Quantitative  Analysis Method of spatial Distribution of Faults and Correlation Analysis of Water Inrush based on improved fractal Dimension and 3-D geological Model: A Case Study in Dafosi Coal Mine

Quantitative Analysis Method of spatial Distribution of Faults and Correlation Analysis of Water Inrush based on improved fractal Dimension and 3-D geological Model: A Case Study in Dafosi Coal Mine | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Quantitative Analysis Method of spatial Distribution of Faults and Correlation Analysis of Water Inrush based on improved fractal Dimension and 3-D geological Model: A Case Study in Dafosi Coal Mine Junsheng Yan, Zaibin Liu, Qian Xie, Chenguang Liu, Xuefei Wu, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4647862/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 10 Mar, 2025 Read the published version in Mine Water and the Environment → Version 1 posted 4 You are reading this latest preprint version Abstract Fault is one of the most threatening factors among the hidden disaster-causing factors in coal mines. The current quantitative analysis method of fault is still unsatisfactory, which is mainly reflected in the fact that the quantitative results cannot reflect the morphological characteristics of fault and lack of three-dimensional(3-D) quantitative methods. In this paper, we propose a method for quantitative analysis of spatial distribution faults based on improved fractal dimension and 3-D geological model. The method utilizes the Delaunay algorithm to improve the fractal dimension calculation parameters. On the other hand, the 3-D geological model is used to calculate the curvature of the fault plane, and the mean curvature of the fault plane is used to correct the number of parameters in the calculation of 3-D fractal dimension. The calculated indices can reflect the spatial distribution characteristics of the faults in the study area as well as their own structural characteristics. Finally, we calculated the correlation coefficients between the calculated results and the distribution of water inrush points by linear regression analysis. The regression coefficient \({\text{R}}^{2}\) obtained are above 0.7, which proves that the spatial distribution faults proposed in this paper has a strong correlation with the water inrush conditions in mines, and further verifies the validity of the method proposed in this paper. fault plane morphological characteristics curvature analysis Delaunay algorithm linear regression Full Text Cite Share Download PDF Status: Published Journal Publication published 10 Mar, 2025 Read the published version in Mine Water and the Environment → Version 1 posted Reviewers agreed at journal 07 Jul, 2024 Reviewers invited by journal 07 Jul, 2024 Editor assigned by journal 01 Jul, 2024 First submitted to journal 29 Jun, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4647862","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":323629068,"identity":"20bb0e18-a9c8-440d-8026-5b0cc045e4e1","order_by":0,"name":"Junsheng Yan","email":"","orcid":"","institution":"China Coal Technology and Engineering Group Corp China Coal Research Institute","correspondingAuthor":false,"prefix":"","firstName":"Junsheng","middleName":"","lastName":"Yan","suffix":""},{"id":323629069,"identity":"c9988f30-2949-4509-937b-39b8d630cfab","order_by":1,"name":"Zaibin 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The current quantitative analysis method of fault is still unsatisfactory, which is mainly reflected in the fact that the quantitative results cannot reflect the morphological characteristics of fault and lack of three-dimensional(3-D) quantitative methods. In this paper, we propose a method for quantitative analysis of spatial distribution faults based on improved fractal dimension and 3-D geological model. The method utilizes the Delaunay algorithm to improve the fractal dimension calculation parameters. On the other hand, the 3-D geological model is used to calculate the curvature of the fault plane, and the mean curvature of the fault plane is used to correct the number of parameters in the calculation of 3-D fractal dimension. The calculated indices can reflect the spatial distribution characteristics of the faults in the study area as well as their own structural characteristics. 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