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Two-year growth of Deep Underground Science and Engineering: A perspective
Pub Date : 2024-12-13 DOI: 10.1002/dug2.12139
Jianguo Wang, Chunfai Leung, Heping Xie, Xiaozhao Li, Na Yue, Qingping Hou, Jihong Wang
<p><i>Deep Underground Science and Engineering</i> (DUSE) launched its first issue in September 2022 as a quarterly journal. So far, it has published 106 articles with nine issues and online early view. The volume of received manuscripts increases by 50% each year and over 200 manuscripts were received by 28th of November 2024. In the early period, DUSE authorship came from five countries and now reaches 29 countries. DUSE articles have been downloaded over 97 000 times by readers from 170 countries/regions. It is indeed encouraging to note that DUSE has been admitted to different indices, including ESCI (August 2024), EI (March 2024), Scopus (July 2023), and DOAJ (May 2023). Its CiteScore in Scopus was 2.2 in 2023 and increased to 5.1 at the mid-November 2024. Its first impact factor from the Web of Science will be available in 2025. DUSE is growing to be a rapidly recognized international journal by readers in deep underground research and practice.</p><p>DUSE is making its best efforts to trace and shape a full-chain deep underground science and engineering through its six directions. <i>Direction 1</i>: Exploration and extraction of geo-resources. The geo-resources refer to minerals, energy sources, and water. DUSE makes efforts to streamline research studies in geo-resources from the initial geological analysis of source location, geo-resource volume estimation, and hot sweat point identification. These processes involve geology, geophysics, rock mechanics, and related material science and technology. After the identification of geo-resources, the next step is to extract these geo-resources from (deep) ground. This step involves engineering science and technology, such as rock mechanics, hydraulic fracturing technology, blasting, and so on. The key outcome is the extraction of these identified geo-sources from the deep ground with technical feasibility and economic benefit. <i>Direction 2</i>: Energy extraction and storage. Deep underground has abundant fuel matter, which was generated through long-term geological actions. Deep underground also has abundant space for the storage of energy and materials. This direction involves branches of engineering science, such as petroleum, engineering science and technology, material science, and environment science. <i>Direction 3</i>: Underground infrastructures. This direction focuses on the excavation and utilization of underground spaces, such as cavern construction, tunneling, and other pore space use. <i>Direction 4</i>: Geo-environments and waste geological disposal, which deals with the solutions to environmental problems in deep underground. The environmental problems have two types: The first one refers to the environmental problems induced by the exploitation of underground resources. The second one refers to the utilization of underground space (including pore space) to solve the environmental problems that are difficult to tackle on the ground surface, such as geological disposal of nuclea
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引用次数: 0
Acknowledgment of reviewers
Pub Date : 2024-12-08 DOI: 10.1002/dug2.12137
<p>The Editors of <i>Deep Underground Science and Engineering</i> (DUSE) wish to extend our deepest thanks to the following peer reviewers in 2024. We are grateful to their contributions of time and expertise to improve the quality of DUSE. We have made every effort to ensure that all ad hoc reviewers are correctly listed. Our apologies are given to those whose names were unwittingly misspelled or omitted.</p><p>Mahamuda Abu</p><p>Salaam Jansbaka Adams</p><p>Musab A. Q. Al-Janabi</p><p>Ni An</p><p>Matteo Antelmi</p><p>Gabriel de Alemar Barberes</p><p>Luca Basilone</p><p>Jianchao Cai</p><p>Jian Cao</p><p>Jie Cao</p><p>Shuai Cao</p><p>Zhiming Chao</p><p>Chaofan Chen</p><p>Jueliang Chen</p><p>Luwang Chen</p><p>Min Chen</p><p>Shi Chen</p><p>Yifan Chen</p><p>Yuedu Chen</p><p>Gang Cheng</p><p>Guanglei Cui</p><p>Xiaopu Cui</p><p>Chenxi Ding</p><p>Zhuo Dong</p><p>Xueming Du</p><p>Hongyu Duan</p><p>Hongyun Fan</p><p>Jinyang Fan</p><p>Ning Fan</p><p>Gan Feng</p><p>Aime Fournier</p><p>Jinwei Fu</p><p>Xiaolu Gan</p><p>Yanan Gao</p><p>Mehran Ghasabeh</p><p>Bin Gong</p><p>Fengqiang Gong</p><p>Qiuming Gong</p><p>Ankit Grag</p><p>Dogukan Guner</p><p>Weiyao Guo</p><p>Zhizheng Guo</p><p>H. Haeri</p><p>Jianyong Han</p><p>Sakuma Hiroshi</p><p>Hussein Hoteit</p><p>Zhengmeng Hou</p><p>Dawei Hu</p><p>Nan Hu</p><p>Xunjian Hu</p><p>Haiping Huang</p><p>Changbao Jiang</p><p>Wencheng Jin</p><p>Xiangsong Kong</p><p>Sunil Kumar</p><p>Guohui Lei</p><p>Bo Li</p><p>Genzhuang Li</p><p>Xiaofeng Li</p><p>Xing Li</p><p>Xudong Li</p><p>Yanghui Li</p><p>Yuwei Li</p><p>Zhiqiang Li</p><p>Wei Liang</p><p>Botao Lin</p><p>Hang Lin</p><p>Hejuan Liu</p><p>Jian Liu</p><p>Jianfeng Liu</p><p>Liyuan Liu</p><p>Mengxin Liu</p><p>Xuesheng Liu</p><p>A. J. (Tom) Van Loon</p><p>Shifeng Lu</p><p>Shouqing Lu</p><p>Yimin Lu</p><p>Zhao Lu</p><p>Zheng Lu</p><p>Hu Lv</p><p>Dongdong Ma</p><p>Ke Ma</p><p>Tianshou Ma</p><p>Satar Mahdevari</p><p>Mohamed Malki</p><p>Mohammad Mehrad</p><p>Pinqiang Mo</p><p>Mostafa Mollaali</p><p>Arun Narayanan Nair</p><p>Hongyang Ni</p><p>Fulong Ning</p><p>Qiang Ou</p><p>Dongjiang Pan</p><p>Deepak Patwa</p><p>J. K. Pearce</p><p>Huafu Pei</p><p>Chunde Piao</p><p>Chengzhi Qi</p><p>Dwarikanath Ratha</p><p>Bharat Rattan</p><p>Arshad Raza</p><p>Shengjie Rui</p><p>Zhenhua Rui</p><p>Ahmad Sakhaee Pour</p><p>Vahab Sarfarazi</p><p>Axel Schippers</p><p>Resmi Sebastian</p><p>Jianfu Shao</p><p>Zhushan Shao</p><p>Jihong Shi</p><p>Yue Shi</p><p>Dazhao Song</p><p>Yang Song</p><p>Zhanping Song</p><p>Mairaj Soomro</p><p>Alfred Strauss</p><p>Benyu Su</p><p>Shanjie Su</p><p>Wanghua Sui</p><p>Qiang Sun</p><p>Yuantian Sun</p><p>Xu Tao</p><p>Zhigang Tao</p><p>Francesco Tinti</p><p>Olli H. Tuovinen</p><p>Chunguang Wang</p><p>Daobing Wang</p><p>Fuyong Wang</p><p>Haiyang Wang</p><p>Huimin Wang</p><p>Jun Wang</p><p>Lu Wang</p><p>Luqi Wang</p><p>Mingquan Wang</p><p>Susheng Wang</p><p>Xiao Wang</p><p>Yukai Wang</p><p>Ming Wen</p><p>Tao Wen</p><p>Fei Wu</p><p>Huanyu Wu</p><p>Jinwen Wu</p><p>Saisai Wu</p><p>X
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Al-Janabi&lt;/p&gt;&lt;p&gt;Ni An&lt;/p&gt;&lt;p&gt;Matteo Antelmi&lt;/p&gt;&lt;p&gt;Gabriel de Alemar Barberes&lt;/p&gt;&lt;p&gt;Luca Basilone&lt;/p&gt;&lt;p&gt;Jianchao Cai&lt;/p&gt;&lt;p&gt;Jian Cao&lt;/p&gt;&lt;p&gt;Jie Cao&lt;/p&gt;&lt;p&gt;Shuai Cao&lt;/p&gt;&lt;p&gt;Zhiming Chao&lt;/p&gt;&lt;p&gt;Chaofan Chen&lt;/p&gt;&lt;p&gt;Jueliang Chen&lt;/p&gt;&lt;p&gt;Luwang Chen&lt;/p&gt;&lt;p&gt;Min Chen&lt;/p&gt;&lt;p&gt;Shi Chen&lt;/p&gt;&lt;p&gt;Yifan Chen&lt;/p&gt;&lt;p&gt;Yuedu Chen&lt;/p&gt;&lt;p&gt;Gang Cheng&lt;/p&gt;&lt;p&gt;Guanglei Cui&lt;/p&gt;&lt;p&gt;Xiaopu Cui&lt;/p&gt;&lt;p&gt;Chenxi Ding&lt;/p&gt;&lt;p&gt;Zhuo Dong&lt;/p&gt;&lt;p&gt;Xueming Du&lt;/p&gt;&lt;p&gt;Hongyu Duan&lt;/p&gt;&lt;p&gt;Hongyun Fan&lt;/p&gt;&lt;p&gt;Jinyang Fan&lt;/p&gt;&lt;p&gt;Ning Fan&lt;/p&gt;&lt;p&gt;Gan Feng&lt;/p&gt;&lt;p&gt;Aime Fournier&lt;/p&gt;&lt;p&gt;Jinwei Fu&lt;/p&gt;&lt;p&gt;Xiaolu Gan&lt;/p&gt;&lt;p&gt;Yanan Gao&lt;/p&gt;&lt;p&gt;Mehran Ghasabeh&lt;/p&gt;&lt;p&gt;Bin Gong&lt;/p&gt;&lt;p&gt;Fengqiang Gong&lt;/p&gt;&lt;p&gt;Qiuming Gong&lt;/p&gt;&lt;p&gt;Ankit Grag&lt;/p&gt;&lt;p&gt;Dogukan Guner&lt;/p&gt;&lt;p&gt;Weiyao Guo&lt;/p&gt;&lt;p&gt;Zhizheng Guo&lt;/p&gt;&lt;p&gt;H. Haeri&lt;/p&gt;&lt;p&gt;Jianyong Han&lt;/p&gt;&lt;p&gt;Sakuma Hiroshi&lt;/p&gt;&lt;p&gt;Hussein Hoteit&lt;/p&gt;&lt;p&gt;Zhengmeng Hou&lt;/p&gt;&lt;p&gt;Dawei Hu&lt;/p&gt;&lt;p&gt;Nan Hu&lt;/p&gt;&lt;p&gt;Xunjian Hu&lt;/p&gt;&lt;p&gt;Haiping Huang&lt;/p&gt;&lt;p&gt;Changbao Jiang&lt;/p&gt;&lt;p&gt;Wencheng Jin&lt;/p&gt;&lt;p&gt;Xiangsong Kong&lt;/p&gt;&lt;p&gt;Sunil Kumar&lt;/p&gt;&lt;p&gt;Guohui Lei&lt;/p&gt;&lt;p&gt;Bo Li&lt;/p&gt;&lt;p&gt;Genzhuang Li&lt;/p&gt;&lt;p&gt;Xiaofeng Li&lt;/p&gt;&lt;p&gt;Xing Li&lt;/p&gt;&lt;p&gt;Xudong Li&lt;/p&gt;&lt;p&gt;Yanghui Li&lt;/p&gt;&lt;p&gt;Yuwei Li&lt;/p&gt;&lt;p&gt;Zhiqiang Li&lt;/p&gt;&lt;p&gt;Wei Liang&lt;/p&gt;&lt;p&gt;Botao Lin&lt;/p&gt;&lt;p&gt;Hang Lin&lt;/p&gt;&lt;p&gt;Hejuan Liu&lt;/p&gt;&lt;p&gt;Jian Liu&lt;/p&gt;&lt;p&gt;Jianfeng Liu&lt;/p&gt;&lt;p&gt;Liyuan Liu&lt;/p&gt;&lt;p&gt;Mengxin Liu&lt;/p&gt;&lt;p&gt;Xuesheng Liu&lt;/p&gt;&lt;p&gt;A. J. (Tom) Van Loon&lt;/p&gt;&lt;p&gt;Shifeng Lu&lt;/p&gt;&lt;p&gt;Shouqing Lu&lt;/p&gt;&lt;p&gt;Yimin Lu&lt;/p&gt;&lt;p&gt;Zhao Lu&lt;/p&gt;&lt;p&gt;Zheng Lu&lt;/p&gt;&lt;p&gt;Hu Lv&lt;/p&gt;&lt;p&gt;Dongdong Ma&lt;/p&gt;&lt;p&gt;Ke Ma&lt;/p&gt;&lt;p&gt;Tianshou Ma&lt;/p&gt;&lt;p&gt;Satar Mahdevari&lt;/p&gt;&lt;p&gt;Mohamed Malki&lt;/p&gt;&lt;p&gt;Mohammad Mehrad&lt;/p&gt;&lt;p&gt;Pinqiang Mo&lt;/p&gt;&lt;p&gt;Mostafa Mollaali&lt;/p&gt;&lt;p&gt;Arun Narayanan Nair&lt;/p&gt;&lt;p&gt;Hongyang Ni&lt;/p&gt;&lt;p&gt;Fulong Ning&lt;/p&gt;&lt;p&gt;Qiang Ou&lt;/p&gt;&lt;p&gt;Dongjiang Pan&lt;/p&gt;&lt;p&gt;Deepak Patwa&lt;/p&gt;&lt;p&gt;J. K. Pearce&lt;/p&gt;&lt;p&gt;Huafu Pei&lt;/p&gt;&lt;p&gt;Chunde Piao&lt;/p&gt;&lt;p&gt;Chengzhi Qi&lt;/p&gt;&lt;p&gt;Dwarikanath Ratha&lt;/p&gt;&lt;p&gt;Bharat Rattan&lt;/p&gt;&lt;p&gt;Arshad Raza&lt;/p&gt;&lt;p&gt;Shengjie Rui&lt;/p&gt;&lt;p&gt;Zhenhua Rui&lt;/p&gt;&lt;p&gt;Ahmad Sakhaee Pour&lt;/p&gt;&lt;p&gt;Vahab Sarfarazi&lt;/p&gt;&lt;p&gt;Axel Schippers&lt;/p&gt;&lt;p&gt;Resmi Sebastian&lt;/p&gt;&lt;p&gt;Jianfu Shao&lt;/p&gt;&lt;p&gt;Zhushan Shao&lt;/p&gt;&lt;p&gt;Jihong Shi&lt;/p&gt;&lt;p&gt;Yue Shi&lt;/p&gt;&lt;p&gt;Dazhao Song&lt;/p&gt;&lt;p&gt;Yang Song&lt;/p&gt;&lt;p&gt;Zhanping Song&lt;/p&gt;&lt;p&gt;Mairaj Soomro&lt;/p&gt;&lt;p&gt;Alfred Strauss&lt;/p&gt;&lt;p&gt;Benyu Su&lt;/p&gt;&lt;p&gt;Shanjie Su&lt;/p&gt;&lt;p&gt;Wanghua Sui&lt;/p&gt;&lt;p&gt;Qiang Sun&lt;/p&gt;&lt;p&gt;Yuantian Sun&lt;/p&gt;&lt;p&gt;Xu Tao&lt;/p&gt;&lt;p&gt;Zhigang Tao&lt;/p&gt;&lt;p&gt;Francesco Tinti&lt;/p&gt;&lt;p&gt;Olli H. Tuovinen&lt;/p&gt;&lt;p&gt;Chunguang Wang&lt;/p&gt;&lt;p&gt;Daobing Wang&lt;/p&gt;&lt;p&gt;Fuyong Wang&lt;/p&gt;&lt;p&gt;Haiyang Wang&lt;/p&gt;&lt;p&gt;Huimin Wang&lt;/p&gt;&lt;p&gt;Jun Wang&lt;/p&gt;&lt;p&gt;Lu Wang&lt;/p&gt;&lt;p&gt;Luqi Wang&lt;/p&gt;&lt;p&gt;Mingquan Wang&lt;/p&gt;&lt;p&gt;Susheng Wang&lt;/p&gt;&lt;p&gt;Xiao Wang&lt;/p&gt;&lt;p&gt;Yukai Wang&lt;/p&gt;&lt;p&gt;Ming Wen&lt;/p&gt;&lt;p&gt;Tao Wen&lt;/p&gt;&lt;p&gt;Fei Wu&lt;/p&gt;&lt;p&gt;Huanyu Wu&lt;/p&gt;&lt;p&gt;Jinwen Wu&lt;/p&gt;&lt;p&gt;Saisai Wu&lt;/p&gt;&lt;p&gt;X","PeriodicalId":100363,"journal":{"name":"Deep Underground Science and Engineering","volume":"3 4","pages":"508-509"},"PeriodicalIF":0.0,"publicationDate":"2024-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/dug2.12137","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143248947","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
A review of mechanical deformation and seepage mechanism of rock with filled joints
Pub Date : 2024-09-27 DOI: 10.1002/dug2.12126
Lei Yue, Wei Li, Yu Liu, Shuncai Li, Jintao Wang

Various defects exist in natural rock masses, with filled joints being a vital factor complicating both the mechanical characteristics and seepage mechanisms of the rock mass. Filled jointed rocks usually show mechanical properties that are weaker than those of intact rocks but stronger than those of rocks with fractures. The shape of the rock, filling material, prefabricated fissure geometry, fissure roughness, fissure inclination angle, and other factors mainly influence the mechanical and seepage properties. This paper systematically reviews the research progress and findings on filled rock joints, focusing on three key aspects: mechanical properties, seepage properties, and flow properties under mechanical response. First, the study emphasizes the effects of prefabricated defects (shape, size, filling material, inclination angle, and other factors) on the mechanical properties of the rock. The fracture extension behavior of rock masses is revealed by the stress state of rocks with filled joints under uniaxial compression, using advanced auxiliary test techniques. Second, the seepage properties of rocks with filled joints are discussed and summarized through theoretical analysis, experimental research, and numerical simulations, focusing on organizing the seepage equations of these rocks. The study also considers the form of failure under stress–seepage coupling for both fully filled and partially filled fissured rocks. Finally, the limitations in the current research on the rock with filled joints are pointed out. It is emphasized that the specimens should more closely resemble real conditions, the analysis of mechanical indexes should be multi-parameterized, the construction of the seepage model should be refined, and the engineering coupling application should be multi-field–multiphase.

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引用次数: 0
Applications of artificial intelligence in geothermal resource exploration: A review 人工智能在地热资源勘探中的应用:综述
Pub Date : 2024-09-04 DOI: 10.1002/dug2.12122
Mahmoud AlGaiar, Mamdud Hossain, Andrei Petrovski, Aref Lashin, Nadimul Faisal

Artificial intelligence (AI) has become increasingly important in geothermal exploration, significantly improving the efficiency of resource identification. This review examines current AI applications, focusing on the algorithms used, the challenges addressed, and the opportunities created. In addition, the review highlights the growth of machine learning applications in geothermal exploration over the past decade, demonstrating how AI has improved the analysis of subsurface data to identify potential resources. AI techniques such as neural networks, support vector machines, and decision trees are used to estimate subsurface temperatures, predict rock and fluid properties, and identify optimal drilling locations. In particular, neural networks are the most widely used technique, further contributing to improved exploration efficiency. However, the widespread adoption of AI in geothermal exploration is hindered by challenges, such as data accessibility, data quality, and the need for tailored data science training for industry professionals. Furthermore, the review emphasizes the importance of data engineering methodologies, data scaling, and standardization to enable the development of accurate and generalizable AI models for geothermal exploration. It is concluded that the integration of AI into geothermal exploration holds great promise for accelerating the development of geothermal energy resources. By effectively addressing key challenges and leveraging AI technologies, the geothermal industry can unlock cost-effective and sustainable power generation opportunities.

人工智能(AI)在地热勘探中的重要性与日俱增,大大提高了资源识别的效率。本综述探讨了当前的人工智能应用,重点关注所使用的算法、应对的挑战以及创造的机遇。此外,综述还重点介绍了过去十年机器学习在地热勘探中的应用增长情况,展示了人工智能如何改进了对地下数据的分析,以识别潜在资源。神经网络、支持向量机和决策树等人工智能技术被用于估算地下温度、预测岩石和流体特性以及确定最佳钻探位置。其中,神经网络是应用最广泛的技术,可进一步提高勘探效率。然而,人工智能在地热勘探中的广泛应用受到各种挑战的阻碍,例如数据的可获取性、数据质量以及对行业专业人员进行量身定制的数据科学培训的需求。此外,综述还强调了数据工程方法、数据扩展和标准化的重要性,以便为地热勘探开发准确、可推广的人工智能模型。综述认为,将人工智能融入地热勘探,为加快地热能源资源的开发带来了巨大希望。通过有效应对关键挑战和利用人工智能技术,地热行业可以释放出具有成本效益和可持续的发电机会。
{"title":"Applications of artificial intelligence in geothermal resource exploration: A review","authors":"Mahmoud AlGaiar,&nbsp;Mamdud Hossain,&nbsp;Andrei Petrovski,&nbsp;Aref Lashin,&nbsp;Nadimul Faisal","doi":"10.1002/dug2.12122","DOIUrl":"https://doi.org/10.1002/dug2.12122","url":null,"abstract":"<p>Artificial intelligence (AI) has become increasingly important in geothermal exploration, significantly improving the efficiency of resource identification. This review examines current AI applications, focusing on the algorithms used, the challenges addressed, and the opportunities created. In addition, the review highlights the growth of machine learning applications in geothermal exploration over the past decade, demonstrating how AI has improved the analysis of subsurface data to identify potential resources. AI techniques such as neural networks, support vector machines, and decision trees are used to estimate subsurface temperatures, predict rock and fluid properties, and identify optimal drilling locations. In particular, neural networks are the most widely used technique, further contributing to improved exploration efficiency. However, the widespread adoption of AI in geothermal exploration is hindered by challenges, such as data accessibility, data quality, and the need for tailored data science training for industry professionals. Furthermore, the review emphasizes the importance of data engineering methodologies, data scaling, and standardization to enable the development of accurate and generalizable AI models for geothermal exploration. It is concluded that the integration of AI into geothermal exploration holds great promise for accelerating the development of geothermal energy resources. By effectively addressing key challenges and leveraging AI technologies, the geothermal industry can unlock cost-effective and sustainable power generation opportunities.</p>","PeriodicalId":100363,"journal":{"name":"Deep Underground Science and Engineering","volume":"3 3","pages":"269-285"},"PeriodicalIF":0.0,"publicationDate":"2024-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/dug2.12122","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142233178","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
The influence of the disturbing effect of roadways through faults on the faults' stability and slip characteristics
Pub Date : 2024-09-01 DOI: 10.1002/dug2.12119
Shuaifeng Lu, Andrew Chan, Xiaolin Wang, Shanyong Wang, Zhijun Wan, Jingyi Cheng

In order to mitigate the risk of geological disasters induced by fault activation when roadways intersect reverse faults in coal mining, this paper uses a combination of mechanical models with PFC2D software. A mechanical model is introduced to represent various fault angles, followed by a series of PFC2D loading and unloading tests to validate the model and investigate fault instability and crack propagation under different excavation rates and angles. The results show that (1) the theoretical fault model, impacted by roadway advancing, shows a linear reduction in horizontal stress at a rate of −2.01 MPa/m, while vertical stress increases linearly at 4.02 MPa/m. (2) At field excavation speeds of 2.4, 4.8, 7.2, and 9.6 m/day, the vertical loading rates for the model are 2.23, 4.47, 6.70, and 8.93 Pa/s, respectively. (3) Roadway advancement primarily causes tensile-compressive failures in front of the roadway, with a decrease in tensile cracks as the stress rate increases. (4) An increase in the fault angle leads to denser cracking on the fault plane, with negligible cracking near the fault itself. The dominant crack orientation is approximately 90°, aligned with the vertical stress.

{"title":"The influence of the disturbing effect of roadways through faults on the faults' stability and slip characteristics","authors":"Shuaifeng Lu,&nbsp;Andrew Chan,&nbsp;Xiaolin Wang,&nbsp;Shanyong Wang,&nbsp;Zhijun Wan,&nbsp;Jingyi Cheng","doi":"10.1002/dug2.12119","DOIUrl":"https://doi.org/10.1002/dug2.12119","url":null,"abstract":"<p>In order to mitigate the risk of geological disasters induced by fault activation when roadways intersect reverse faults in coal mining, this paper uses a combination of mechanical models with PFC<sup>2D</sup> software. A mechanical model is introduced to represent various fault angles, followed by a series of PFC<sup>2D</sup> loading and unloading tests to validate the model and investigate fault instability and crack propagation under different excavation rates and angles. The results show that (1) the theoretical fault model, impacted by roadway advancing, shows a linear reduction in horizontal stress at a rate of −2.01 MPa/m, while vertical stress increases linearly at 4.02 MPa/m. (2) At field excavation speeds of 2.4, 4.8, 7.2, and 9.6 m/day, the vertical loading rates for the model are 2.23, 4.47, 6.70, and 8.93 Pa/s, respectively. (3) Roadway advancement primarily causes tensile-compressive failures in front of the roadway, with a decrease in tensile cracks as the stress rate increases. (4) An increase in the fault angle leads to denser cracking on the fault plane, with negligible cracking near the fault itself. The dominant crack orientation is approximately 90°, aligned with the vertical stress.</p>","PeriodicalId":100363,"journal":{"name":"Deep Underground Science and Engineering","volume":"3 4","pages":"399-412"},"PeriodicalIF":0.0,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/dug2.12119","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143248171","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Geothermal energy for sustainable and green energy supply in the future 地热能为未来提供可持续的绿色能源
Pub Date : 2024-08-25 DOI: 10.1002/dug2.12121
Chunfai Leung, Jianguo Wang, Heping Xie, Xiaozhao Li
<p><i>Deep Underground Science and Engineering</i> (DUSE) publishes this special issue on geothermal energy. The guest editors of this special issue are Prof. Ranjith Pathegama Gamage (Monash University, Australia), Prof. Zhongwei Huang (China University of Petroleum, Beijing, China), and Prof. Bing Bai (Institute of Rock and Soil Mechanics, Chinese Academy of Sciences, Wuhan, China). Geothermal energy is one sustainable and renewable energy and currently a hot research topic in research and development. Geothermal energy supply is one of the long-term efforts for carbon footprint reductions to tackle climate change issues. The development of geothermal energy includes exploration and extraction processes. This special issue is to highlight the challenges on the exploration and extraction of geothermal energy such as initial high cost and difficulties in heat extraction from deep underground. This special issue focuses on new geothermal extraction system, new theory, new technology, new application of latest techniques such as artificial intelligence, and potential environmental effects.</p><p>This special issue publishes 10 articles with authors from different countries. An article is contributed by Chinese researchers on the site investigation for geothermal potential evaluation. They propose an integrated geophysics technique by combining multiple geophysics techniques with a new data processing method and apply it to the site investigation of the geothermal potential in a county. A Finnish researcher publishes an article to highlight the challenges and precautionary measures to overcome the difficulties in deep borehole heat exchanges. An article by US researchers explores possible geothermal-mechanical alternations due to heat exchange and extraction in geothermal systems. This article certainly provides new insights into the geothermal energy research and practice. Researchers from Morocco present a status and prospects article on the development of geothermal energy in their country.</p><p>Several interesting articles on geothermal reservoirs appear in this issue. A joint multinational research effort by researchers from the United Kingdom, Belgium, China, and Indonesia reports the results of experiments on fluid-rock interaction for potential carbon storage in geothermal reservoirs. Their experimental results have provided some insightful findings on the subject matter. In addition, a group of researchers from China investigates the impact of well placement and flow rate on production efficiency in fractured geothermal reservoirs. Another group of Chinese researchers provides a state-of-the-art review on research and development for the thermal energy extraction from deep hot dry rock reservoirs. These three articles are certainly useful to researchers and engineers in geothermal energy fields.</p><p>An article by Chinese researchers reports the development of a thermal stress loading technique for mechanical tests on hot dry rock. Last b
深层地下科学与工程》(DUSE)出版了这期关于地热能源的特刊。本期特邀编辑为 Ranjith Pathegama Gamage 教授(澳大利亚莫纳什大学)、黄中伟教授(中国石油大学,中国北京)和白冰教授(中国科学院岩石与土力学研究所,中国武汉)。地热能是一种可持续的可再生能源,也是当前研究和开发的热点。地热能供应是减少碳足迹以应对气候变化问题的长期努力之一。地热能的开发包括勘探和开采过程。本特刊旨在强调地热能勘探和提取过程中面临的挑战,如初期成本高、从地下深处提取热量困难等。本特刊重点关注新型地热提取系统、新理论、新技术、人工智能等最新技术的新应用以及潜在的环境影响。中国研究人员撰写了一篇关于地热潜力评估现场调查的文章。他们将多种地球物理技术与一种新的数据处理方法相结合,提出了一种综合地球物理技术,并将其应用于某县地热潜力的现场调查。一位芬兰研究人员发表文章,强调了克服深孔热交换困难的挑战和预防措施。美国研究人员的一篇文章探讨了地热系统中热交换和抽取可能导致的地热-机械交变。这篇文章无疑为地热能源研究和实践提供了新的见解。来自摩洛哥的研究人员发表了一篇关于该国地热能源发展现状和前景的文章。来自英国、比利时、中国和印度尼西亚的研究人员开展了一项多国联合研究,报告了关于地热储层中潜在碳储存的流体-岩石相互作用的实验结果。他们的实验结果为这一课题提供了一些有见地的发现。此外,一组来自中国的研究人员调查了井位和流速对裂缝地热储层生产效率的影响。另一组中国研究人员对从深层干热岩储层中提取热能的研究和开发进行了最新综述。这三篇文章对地热能源领域的研究人员和工程师肯定很有帮助。中国研究人员的一篇文章报道了热应力加载技术在干热岩机械测试中的发展。最后但同样重要的是,人工智能在地热能源研究中也发挥了作用。来自英国和沙特阿拉伯的研究人员发表了一篇关于人工智能在地热能源勘探中应用的最新综述。来自沙特阿拉伯的研究人员撰写的另一篇论文强调了利用深度机器学习来解决地热能研究和生产问题。随着本期特刊的出版,DUSE 欢迎大家在今后的特刊中继续贡献高质量、创新性的地热能研究成果。
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引用次数: 0
A state-of-the-art review on geothermal energy exploration in Morocco: Current status and prospects 摩洛哥地热能源勘探现状综述:现状与前景
Pub Date : 2024-08-13 DOI: 10.1002/dug2.12116
Redouane Meryem, Khalis Hind, Haissen Faouziya, Sadki Othman, Berkat N. Eddine, Raji Mohammed

In the last few decades, addressing the global challenge of implementation of strategies for renewable energy and energy efficiency has become crucial. Morocco, since 2009, has made a steadfast commitment to sustainability, with a particular focus on advancing the development of renewable energy resources. A comprehensive strategy has been formulated, centering on utilizing the country's energy potential to drive progress in this vital sector. Morocco is considered a country with abundant thermal water, indicating deep reservoirs with significant hydrothermal potential. Geothermal zones were selected based on the abundance of hot springs where water temperatures were high and geothermal gradients were significant. The abundance and importance of hot springs, combined with recent volcanism and ongoing non-tectonic activity linked to alpine orogeny, strongly suggest that these regions are promising reservoirs for geothermal energy. This great potential also extends to neighboring countries. In northeast and south Morocco, the temperature of thermal water ranges from 26 to 54°C. This study serves as an inclusive review of the geothermal potentialities in Morocco.

在过去几十年里,应对实施可再生能源和能源效率战略这一全球性挑战已变得至关重要。自 2009 年以来,摩洛哥坚定不移地致力于可持续发展,尤其注重推进可再生能源的开发。已制定了一项全面战略,其核心是利用该国的能源潜力,推动这一重要部门取得进展。摩洛哥被认为是一个拥有丰富热能水的国家,其深层水库具有巨大的水热潜力。地热区是根据水温高、地热梯度大的温泉数量选定的。温泉的丰富性和重要性,再加上近期的火山活动和与高山造山运动有关的持续非构造活动,都强烈表明这些地区是很有潜力的地热能源储藏地。这一巨大潜力也延伸到了邻国。在摩洛哥东北部和南部,热水温在 26 至 54 摄氏度之间。本研究对摩洛哥的地热潜力进行了全面审查。
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引用次数: 0
Research on the bearing capacity characteristics of initial support for horseshoe-shaped tunnel prefabrication
Pub Date : 2024-06-20 DOI: 10.1002/dug2.12110
Yongtao Xue, Fayuan Yan, Chengzhi Qi, Haochen Zhang, Zhao Xiuwang, Chen Jingxu

In view of the limited theoretical research on the load model of initial support for horseshoe-shaped prefabrication, this study focuses on the Luochuan Tunnel on the Xi'an-Yan'an newly built railway as the research object to explore its load model, load characteristic curve, plastic zone, deformation, and critical thickness. Theoretical research and numerical analysis were conducted. The results indicate that under the same boundary conditions, the ultimate bearing capacity of the prefabricated assembly initial support is higher than that of the shotcrete initial support, resulting in larger ultimate deformation capacity of the prefabricated assembly initial support. Based on numerical calculations, the ultimate deformation and critical thickness of the prefabricated initial lining for single- and double-track railway tunnels are obtained when buried at depths of 200, 500, and 900 m in rock masses of classes III, IV, and V.

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引用次数: 0
Geothermo-mechanical alterations due to heat energy extraction in enhanced geothermal systems: Overview and prospective directions 强化地热系统中热能提取引起的地热机械变化:概述与前瞻性方向
Pub Date : 2024-06-11 DOI: 10.1002/dug2.12109
Mary C. Ngoma, Oladoyin Kolawole, Olufemi Olorode

Geothermal energy from deep underground (or geological) formations, with or without its combination with carbon capture and storage (CCS), can be a key technology to mitigate anthropogenic greenhouse gas emissions and meet the 2050 net-zero carbon emission target. Geothermal resources in low-permeability and medium- and high-temperature reservoirs in sedimentary sequence require hydraulic stimulation for enhanced geothermal systems (EGS). However, fluid migration for geothermal energy in EGS or with potential CO2 storage in a CO2-EGS are both dependent on the in situ flow pathway network created by induced fluid injection. These thermo-mechanical interactions can be complex and induce varying alterations in the mechanical response when the working fluid is water (in EGS) or supercritical CO2 (in CO2-EGS), which could impact the geothermal energy recovery from geological formations. Therefore, there is a need for a deeper understanding of the heat extraction process in EGS and CO2-EGS. This study presents a systematic review of the effects of changes in mechanical properties and behavior of deep underground rocks on the induced flow pathway and heat recovery in EGS reservoirs with or without CO2 storage in CO2-EGS. Further, we proposed waterless-stimulated EGS as an alternative approach to improve heat energy extraction in EGS. Lastly, based on the results of our literature review and proposed ideas, we recommend promising areas of investigation that may provide more insights into understanding geothermo-mechanics to further stimulate new research studies and accelerate the development of geothermal energy as a viable clean energy technology.

来自地下(或地质)深层的地热能源,无论是否与碳捕集与封存(CCS)相结合,都可以成为减少人为温室气体排放和实现 2050 年净零碳排放目标的关键技术。沉积序列中低渗透性和中高温储层中的地热资源需要通过水力刺激来增强地热系统(EGS)。然而,在 EGS 或 CO2-EGS 中潜在的二氧化碳封存中,用于地热能源的流体迁移都依赖于诱导流体注入所形成的原位流动路径网络。当工作流体为水(在 EGS 中)或超临界 CO2(在 CO2-EGS 中)时,这些热机械相互作用可能非常复杂,并引起机械响应的不同变化,这可能会影响地层中的地热能回收。因此,有必要深入了解 EGS 和 CO2-EGS 的热提取过程。本研究系统地综述了地下深层岩石力学性质和行为的变化对 EGS 储层(无论是否在 CO2-EGS 中封存二氧化碳)的诱导流动路径和热能回收的影响。此外,我们还提出了无水刺激 EGS 作为改善 EGS 热能提取的替代方法。最后,根据我们的文献综述结果和提出的想法,我们建议了一些有前景的研究领域,这些领域可能会为理解地热力学提供更多的见解,从而进一步激发新的研究,加快地热能作为一种可行的清洁能源技术的发展。
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引用次数: 0
Numerical study on gas production via a horizontal well from hydrate reservoirs with different slope angles in the South China Sea 南海不同坡角水合物储层水平井产气数值研究
Pub Date : 2024-06-03 DOI: 10.1002/dug2.12103
Tingting Luo, Jianlin Song, Xiang Sun, Fanbao Cheng, Madhusudhan Bangalore Narasimha Murthy, Yulu Chen, Yi Zhao, Yongchen Song

It is important to study the effect of hydrate production on the physical and mechanical properties of low-permeability clayey–silty reservoirs for the large-scale exploitation of hydrate reservoirs in the South China Sea. In this study, a multiphysical-field coupling model, combined with actual exploration drilling data and the mechanical experimental data of hydrate cores in the laboratory, was established to investigate the physical and mechanical properties of low-permeability reservoirs with different slope angles during 5-year hydrate production by the depressurization method via a horizontal well. The result shows that the permeability of reservoirs severely affects gas production rate, and the maximum gas production amount of a 20-m-long horizontal well can reach 186.8 m3/day during the 5-year hydrate production. Reservoirs with smaller slope angles show higher gas production rates. The depressurization propagation and hydrate dissociation mainly develop along the direction parallel to the slope. Besides, the mean effective stress of reservoirs is concentrated in the near-wellbore area with the on-going hydrate production, and gradually decreases with the increase of the slope angle. Different from the effective stress distribution law, the total reservoir settlement amount first decreases and then increases with the increase of the slope angle. The maximum settlement of reservoirs with a 0° slope angle is up to 3.4 m, and the displacement in the near-wellbore area is as high as 2.2 m after 5 years of hydrate production. It is concluded that the pore pressure drop region of low-permeability reservoirs in the South China Sea is limited, and various slope angles further lead to differences in effective stress and strain of reservoirs during hydrate production, resulting in severe uneven settlement of reservoirs.

研究水合物生成对低渗透粘土-淤泥储层物理力学性质的影响,对于大规模开采南海水合物储层具有重要意义。本研究建立了多物理场耦合模型,结合实际勘探钻井数据和实验室水合物岩心力学实验数据,通过水平井减压法研究了 5 年水合物生产过程中不同斜角低渗透储层的物理力学性质。结果表明,储层的渗透率严重影响产气量,一口 20 米长的水平井在 5 年水合物生产期间的最大产气量可达 186.8 立方米/天。斜角较小的储层产气率较高。减压传播和水合物解离主要沿与斜坡平行的方向发展。此外,随着水合物的持续生产,储层的平均有效应力集中在近井筒区域,并随着斜率角的增大而逐渐减小。与有效应力分布规律不同,储层总沉降量随坡度角的增大先减小后增大。水合物生产 5 年后,坡角为 0° 的储层最大沉降量达 3.4 米,近井筒区域的位移高达 2.2 米。结论是南海低渗透储层的孔隙压降区域是有限的,各种坡角进一步导致了水合物生产过程中储层有效应力和应变的差异,造成储层严重的不均匀沉降。
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Deep Underground Science and Engineering
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