Identification of Coal and Gas Outburst-Hazardous Zones by Electric Potential Inversion During Mining Process in Deep Coal Seam
Coal remains an important fuel and energy, especially in China. For coal mining in deep mines, the threat of coal and rock dynamic disasters (such as coal and gas outburst) to safe production is becoming more and more serious with the greatly increasing geo-stress and gas pressure. Hence, it is part...
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description | Coal remains an important fuel and energy, especially in China. For coal mining in deep mines, the threat of coal and rock dynamic disasters (such as coal and gas outburst) to safe production is becoming more and more serious with the greatly increasing geo-stress and gas pressure. Hence, it is particularly important to real-timely monitor and finely identify outburst-hazardous zones and their hazard levels during coal mining. However, conventional methods fail to continuously and precisely monitor outburst-hazardous zones in spatial distribution. Previous studies have shown that under the coupling action of stress and gas, the electric potential (EP) signals can be generated and their response characteristics are closely related to the loading state and damage evolution process of coal. The inversion imaging method can be utilized to analyze the spatial distribution of the EP signals. On this basis, the field tests were conducted to study the EP response characteristics to the mining process of deep coal seams and analyze the relationship between the EP response and outburst hazard. Moreover, in view of the EP inversion imaging mechanism, the bilateral EP inversion n model was established on the mining-disturbed coal seam ahead of the mining face and the field application was also carried out. Furthermore, on account of the membership index of fuzzy mathematics, the critical EP inversion value was proposed. Then the outburst-hazardous zones in the coal seam ahead of the mining face were divided finely and identified quantitatively. In the end, the verification result showed that the yellow zones enable to identify most of outburst-hazardous zones, thus effectively avoiding the missing identification. Besides, the red zones can improve the identification efficiency, which is conducive to focusing on identifying zones with a high hazard level. The study results provide a valuable new application method for finely identifying coal and gas outburst hazards and preventing coal and rock dynamic disasters in deep coal mines.
Highlights
The EP signals response can reflect the stress state and damage evolution of coal seams.
The bilateral EP inversion model was established ahead of mining face to reveal the electric field distribution characteristics.
The EP inversion results could identify the hazardous zones of dynamic disaster for coal and gas outburst in the coal seam. |
doi_str_mv | 10.1007/s00603-022-02804-z |
format | Article |
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Highlights
The EP signals response can reflect the stress state and damage evolution of coal seams.
The bilateral EP inversion model was established ahead of mining face to reveal the electric field distribution characteristics.
The EP inversion results could identify the hazardous zones of dynamic disaster for coal and gas outburst in the coal seam.</description><identifier>ISSN: 0723-2632</identifier><identifier>EISSN: 1434-453X</identifier><identifier>DOI: 10.1007/s00603-022-02804-z</identifier><language>eng</language><publisher>Vienna: Springer Vienna</publisher><subject>Civil Engineering ; Coal ; Coal gas outbursts ; Coal mines ; Coal mining ; Damage ; Disasters ; Distribution ; Earth and Environmental Science ; Earth Sciences ; Electric fields ; Electric potential ; Evolution ; Field tests ; Gas pressure ; Geophysics/Geodesy ; Hazard identification ; Identification ; Imaging techniques ; Mathematics ; Methods ; Mines ; Original Paper ; Rocks ; Spatial distribution</subject><ispartof>Rock mechanics and rock engineering, 2022-06, Vol.55 (6), p.3439-3450</ispartof><rights>The Author(s), under exclusive licence to Springer-Verlag GmbH Austria, part of Springer Nature 2022</rights><rights>The Author(s), under exclusive licence to Springer-Verlag GmbH Austria, part of Springer Nature 2022.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c319t-9752648424a198312dbb03d129c77989ffe283b352fff6e13a5bfd29b2f259613</citedby><cites>FETCH-LOGICAL-c319t-9752648424a198312dbb03d129c77989ffe283b352fff6e13a5bfd29b2f259613</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s00603-022-02804-z$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s00603-022-02804-z$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>314,780,784,27924,27925,41488,42557,51319</link.rule.ids></links><search><creatorcontrib>Niu, Yue</creatorcontrib><creatorcontrib>Wang, Enyuan</creatorcontrib><creatorcontrib>Li, Zhonghui</creatorcontrib><creatorcontrib>Gao, Feng</creatorcontrib><creatorcontrib>Zhang, Zhizhen</creatorcontrib><creatorcontrib>Li, Baolin</creatorcontrib><creatorcontrib>Zhang, Xin</creatorcontrib><title>Identification of Coal and Gas Outburst-Hazardous Zones by Electric Potential Inversion During Mining Process in Deep Coal Seam</title><title>Rock mechanics and rock engineering</title><addtitle>Rock Mech Rock Eng</addtitle><description>Coal remains an important fuel and energy, especially in China. For coal mining in deep mines, the threat of coal and rock dynamic disasters (such as coal and gas outburst) to safe production is becoming more and more serious with the greatly increasing geo-stress and gas pressure. Hence, it is particularly important to real-timely monitor and finely identify outburst-hazardous zones and their hazard levels during coal mining. However, conventional methods fail to continuously and precisely monitor outburst-hazardous zones in spatial distribution. Previous studies have shown that under the coupling action of stress and gas, the electric potential (EP) signals can be generated and their response characteristics are closely related to the loading state and damage evolution process of coal. The inversion imaging method can be utilized to analyze the spatial distribution of the EP signals. On this basis, the field tests were conducted to study the EP response characteristics to the mining process of deep coal seams and analyze the relationship between the EP response and outburst hazard. Moreover, in view of the EP inversion imaging mechanism, the bilateral EP inversion n model was established on the mining-disturbed coal seam ahead of the mining face and the field application was also carried out. Furthermore, on account of the membership index of fuzzy mathematics, the critical EP inversion value was proposed. Then the outburst-hazardous zones in the coal seam ahead of the mining face were divided finely and identified quantitatively. In the end, the verification result showed that the yellow zones enable to identify most of outburst-hazardous zones, thus effectively avoiding the missing identification. Besides, the red zones can improve the identification efficiency, which is conducive to focusing on identifying zones with a high hazard level. The study results provide a valuable new application method for finely identifying coal and gas outburst hazards and preventing coal and rock dynamic disasters in deep coal mines.
Highlights
The EP signals response can reflect the stress state and damage evolution of coal seams.
The bilateral EP inversion model was established ahead of mining face to reveal the electric field distribution characteristics.
The EP inversion results could identify the hazardous zones of dynamic disaster for coal and gas outburst in the coal seam.</description><subject>Civil Engineering</subject><subject>Coal</subject><subject>Coal gas outbursts</subject><subject>Coal mines</subject><subject>Coal mining</subject><subject>Damage</subject><subject>Disasters</subject><subject>Distribution</subject><subject>Earth and Environmental Science</subject><subject>Earth Sciences</subject><subject>Electric fields</subject><subject>Electric potential</subject><subject>Evolution</subject><subject>Field tests</subject><subject>Gas pressure</subject><subject>Geophysics/Geodesy</subject><subject>Hazard identification</subject><subject>Identification</subject><subject>Imaging techniques</subject><subject>Mathematics</subject><subject>Methods</subject><subject>Mines</subject><subject>Original Paper</subject><subject>Rocks</subject><subject>Spatial distribution</subject><issn>0723-2632</issn><issn>1434-453X</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><recordid>eNp9UE1LwzAYDqLgnP4BTwHP1eRN2zRHmXMbTByoIF5C2iaSsSUzaYXt4l-3tYI3Dy_P4fnifRC6pOSaEsJvIiE5YQkB6K4gaXI4QiOasjRJM_Z6jEaEA0sgZ3CKzmJcE9KRvBihr0WtXWONrVRjvcPe4IlXG6xcjWcq4se2KdsQm2SuDirUvo34zTsdcbnH042ummArvPJNH9LZFu5Th9gH3bXBunf8YF0Pq-ArHSO2HaH1buh40mp7jk6M2kR98Ytj9HI_fZ7Mk-XjbDG5XSYVo6JJBM8gT4sUUkVFwSjUZUlYTUFUnItCGKOhYCXLwBiTa8pUVpoaRAkGMpFTNkZXQ-4u-I9Wx0aufRtcVykh52mW84LyTgWDqgo-xqCN3AW7VWEvKZH90HIYWnZDy5-h5aEzscEUd_3LOvxF_-P6BlkMgX0</recordid><startdate>20220601</startdate><enddate>20220601</enddate><creator>Niu, Yue</creator><creator>Wang, Enyuan</creator><creator>Li, Zhonghui</creator><creator>Gao, Feng</creator><creator>Zhang, Zhizhen</creator><creator>Li, Baolin</creator><creator>Zhang, Xin</creator><general>Springer Vienna</general><general>Springer Nature B.V</general><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7TN</scope><scope>7UA</scope><scope>7XB</scope><scope>88I</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>8FK</scope><scope>ABJCF</scope><scope>ABUWG</scope><scope>AEUYN</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>BHPHI</scope><scope>BKSAR</scope><scope>C1K</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>F1W</scope><scope>FR3</scope><scope>GNUQQ</scope><scope>H96</scope><scope>HCIFZ</scope><scope>KR7</scope><scope>L.G</scope><scope>L6V</scope><scope>M2P</scope><scope>M7S</scope><scope>PCBAR</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PTHSS</scope><scope>Q9U</scope></search><sort><creationdate>20220601</creationdate><title>Identification of Coal and Gas Outburst-Hazardous Zones by Electric Potential Inversion During Mining Process in Deep Coal Seam</title><author>Niu, Yue ; Wang, Enyuan ; Li, Zhonghui ; Gao, Feng ; Zhang, Zhizhen ; Li, Baolin ; Zhang, Xin</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c319t-9752648424a198312dbb03d129c77989ffe283b352fff6e13a5bfd29b2f259613</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2022</creationdate><topic>Civil Engineering</topic><topic>Coal</topic><topic>Coal gas outbursts</topic><topic>Coal mines</topic><topic>Coal mining</topic><topic>Damage</topic><topic>Disasters</topic><topic>Distribution</topic><topic>Earth and Environmental Science</topic><topic>Earth Sciences</topic><topic>Electric fields</topic><topic>Electric potential</topic><topic>Evolution</topic><topic>Field tests</topic><topic>Gas pressure</topic><topic>Geophysics/Geodesy</topic><topic>Hazard identification</topic><topic>Identification</topic><topic>Imaging techniques</topic><topic>Mathematics</topic><topic>Methods</topic><topic>Mines</topic><topic>Original Paper</topic><topic>Rocks</topic><topic>Spatial distribution</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Niu, Yue</creatorcontrib><creatorcontrib>Wang, Enyuan</creatorcontrib><creatorcontrib>Li, Zhonghui</creatorcontrib><creatorcontrib>Gao, Feng</creatorcontrib><creatorcontrib>Zhang, Zhizhen</creatorcontrib><creatorcontrib>Li, Baolin</creatorcontrib><creatorcontrib>Zhang, Xin</creatorcontrib><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Oceanic Abstracts</collection><collection>Water Resources Abstracts</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Science Database (Alumni Edition)</collection><collection>Technology Research Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>Materials Science & Engineering Collection</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest One Sustainability</collection><collection>ProQuest Central UK/Ireland</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>Technology Collection</collection><collection>Natural Science Collection</collection><collection>Earth, Atmospheric & Aquatic Science Collection</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>ASFA: Aquatic Sciences and Fisheries Abstracts</collection><collection>Engineering Research Database</collection><collection>ProQuest Central Student</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) 2: Ocean Technology, Policy & Non-Living Resources</collection><collection>SciTech Premium Collection</collection><collection>Civil Engineering Abstracts</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) Professional</collection><collection>ProQuest Engineering Collection</collection><collection>Science Database</collection><collection>Engineering Database</collection><collection>Earth, Atmospheric & Aquatic Science Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>Engineering Collection</collection><collection>ProQuest Central Basic</collection><jtitle>Rock mechanics and rock engineering</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Niu, Yue</au><au>Wang, Enyuan</au><au>Li, Zhonghui</au><au>Gao, Feng</au><au>Zhang, Zhizhen</au><au>Li, Baolin</au><au>Zhang, Xin</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Identification of Coal and Gas Outburst-Hazardous Zones by Electric Potential Inversion During Mining Process in Deep Coal Seam</atitle><jtitle>Rock mechanics and rock engineering</jtitle><stitle>Rock Mech Rock Eng</stitle><date>2022-06-01</date><risdate>2022</risdate><volume>55</volume><issue>6</issue><spage>3439</spage><epage>3450</epage><pages>3439-3450</pages><issn>0723-2632</issn><eissn>1434-453X</eissn><abstract>Coal remains an important fuel and energy, especially in China. For coal mining in deep mines, the threat of coal and rock dynamic disasters (such as coal and gas outburst) to safe production is becoming more and more serious with the greatly increasing geo-stress and gas pressure. Hence, it is particularly important to real-timely monitor and finely identify outburst-hazardous zones and their hazard levels during coal mining. However, conventional methods fail to continuously and precisely monitor outburst-hazardous zones in spatial distribution. Previous studies have shown that under the coupling action of stress and gas, the electric potential (EP) signals can be generated and their response characteristics are closely related to the loading state and damage evolution process of coal. The inversion imaging method can be utilized to analyze the spatial distribution of the EP signals. On this basis, the field tests were conducted to study the EP response characteristics to the mining process of deep coal seams and analyze the relationship between the EP response and outburst hazard. Moreover, in view of the EP inversion imaging mechanism, the bilateral EP inversion n model was established on the mining-disturbed coal seam ahead of the mining face and the field application was also carried out. Furthermore, on account of the membership index of fuzzy mathematics, the critical EP inversion value was proposed. Then the outburst-hazardous zones in the coal seam ahead of the mining face were divided finely and identified quantitatively. In the end, the verification result showed that the yellow zones enable to identify most of outburst-hazardous zones, thus effectively avoiding the missing identification. Besides, the red zones can improve the identification efficiency, which is conducive to focusing on identifying zones with a high hazard level. The study results provide a valuable new application method for finely identifying coal and gas outburst hazards and preventing coal and rock dynamic disasters in deep coal mines.
Highlights
The EP signals response can reflect the stress state and damage evolution of coal seams.
The bilateral EP inversion model was established ahead of mining face to reveal the electric field distribution characteristics.
The EP inversion results could identify the hazardous zones of dynamic disaster for coal and gas outburst in the coal seam.</abstract><cop>Vienna</cop><pub>Springer Vienna</pub><doi>10.1007/s00603-022-02804-z</doi><tpages>12</tpages></addata></record> |
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subjects | Civil Engineering Coal Coal gas outbursts Coal mines Coal mining Damage Disasters Distribution Earth and Environmental Science Earth Sciences Electric fields Electric potential Evolution Field tests Gas pressure Geophysics/Geodesy Hazard identification Identification Imaging techniques Mathematics Methods Mines Original Paper Rocks Spatial distribution |
title | Identification of Coal and Gas Outburst-Hazardous Zones by Electric Potential Inversion During Mining Process in Deep Coal Seam |
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