Yudi Wang , Yungui Xu , Libing Du , Xuri Huang , Haifa AlSalmi , Jiali Liang
{"title":"以断裂发生和空间位置为约束的新型高效 DFN 建模方法","authors":"Yudi Wang , Yungui Xu , Libing Du , Xuri Huang , Haifa AlSalmi , Jiali Liang","doi":"10.1016/j.cageo.2024.105729","DOIUrl":null,"url":null,"abstract":"<div><p>Fractures or faults in the subsurface exert a significant impact on fluid flow and engineering activities in that environment. Fracture modelling is one of the crucial techniques, providing essential insights into the mechanisms underlying these impacts. As a useful tool, the Discrete Fracture Network (DFN) method is often utilized to simulate fracture networks and to integrate fracture statistics into 3D numerical models. However, the current DFN modeling technology suffers from low operational efficiency, particularly when handling a substantial quantity of fractures in 3D models. This paper proposes two ways to improve the efficiency and accuracy of modelling fractures: the matrix-based random sampling method (for faster generation of fracture loactions) and the quaternion method (for more accurate description of fractures). These proposed approaches simplify the management of large number of fractures within 3D models. The paper provides a comprehensive description of the proposed methods, accompanied by pseudo-code for the algorithms. The effectiveness of the proposed approach is validated through a practical case study, demonstrating superior computational efficiency and enhanced applicability for large-scale fracture modeling.</p></div>","PeriodicalId":55221,"journal":{"name":"Computers & Geosciences","volume":null,"pages":null},"PeriodicalIF":4.2000,"publicationDate":"2024-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A new efficient approach of DFN modelling constrained with fracture occurrence and spatial location\",\"authors\":\"Yudi Wang , Yungui Xu , Libing Du , Xuri Huang , Haifa AlSalmi , Jiali Liang\",\"doi\":\"10.1016/j.cageo.2024.105729\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Fractures or faults in the subsurface exert a significant impact on fluid flow and engineering activities in that environment. Fracture modelling is one of the crucial techniques, providing essential insights into the mechanisms underlying these impacts. As a useful tool, the Discrete Fracture Network (DFN) method is often utilized to simulate fracture networks and to integrate fracture statistics into 3D numerical models. However, the current DFN modeling technology suffers from low operational efficiency, particularly when handling a substantial quantity of fractures in 3D models. This paper proposes two ways to improve the efficiency and accuracy of modelling fractures: the matrix-based random sampling method (for faster generation of fracture loactions) and the quaternion method (for more accurate description of fractures). These proposed approaches simplify the management of large number of fractures within 3D models. The paper provides a comprehensive description of the proposed methods, accompanied by pseudo-code for the algorithms. The effectiveness of the proposed approach is validated through a practical case study, demonstrating superior computational efficiency and enhanced applicability for large-scale fracture modeling.</p></div>\",\"PeriodicalId\":55221,\"journal\":{\"name\":\"Computers & Geosciences\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":4.2000,\"publicationDate\":\"2024-09-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Computers & Geosciences\",\"FirstCategoryId\":\"89\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0098300424002127\",\"RegionNum\":2,\"RegionCategory\":\"地球科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Computers & Geosciences","FirstCategoryId":"89","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0098300424002127","RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
A new efficient approach of DFN modelling constrained with fracture occurrence and spatial location
Fractures or faults in the subsurface exert a significant impact on fluid flow and engineering activities in that environment. Fracture modelling is one of the crucial techniques, providing essential insights into the mechanisms underlying these impacts. As a useful tool, the Discrete Fracture Network (DFN) method is often utilized to simulate fracture networks and to integrate fracture statistics into 3D numerical models. However, the current DFN modeling technology suffers from low operational efficiency, particularly when handling a substantial quantity of fractures in 3D models. This paper proposes two ways to improve the efficiency and accuracy of modelling fractures: the matrix-based random sampling method (for faster generation of fracture loactions) and the quaternion method (for more accurate description of fractures). These proposed approaches simplify the management of large number of fractures within 3D models. The paper provides a comprehensive description of the proposed methods, accompanied by pseudo-code for the algorithms. The effectiveness of the proposed approach is validated through a practical case study, demonstrating superior computational efficiency and enhanced applicability for large-scale fracture modeling.
期刊介绍:
Computers & Geosciences publishes high impact, original research at the interface between Computer Sciences and Geosciences. Publications should apply modern computer science paradigms, whether computational or informatics-based, to address problems in the geosciences.