₂ Geological Storage and Utilization

Dear Colleagues,

Rapid urbanization and industrialization continue to drive global fossil fuel consumption, leading to substantial CO₂ emissions. The accumulation of excess CO₂ in the atmosphere exacerbates the greenhouse effect, contributing to adverse changes in the global climate and ecological systems. Carbon capture, utilization, and storage (CCUS) has emerged as a critical technology capable of significantly reducing CO₂ emissions from industrial sources. CO₂ geological storage and utilization represents a key direction in CCUS, offering both large-scale storage potential and economic advantages through enhanced oil and gas recovery.

The field of CO₂ geological storage and utilization involves multidisciplinary research on porous media, where complex physicochemical interactions occur between multiphase fluids and subsurface porous structures. Despite the progress in this field, numerous theoretical and technical challenges remain unresolved, and there is a pressing need for multi-scale studies to glean new insights and accelerate the commercial deployment of technologies related to CO₂ geological storage and utilization.

We invite authors to contribute original research or review articles to this Special Issue, titled “Advances in CO₂ Geological Storage and Utilization”. Relevant topics include, but are not limited to, CO₂ storage or utilization in shale oil/gas reservoirs, coalbed methane formations, conventional and depleted hydrocarbon reservoirs, natural gas hydrate systems, saline aquifers, and geothermal systems. Suitable themes include CO₂ injection techniques (e.g., flooding, huff-n-puff, cyclic gas injection); physical and chemical interactions between CO₂, rocks, and fluids; adsorption/desorption; diffusion; flow and phase behavior; mechanisms of CO₂-enhanced hydrocarbon recovery; and CO₂ leakage monitoring and assessment. Submissions can include laboratory experiments; theoretical models; multi-scale simulations (molecular simulation, lattice Boltzmann simulation, pore-network simulation, reservoir simulation, etc.); field tests; and applications of artificial intelligence, machine learning, and data science.

Prof. Dr. Liang Huang
Dr. Xiaojun Wu
Dr. Wentong Zhang
Dr. Tao Zhang
Guest Editors

Manuscript Submission Information

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