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Selecting Geological Formations for CO 2 Storage: A Comparative Rating System

Author

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  • Muhammad Hammad Rasool

    (Petroleum Geosciences Department, Universiti Teknologi Petronas, Seri Iskandar 32610, Malaysia)

  • Maqsood Ahmad

    (Petroleum Geosciences Department, Universiti Teknologi Petronas, Seri Iskandar 32610, Malaysia)

  • Muhammad Ayoub

    (Chemical Engineering Department, Universiti Teknologi Petronas, Seri Iskandar 32610, Malaysia)

Abstract

Underground storage of carbon dioxide (CO 2 ) in geological formations plays a vital role in carbon capture and storage (CCS) technology. It involves capturing CO 2 emissions from industrial processes and power generation and storing them underground, thereby reducing greenhouse gas emissions and curbing the impact of climate change. This review paper features a comparative analysis of CO 2 storage in deep saline aquifers, depleted reservoirs, coal seams, basaltic formations and clastic formations. The comparison has been drawn based upon seven factors carefully selected from the literature, i.e., safety, storage capacity, injection rates, efficiency, residual trapping, containment and integrity and potential to improve, and all of these factors have been rated from low (1) to high (5) based upon their individual traits. Based upon these factors, an overall M.H. rating system has been developed to categorize geological formations for CO 2 storage and it is observed that deep water aquifers and basaltic formations are the most effective options for CO 2 storage. Lastly, a detailed way forward has been suggested, which can help researchers and policymakers to find more viable ways to enhance the efficiency of CO 2 storage in various geological formations.

Suggested Citation

  • Muhammad Hammad Rasool & Maqsood Ahmad & Muhammad Ayoub, 2023. "Selecting Geological Formations for CO 2 Storage: A Comparative Rating System," Sustainability, MDPI, vol. 15(8), pages 1-39, April.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:8:p:6599-:d:1122714
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    References listed on IDEAS

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    1. Wang, Xin & Li, Shaohua & Tong, Baocai & Jiang, Lanlan & Lv, Pengfei & Zhang, Yi & Liu, Yu & Song, Yongchen, 2024. "Multiscale wettability characterization under CO2 geological storage conditions: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 189(PB).
    2. Sadeghpour, Farshad, 2025. "Storage efficiency prediction for feasibility assessment of underground CO2 storage: Novel machine learning approaches," Energy, Elsevier, vol. 324(C).

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