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Multi-objective optimization for efficient CO2 storage under pressure buildup constraint in saline aquifer

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  • Liu, Jianqiao
  • Liu, Jia
  • Zhu, Yiheng
  • Sun, Wenyue
  • Zhang, Daowei
  • Pan, Huanquan

Abstract

CO2 storage within saline aquifers represents a pivotal strategy for mitigating climate change. Continuous injection of CO2 into saline aquifers can lead to a sharp increase in formation pressure, potentially reducing storage efficiency and escalating the risks of CO2 leakage and seismic activities resulting from stress-induced changes. Developing an optimal injection strategy that maximizes CO2 storage while minimizing leakage risk is critical for storage projects. Current research primarily focuses on optimization tasks that incorporate geomechanical considerations, often necessitating extensive flow-geomechanics coupled forward simulations. These simulations are computationally intensive, posing challenges in convergence and making them impractical for field-scale CO2 storage deployments.

Suggested Citation

  • Liu, Jianqiao & Liu, Jia & Zhu, Yiheng & Sun, Wenyue & Zhang, Daowei & Pan, Huanquan, 2025. "Multi-objective optimization for efficient CO2 storage under pressure buildup constraint in saline aquifer," Applied Energy, Elsevier, vol. 382(C).
  • Handle: RePEc:eee:appene:v:382:y:2025:i:c:s0306261924025595
    DOI: 10.1016/j.apenergy.2024.125175
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    References listed on IDEAS

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    1. Nathália Weber & Saulo B. de Oliveira & Allan Cavallari & Isabela Morbach & Colombo C. G. Tassinari & Julio Meneghini, 2024. "Assessing the potential for CO2 storage in saline aquifers in Brazil: Challenges and Opportunities," Greenhouse Gases: Science and Technology, Blackwell Publishing, vol. 14(2), pages 319-329, April.
    2. Cheng Cao & Hejuan Liu & Zhengmeng Hou & Faisal Mehmood & Jianxing Liao & Wentao Feng, 2020. "A Review of CO 2 Storage in View of Safety and Cost-Effectiveness," Energies, MDPI, vol. 13(3), pages 1-45, January.
    3. Wu, Hao & Lubbers, Nicholas & Viswanathan, Hari S. & Pollyea, Ryan M., 2021. "A multi-dimensional parametric study of variability in multi-phase flow dynamics during geologic CO2 sequestration accelerated with machine learning," Applied Energy, Elsevier, vol. 287(C).
    4. Kim, Youngmin & Jang, Hochang & Kim, Junggyun & Lee, Jeonghwan, 2017. "Prediction of storage efficiency on CO2 sequestration in deep saline aquifers using artificial neural network," Applied Energy, Elsevier, vol. 185(P1), pages 916-928.
    5. Paul E. Hardisty & Mayuran Sivapalan & Peter Brooks, 2011. "The Environmental and Economic Sustainability of Carbon Capture and Storage," IJERPH, MDPI, vol. 8(5), pages 1-18, May.
    6. Leung, Dennis Y.C. & Caramanna, Giorgio & Maroto-Valer, M. Mercedes, 2014. "An overview of current status of carbon dioxide capture and storage technologies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 39(C), pages 426-443.
    7. Zhuang, Xinyu & Wang, Wendong & Su, Yuliang & Li, Yuan & Dai, Zhenxue & Yuan, Bin, 2024. "Spatio-temporal sequence prediction of CO2 flooding and sequestration potential under geological and engineering uncertainties," Applied Energy, Elsevier, vol. 359(C).
    8. Vo Thanh, Hung & Yasin, Qamar & Al-Mudhafar, Watheq J. & Lee, Kang-Kun, 2022. "Knowledge-based machine learning techniques for accurate prediction of CO2 storage performance in underground saline aquifers," Applied Energy, Elsevier, vol. 314(C).
    9. Yuting Zhang & Christopher Jackson & Samuel Krevor, 2024. "The feasibility of reaching gigatonne scale CO2 storage by mid-century," Nature Communications, Nature, vol. 15(1), pages 1-13, December.
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