LSTM-based proxy model combined with wellbore-reservoir coupling simulations for predicting multi-dimensional state parameters in depleted gas reservoirs
文献类型：期刊论文
| 作者 | Zhang, Jinyong5,6; Hong, Yi6; Wang, Lizhong6; Li, Xiaochun4 ; Lei, Hongwu4; Li, Fangfang3; Gao, Bo2; Zheng, Jia-nan1
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| 刊名 | COMPUTERS & GEOSCIENCES
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| 出版日期 | 2025-02-01 |
| 卷号 | 196页码:15 |
| 关键词 | CO 2 sequestration Wellbore-reservoir coupling Pressure buildup Depleted gas reservoirs LSTM Prediction |
| ISSN号 | 0098-3004 |
| DOI | 10.1016/j.cageo.2024.105824 |
| 英文摘要 | Although most CO2 geologic storage projects focus on deep saline aquifers, depleted gas reservoirs are a more economical option as a potential site. However, due to the extremely low initial pressure, the injection of highpressure supercritical CO2 into the reservoir can result in dramatic changes in CO2 properties, which may affect the well head pressure and bottom hole pressure. Aside from the injection rate, the injection of supercritical CO2 at different temperature and pressure has varying degrees of impact on reservoir pressure. In order to design the optimal injection condition, a deep learning proxy model, combining wellbore-reservoir coupling numerous simulations, is proposed to quickly interrogate status response of wellbores and reservoirs. Based on 567 simulation cases of supercritical CO2 injection into a deep depleted gas reservoir, the model uses the T2Well/ ECO2N software to capture the time evolution of the pressure, temperature, and rate fields of wellbore and reservoirs, and is trained to get the optimal LSTM-based proxy network. Compared with simulation results, the proxy model predicts in less than 0.1s while ensuring an overall coefficient of determination (R2) of up to 99.9%. The maximum prediction errors of pressure, temperature, and rates at all times are also not more than 0.04, 0.02, and 0.08 for a single case, respectively. The assessment findings of the ultimate reservoir pressure based on the model show that injecting supercritical CO2 under low initial pressure and high temperature is beneficial to the long-term safety of CO2 sequestration engineering in depleted gas reservoirs. |
| 资助项目 | National Natural Science Foundation of China[52122906] ; National Natural Science Foundation of China[52238001] ; National Natural Science Foundation of China[52306205] ; National Natural Science Foundation of China[DH-2022ZY0008] |
| WOS研究方向 | Computer Science ; Geology |
| 语种 | 英语 |
| WOS记录号 | WOS:001403447300001 |
| 出版者 | PERGAMON-ELSEVIER SCIENCE LTD |
| 源URL | [http://119.78.100.198/handle/2S6PX9GI/37405]  |
| 专题 | 中科院武汉岩土力学所 |
| 通讯作者 | Hong, Yi |
| 作者单位 | 1.Zhejiang Univ, Shanghai Inst Adv Study, Hangzhou 310056, Peoples R China 2.CNOOC EnerTech Clean Energy Branch, Tianjin 300452, Peoples R China 3.EnerTech CNOOC, Tianjin 300452, Peoples R China 4.Chinese Acad Sci, Inst Rock & Soil Mech, State Key Lab Geomech & Geotech Engn, Wuhan 430071, Peoples R China 5.Donghai Lab, Zhoushan 316021, Peoples R China 6.Zhejiang Univ, Coll Civil Engn & Architecture, Key Lab Offshore Geotech & Mat Zhejiang Prov, Hangzhou 310056, Peoples R China |
| 推荐引用方式 GB/T 7714 | Zhang, Jinyong,Hong, Yi,Wang, Lizhong,et al. LSTM-based proxy model combined with wellbore-reservoir coupling simulations for predicting multi-dimensional state parameters in depleted gas reservoirs[J]. COMPUTERS & GEOSCIENCES,2025,196:15. |
| APA | Zhang, Jinyong.,Hong, Yi.,Wang, Lizhong.,Li, Xiaochun.,Lei, Hongwu.,...&Zheng, Jia-nan.(2025).LSTM-based proxy model combined with wellbore-reservoir coupling simulations for predicting multi-dimensional state parameters in depleted gas reservoirs.COMPUTERS & GEOSCIENCES,196,15. |
| MLA | Zhang, Jinyong,et al."LSTM-based proxy model combined with wellbore-reservoir coupling simulations for predicting multi-dimensional state parameters in depleted gas reservoirs".COMPUTERS & GEOSCIENCES 196(2025):15. |
入库方式： OAI收割
来源：武汉岩土力学研究所
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