Dynamic geothermal resource assessment: Integrating reservoir simulation and Gaussian Kernel Density Estimation under geological uncertainties
文献类型：期刊论文
| 作者 | Tian, Xiaoming4,5,7; Kong, Yanlong6; Gong, Yulie4,5,7; Huang, Yonghui2,3; Wang, Shejiao1; Du, Guanglin1 |
| 刊名 | GEOTHERMICS
 |
| 出版日期 | 2024-06-01 |
| 卷号 | 120页码:12 |
| 关键词 | Dynamic geothermal resource assessment Gaussian kernel density estimation Geological uncertainties Reservoir simulation |
| ISSN号 | 0375-6505 |
| DOI | 10.1016/j.geothermics.2024.103017 |
| 通讯作者 | Kong, Yanlong(ylkong@mail.iggcas.ac.cn) ; Gong, Yulie(gongyl@ms.giec.ac.cn) |
| 英文摘要 | This paper presents a dynamic geothermal resource assessment method that integrates reservoir simulation and Gaussian kernel density estimation (KDE). This approach addresses geological uncertainties by employing reservoir simulation techniques to model the fluid and heat flow under the condition of permeability heterogeneity. Incorporating probabilistic resource assessment through Gaussian KDE, the study quantifies uncertainties, estimating the probability density function (PDF) of ensemble results under conditions like thermal breakthrough thresholds, fixed reservoir lifespans, and target energy production. The demonstrations of assessment start with a simple homogeneous model. The results show that larger doublet well distances result in extended lifespan, higher final production well temperatures, and increased energy production. Brugge reservoir emphasizes the impact of heterogeneity and uncertainty on production outcomes, especially at smaller doublet well distances. Assessment of fluvial Egg model reveals that drilling in fluvial channels causes rapid thermal breakthrough. This result indicates that, to optimize reservoir performance, it is recommended to refrain from drilling doublet wells within high -permeability fluvial channels. Furthermore, it is worthy of mention that the Gaussian kernel is not always favored for KDE, particularly in scenarios involving nonGaussian distribution ensembles. The proposed method, which integrates reservoir simulation and Gaussian KDE, enhances understanding of geological uncertainties and the intricate nature of geothermal reservoirs, facilitating more reliable and accurate resource assessments. |
| WOS关键词 | OPERATOR-BASED LINEARIZATION ; FLOW |
| 资助项目 | Third Xinjiang Scientific Expedition Program[2022xjkk1304] ; National Natural Science Foundation of China[52192623] ; Youth Innovation Promotion Association of CAS[2020067] |
| WOS研究方向 | Energy & Fuels ; Geology |
| 语种 | 英语 |
| WOS记录号 | WOS:001228777400001 |
| 出版者 | PERGAMON-ELSEVIER SCIENCE LTD |
| 资助机构 | Third Xinjiang Scientific Expedition Program ; National Natural Science Foundation of China ; Youth Innovation Promotion Association of CAS |
| 源URL | [http://ir.giec.ac.cn/handle/344007/41849]  |
| 专题 | 中国科学院广州能源研究所 |
| 通讯作者 | Kong, Yanlong; Gong, Yulie |
| 作者单位 | 1.PetroChina Shenzhen New Energy Res Inst, Shenzhen, Peoples R China 2.China Univ Petr, State Key Lab Petr Resources & Prospecting, Beijing, Peoples R China 3.Chinese Univ Petr Beijing, Coll Geosci, Beijing, Peoples R China 4.Guangdong Prov Key Lab New & Renewable Energy Res, Guangzhou, Peoples R China 5.CAS Key Lab Renewable Energy, Guangzhou, Peoples R China 6.Chinese Acad Sci, Inst Geol & Geophys, Beijing, Peoples R China 7.Chinese Acad Sci, Guangzhou Inst Energy Convers, Guangzhou, Peoples R China |
| 推荐引用方式 GB/T 7714 | Tian, Xiaoming,Kong, Yanlong,Gong, Yulie,et al. Dynamic geothermal resource assessment: Integrating reservoir simulation and Gaussian Kernel Density Estimation under geological uncertainties[J]. GEOTHERMICS,2024,120:12. |
| APA | Tian, Xiaoming,Kong, Yanlong,Gong, Yulie,Huang, Yonghui,Wang, Shejiao,&Du, Guanglin.(2024).Dynamic geothermal resource assessment: Integrating reservoir simulation and Gaussian Kernel Density Estimation under geological uncertainties.GEOTHERMICS,120,12. |
| MLA | Tian, Xiaoming,et al."Dynamic geothermal resource assessment: Integrating reservoir simulation and Gaussian Kernel Density Estimation under geological uncertainties".GEOTHERMICS 120(2024):12. |
入库方式： OAI收割
来源：广州能源研究所
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