Characterization and reconstruction of rough fractures based on vector statistics
文献类型：期刊论文
| 作者 | Wu, Mingyang4,5,6; Jiang, Changbao4; Deng, Bozhi4; Gao, Ke2; Li, Minghui3; Liu, Bo1 |
| 刊名 | GEOENERGY SCIENCE AND ENGINEERING
 |
| 出版日期 | 2024-03-01 |
| 卷号 | 234页码:16 |
| 关键词 | Rough fractures Quantitative characterization Vector statistics Stochastic reconstruction Rough discrete fracture network |
| ISSN号 | 2949-8929 |
| DOI | 10.1016/j.geoen.2024.212664 |
| 英文摘要 | The characteristics of fracture networks are of great significance for unconventional geo-energy exploitation such as shale oil, shale gas and geo-thermal extraction. Natural fractures and induced fractures after reservoir stimulation control the mechanical properties and fluid flow of the reservoirs. The quantitative characterization and reconstruction of rough fractures are essential for studying the fluid flow and mechanical properties of the reservoirs with complicated fracture networks. Based on vector statistics, a vector statistical method (VSM) for quantitative characterization of rough fractures is proposed and tested using 10 standard joint profiles. Furthermore, the growth vector counting method (counting method) and growth vector probability method (probability method) for single rough fractures in two-dimensional (2D) and three-dimensional (3D) models are proposed. Afterward, a morphology comparison and quantitative evaluation of single rough fractures before and after reconstruction are conducted. When the counting and probability methods are used to reconstruct single rough fractures, the difference in the tortuosity and fractal dimensions of the original and reconstructed fractures are less than 5% and 2.5%, respectively. It implies the counting and probability methods proposed herein can reconstruct rough fractures with approximate statistical characteristics and quantitative characterization parameters. Subsequently, the counting and probability methods for single rough fractures are further developed for 2D and 3D modeling of conventional and rough discrete fracture networks. The results indicate that the growth vector counting and probability methods proposed in this study have significant potential for rough discrete fracture network modeling. In addition, the merits and limitations of the proposed algorithms in modeling discrete fracture network models are discussed. |
| 资助项目 | research of Chongqing[2021XM2004] |
| WOS研究方向 | Energy & Fuels ; Engineering |
| 语种 | 英语 |
| WOS记录号 | WOS:001178394700001 |
| 出版者 | ELSEVIER |
| 源URL | [http://119.78.100.198/handle/2S6PX9GI/40845]  |
| 专题 | 中科院武汉岩土力学所 |
| 通讯作者 | Jiang, Changbao; Deng, Bozhi |
| 作者单位 | 1.Southwest Jiaotong Univ, Fac Earth Sci & Environm Engn, Chengdu 611756, Peoples R China 2.Southern Univ Sci & Technol, Dept Earth & Space Sci, Shenzhen 518055, Peoples R China 3.Shenzhen Univ, Inst Deep Earth Sci & Green Energy, Guangdong Prov Key Lab Deep Earth Sci & Geothermal, Shenzhen 518060, Peoples R China 4.Chongqing Univ, Sch Resources & Safety Engn, State Key Lab Coal Mine Disaster Dynam & Control, Chongqing 400030, Peoples R China 5.Chinese Acad Sci, Wuhan Inst Rock & Soil Mech, State Key Lab Geomech & Geotech Engn, Wuhan 430071, Peoples R China 6.Chinese Acad Sci, Inst Rock & Soil Mech, Hubei Key Lab Geoenvironm Engn, Wuhan 430071, Peoples R China |
| 推荐引用方式 GB/T 7714 | Wu, Mingyang,Jiang, Changbao,Deng, Bozhi,et al. Characterization and reconstruction of rough fractures based on vector statistics[J]. GEOENERGY SCIENCE AND ENGINEERING,2024,234:16. |
| APA | Wu, Mingyang,Jiang, Changbao,Deng, Bozhi,Gao, Ke,Li, Minghui,&Liu, Bo.(2024).Characterization and reconstruction of rough fractures based on vector statistics.GEOENERGY SCIENCE AND ENGINEERING,234,16. |
| MLA | Wu, Mingyang,et al."Characterization and reconstruction of rough fractures based on vector statistics".GEOENERGY SCIENCE AND ENGINEERING 234(2024):16. |
入库方式： OAI收割
来源：武汉岩土力学研究所
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