Machine Learning and Reinforcement Learning-Driven Optimization of Carbon Capture and Storage Processes and Their Environmental Impact Assessment

[1] Lee, S. Y., Lee, J. U., Lee, I. B., & others. (2017). Design under uncertainty of carbon capture and storage infrastructure considering cost, environmental impact, and preference on risk. Applied Energy, 189, 725-738. Lee S. Y. Lee J. U. Lee I. B. others ( 2017 ). Design under uncertainty of carbon capture and storage infrastructure considering cost, environmental impact, and preference on risk . Applied Energy , 189 , 725 - 738 . Search in Google Scholar

[2] Koornneef, J., Ramírez, A., Turkenburg, W., & others. (2012). The environmental impact and risk assessment of CO2 capture, transport and storage–An evaluation of the knowledge base. Progress in Energy and Combustion Science, 38(1),62-86. Koornneef J. Ramírez A. Turkenburg W. others ( 2012 ). The environmental impact and risk assessment of CO2 capture, transport and storage–An evaluation of the knowledge base . Progress in Energy and Combustion Science , 38 ( 1 ), 62 - 86 . Search in Google Scholar

[3] Zhang, S., Zhuang, Y., Tao, R., & others. (2020). Multi-objective optimization for the deployment of carbon capture utilization and storage supply chain considering economic and environmental performance. Journal of Cleaner Production, 270, 122481. Zhang S. Zhuang Y. Tao R. others ( 2020 ). Multi-objective optimization for the deployment of carbon capture utilization and storage supply chain considering economic and environmental performance . Journal of Cleaner Production , 270 , 122481 . Search in Google Scholar

[4] Huang, Y., Rebennack, S., & Zheng, Q. P. (2013). Techno-economic analysis and optimization models for carbon capture and storage: A survey. Energy Systems, 4(4), 315-353. Huang Y. Rebennack S. Zheng Q. P. ( 2013 ). Techno-economic analysis and optimization models for carbon capture and storage: A survey . Energy Systems , 4 ( 4 ), 315 - 353 . Search in Google Scholar

[5] Al-Sakkari, E. G., Ragab, A., Dagdougui, H., & others. (2024). Carbon capture, utilization and sequestration systems design and operation optimization: Assessment and perspectives of artificial intelligence opportunities. Science of The Total Environment, 170085. Al-Sakkari E. G. Ragab A. Dagdougui H. others ( 2024 ). Carbon capture, utilization and sequestration systems design and operation optimization: Assessment and perspectives of artificial intelligence opportunities . Science of The Total Environment , 170085 . Search in Google Scholar

[6] Zhang, S., Zhuang, Y., Liu, L., & others. (2019). Risk management optimization framework for the optimal deployment of carbon capture and storage system under uncertainty. Renewable and Sustainable Energy Reviews, 113, 109280. Zhang S. Zhuang Y. Liu L. others ( 2019 ). Risk management optimization framework for the optimal deployment of carbon capture and storage system under uncertainty . Renewable and Sustainable Energy Reviews , 113 , 109280 . Search in Google Scholar

[7] Romero-García, A. G., Ramírez-Corona, N., Sánchez-Ramírez, E., & others. (2022). Sustainability assessment in the CO2 capture process: Multi-objective optimization. Chemical Engineering and Processing-Process Intensification, 182,109207. Romero-García A. G. Ramírez-Corona N. Sánchez-Ramírez E. others ( 2022 ). Sustainability assessment in the CO2 capture process: Multi-objective optimization . Chemical Engineering and Processing-Process Intensification , 182 , 109207 . Search in Google Scholar

[8] Lee, S. Y., Lee, I. B., & Han, J. (2019). Design under uncertainty of carbon capture, utilization and storage infrastructure considering profit, environmental impact, and risk preference. Applied Energy, 238, 34-44. Lee S. Y. Lee I. B. Han J. ( 2019 ). Design under uncertainty of carbon capture, utilization and storage infrastructure considering profit, environmental impact, and risk preference . Applied Energy , 238 , 34 - 44 . Search in Google Scholar

[9] Kaelbling, L. P., Littman, M. L., & Moore, A. W. (1996). Reinforcement learning: A survey. Journal of Artificial Intelligence Research, 4, 237-285. Kaelbling L. P. Littman M. L. Moore A. W. ( 1996 ). Reinforcement learning: A survey . Journal of Artificial Intelligence Research , 4 , 237 - 285 . Search in Google Scholar

[10] Wiering, M. A., & Van Otterlo, M. (2012). Reinforcement learning. Adaptation, Learning, and Optimization, 12(3),729. Wiering M. A. Van Otterlo M. ( 2012 ). Reinforcement learning . Adaptation, Learning, and Optimization , 12 ( 3 ), 729 . Search in Google Scholar

[11] Yao, P., Yu, Z., Zhang, Y., & others. (2023). Application of machine learning in carbon capture and storage: An in-depth insight from the perspective of geoscience. Fuel, 333, 126296. Yao P. Yu Z. Zhang Y. others ( 2023 ). Application of machine learning in carbon capture and storage: An in-depth insight from the perspective of geoscience . Fuel , 333 , 126296 . Search in Google Scholar

[12] Menad, N. A., Hemmati-Sarapardeh, A., Varamesh, A., & others. (2019). Predicting solubility of CO2 in brine by advanced machine learning systems: Application to carbon capture and sequestration. Journal of CO2 Utilization, 33, 83-95. Menad N. A. Hemmati-Sarapardeh A. Varamesh A. others ( 2019 ). Predicting solubility of CO2 in brine by advanced machine learning systems: Application to carbon capture and sequestration . Journal of CO2 Utilization , 33 , 83 - 95 . Search in Google Scholar

[13] Kotov, E. V., Sravanthi, J., Logabiraman, G., & others. (2024). Carbon capture and storage optimization with machine learning using an ANN model. In E3S Web of Conferences, 588, 01003. Kotov E. V. Sravanthi J. Logabiraman G. others ( 2024 ). Carbon capture and storage optimization with machine learning using an ANN model . In E3S Web of Conferences , 588 , 01003 . Search in Google Scholar

[14] Yan, Y., Borhani, T. N., Subraveti, S. G., & others. (2021). Harnessing the power of machine learning for carbon capture, utilization, and storage (CCUS)–a state-of-the-art review. Energy & Environmental Science, 14(12), 6122-6157. Yan Y. Borhani T. N. Subraveti S. G. others ( 2021 ). Harnessing the power of machine learning for carbon capture, utilization, and storage (CCUS)–a state-of-the-art review . Energy & Environmental Science , 14 ( 12 ), 6122 - 6157 . Search in Google Scholar

[15] Siri, D., Sandhya, T., Pandey, S., & others. (2024). Carbon capture and storage optimization with machine learning. In E3S Web of Conferences, 581, 01003. Siri D. Sandhya T. Pandey S. others ( 2024 ). Carbon capture and storage optimization with machine learning . In E3S Web of Conferences , 581 , 01003 . Search in Google Scholar

[16] Gupta, S., & Li, L. (2022). The potential of machine learning for enhancing CO2 sequestration, storage, transportation, and utilization-based processes: A brief perspective. JOM, 74(2), 414-428. Gupta S. Li L. ( 2022 ). The potential of machine learning for enhancing CO2 sequestration, storage, transportation, and utilization-based processes: A brief perspective . JOM , 74 ( 2 ), 414 - 428 . Search in Google Scholar

[17] Sun, A. Y. (2020). Optimal carbon storage reservoir management through deep reinforcement learning. Applied Energy, 278, 115660. Sun A. Y. ( 2020 ). Optimal carbon storage reservoir management through deep reinforcement learning . Applied Energy , 278 , 115660 . Search in Google Scholar

[18] Al-Sakkari, E. G., Ragab, A., Alic, M., & others. (2024). Learn-to-design: Reinforcement learning-assisted chemical process optimization. Systems and Control Transactions, 3, 245-252. Al-Sakkari E. G. Ragab A. Alic M. others ( 2024 ). Learn-to-design: Reinforcement learning-assisted chemical process optimization . Systems and Control Transactions , 3 , 245 - 252 . Search in Google Scholar

[19] Alanazi, A., Ibrahim, A. F., Bawazer, S., & others. (2023). Machine learning framework for estimating CO2 adsorption on coalbed for carbon capture, utilization, and storage applications. International Journal of Coal Geology, 275, 104297. Alanazi A. Ibrahim A. F. Bawazer S. others ( 2023 ). Machine learning framework for estimating CO2 adsorption on coalbed for carbon capture, utilization, and storage applications . International Journal of Coal Geology , 275 , 104297 . Search in Google Scholar

[20] Priya, A. K., Devarajan, B., Alagumalai, A., & others. (2023). Artificial intelligence enabled carbon capture: A review. Science of The Total Environment, 886, 163913. Priya A. K. Devarajan B. Alagumalai A. others ( 2023 ). Artificial intelligence enabled carbon capture: A review . Science of The Total Environment , 886 , 163913 . Search in Google Scholar