中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
首页 机构 成果 学者
  
  1. CAS IR Grid
  2. 武汉岩土力学研究所
  3. 中科院武汉岩土力学所
Probabilistic assessment of the thermal performance of low-enthalpy geothermal system under impact of spatially correlated heterogeneity by using XGBoost algorithms

文献类型：期刊论文

作者Liao, Jianxing2,3,4; Xie, Yachen3,4,5,6; Zhao, Pengfei5; Xia, Kaiwen1; Xu, Bin2,4; Wang, Hong2; Li, Cunbao4; Li, Cong3; Liu, Hejuan6
刊名ENERGY
出版日期2024-12-30
卷号313页码:18
关键词Thermal performance Reservoir heterogeneity XGBoost SHAP Probability of failure
ISSN号0360-5442
DOI10.1016/j.energy.2024.133947
英文摘要Low-enthalpy geothermal energy represents a widely accessible renewable resource. However, efficient heat extraction in such systems remains complex due to uncertainties associated with spatially correlated reservoir heterogeneity. This study presents a computational framework that integrates numerical simulations with datadriven modeling to analyze the impact of reservoir heterogeneity on thermal performance. Initially, 6000 simulations were conducted on heterogeneous models, yielding 5866 valid results to train and validate a surrogate XGBoost model. SHAP analysis was utilized to systematically assess the influence of reservoir heterogeneity on thermal performance. To quantify the likelihood of not meeting design specifications, a failure probability was introduced and computed based on 64,000 additional predictions from the XGBoost model. Results suggest a generally positive correlation between porosity and all thermal performance indicators. High levels of reservoir heterogeneity are likely to decrease thermal breakthrough time, thermal production lifetime, and production capacity. Feature importance analysis identified mean porosity as the most significant variable, followed by porosity at injection and production well. In highly heterogeneous reservoirs, uncertainties can cause intricate variations in performance metrics. In cases with limited geological data, the failure probability metric offers a practical means for rapidly evaluating thermal performance during early-stage design.
资助项目National Natural Science Foundation of China, China[42477191] ; National Natural Science Foundation of China, China[U22A20166] ; National Key Research and Development Program of China, China[2023YFF0615401] ; Fundamental Research Funds for the Central Universities, China[YJ202449] ; Open Research Fund of State Key Laboratory of Intelligent Construction and Healthy Operation and Maintenance of Deep Underground Engineering, China[SDGZK2424] ; Open Research Fund of State Key Laboratory of Geomechanics and Geotechnical Engineering, Institute of Rock and Soil Mechanics, Chinese Academy of Sciences, China[SKLGME022009]
WOS研究方向Thermodynamics ; Energy & Fuels
语种英语
WOS记录号WOS:001367052800001
出版者PERGAMON-ELSEVIER SCIENCE LTD
源URL[http://119.78.100.198/handle/2S6PX9GI/43296]  
专题中科院武汉岩土力学所
通讯作者Xie, Yachen
作者单位1.China Univ Geosci, Inst Geosafety, Sch Engn & Technol, Beijing 100083, Peoples R China
2.Guizhou Univ, Coll Civil Engn, Guiyang 550025, Peoples R China
3.Sichuan Univ, Coll Water Resources & Hydropower, Chengdu 610225, Peoples R China
4.Shenzhen Univ, State Key Lab Intelligent Construction & Hlth Oper, Minist Educ, Shenzhen 518060, Peoples R China
5.Univ Toronto, Dept Civil & Mineral Engn, Toronto, ON M5S1A4, Canada
6.Inst Rock & Soil Mech, State Key Lab Geomech & Geotech Engn, Wuhan 430071, Peoples R China
推荐引用方式
GB/T 7714		 Liao, Jianxing,Xie, Yachen,Zhao, Pengfei,et al. Probabilistic assessment of the thermal performance of low-enthalpy geothermal system under impact of spatially correlated heterogeneity by using XGBoost algorithms[J]. ENERGY,2024,313:18.
APA Liao, Jianxing.,Xie, Yachen.,Zhao, Pengfei.,Xia, Kaiwen.,Xu, Bin.,...&Liu, Hejuan.(2024).Probabilistic assessment of the thermal performance of low-enthalpy geothermal system under impact of spatially correlated heterogeneity by using XGBoost algorithms.ENERGY,313,18.
MLA Liao, Jianxing,et al."Probabilistic assessment of the thermal performance of low-enthalpy geothermal system under impact of spatially correlated heterogeneity by using XGBoost algorithms".ENERGY 313(2024):18.

入库方式： OAI收割

来源：武汉岩土力学研究所

浏览0
下载0
收藏0
其他版本

除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。