Inversion of Mine Transient Electromagnetic Data via the PSO-GIS Algorithm From a Conical Source
The overlap winding system of coils in a multiturn small loop device in the transient electromagnetic method makes the mutual inductance coefficient large, and the measurement data are seriously affected by the turn-off effect. The conical source has the advantages of low mutual inductance effects a...
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Veröffentlicht in: | IEEE transactions on geoscience and remote sensing 2022, Vol.60, p.1-12 |
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description | The overlap winding system of coils in a multiturn small loop device in the transient electromagnetic method makes the mutual inductance coefficient large, and the measurement data are seriously affected by the turn-off effect. The conical source has the advantages of low mutual inductance effects and strong secondary fields. This study conducts an inversion of an improved particle swarm optimization (PSO) algorithm for this device. The new PSO algorithm improvement strategy (PSO-GIS algorithm) has the advantages of high success rate of optimization, fast convergence speed, high calculation accuracy, and low calculation elapsed time. The inversion results of the theoretical model and the measured mine data show that the PSO-GIS algorithm does not depend on the initial model setting, and the inversion of the layered full-space geoelectric model has a fast convergence speed and enhanced calculation accuracy. The PSO-GIS algorithm inversion is applied to the measured data of coal mine wells, which can achieve the effect of abnormal separation of roof and floor. The reflection of low-resistivity anomalous bodies is refined, and the drilling verification results agree well with the inversion interpretation. The PSO-GIS algorithm inversion in this article can be applied to the processing of real measured mine data to improve the interpretation effect of full-space inversion of mines. |
doi_str_mv | 10.1109/TGRS.2022.3173301 |
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The conical source has the advantages of low mutual inductance effects and strong secondary fields. This study conducts an inversion of an improved particle swarm optimization (PSO) algorithm for this device. The new PSO algorithm improvement strategy (PSO-GIS algorithm) has the advantages of high success rate of optimization, fast convergence speed, high calculation accuracy, and low calculation elapsed time. The inversion results of the theoretical model and the measured mine data show that the PSO-GIS algorithm does not depend on the initial model setting, and the inversion of the layered full-space geoelectric model has a fast convergence speed and enhanced calculation accuracy. The PSO-GIS algorithm inversion is applied to the measured data of coal mine wells, which can achieve the effect of abnormal separation of roof and floor. The reflection of low-resistivity anomalous bodies is refined, and the drilling verification results agree well with the inversion interpretation. The PSO-GIS algorithm inversion in this article can be applied to the processing of real measured mine data to improve the interpretation effect of full-space inversion of mines.</description><identifier>ISSN: 0196-2892</identifier><identifier>EISSN: 1558-0644</identifier><identifier>DOI: 10.1109/TGRS.2022.3173301</identifier><identifier>CODEN: IGRSD2</identifier><language>eng</language><publisher>New York: IEEE</publisher><subject>Accuracy ; Algorithms ; Coal ; Coal mines ; Coils ; Coils (windings) ; Conical source ; Convergence ; Data models ; Drilling ; Electric potential ; Fuel processing industries ; Geoelectricity ; Geographical information systems ; Inductance ; inversion ; mine transient electromagnetic (MTEM) ; Optimization ; Particle swarm optimization ; particle swarm optimization (PSO) ; Transient analysis</subject><ispartof>IEEE transactions on geoscience and remote sensing, 2022, Vol.60, p.1-12</ispartof><rights>Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2022</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c293t-8ae6497a9982ef236c7c36e20366965769227243996e0bbd036acbad862b2bd73</citedby><cites>FETCH-LOGICAL-c293t-8ae6497a9982ef236c7c36e20366965769227243996e0bbd036acbad862b2bd73</cites><orcidid>0000-0003-3368-0973 ; 0000-0003-1923-7166 ; 0000-0003-1293-5412 ; 0000-0002-2786-8243</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/9770801$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>315,781,785,797,4025,27927,27928,27929,54762</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/9770801$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Jiao, Junjun</creatorcontrib><creatorcontrib>Yang, Haiyan</creatorcontrib><creatorcontrib>Chen, Zhi</creatorcontrib><creatorcontrib>Gu, Yanyan</creatorcontrib><creatorcontrib>Liu, Jianpeng</creatorcontrib><title>Inversion of Mine Transient Electromagnetic Data via the PSO-GIS Algorithm From a Conical Source</title><title>IEEE transactions on geoscience and remote sensing</title><addtitle>TGRS</addtitle><description>The overlap winding system of coils in a multiturn small loop device in the transient electromagnetic method makes the mutual inductance coefficient large, and the measurement data are seriously affected by the turn-off effect. The conical source has the advantages of low mutual inductance effects and strong secondary fields. This study conducts an inversion of an improved particle swarm optimization (PSO) algorithm for this device. The new PSO algorithm improvement strategy (PSO-GIS algorithm) has the advantages of high success rate of optimization, fast convergence speed, high calculation accuracy, and low calculation elapsed time. The inversion results of the theoretical model and the measured mine data show that the PSO-GIS algorithm does not depend on the initial model setting, and the inversion of the layered full-space geoelectric model has a fast convergence speed and enhanced calculation accuracy. The PSO-GIS algorithm inversion is applied to the measured data of coal mine wells, which can achieve the effect of abnormal separation of roof and floor. The reflection of low-resistivity anomalous bodies is refined, and the drilling verification results agree well with the inversion interpretation. The PSO-GIS algorithm inversion in this article can be applied to the processing of real measured mine data to improve the interpretation effect of full-space inversion of mines.</description><subject>Accuracy</subject><subject>Algorithms</subject><subject>Coal</subject><subject>Coal mines</subject><subject>Coils</subject><subject>Coils (windings)</subject><subject>Conical source</subject><subject>Convergence</subject><subject>Data models</subject><subject>Drilling</subject><subject>Electric potential</subject><subject>Fuel processing industries</subject><subject>Geoelectricity</subject><subject>Geographical information systems</subject><subject>Inductance</subject><subject>inversion</subject><subject>mine transient electromagnetic (MTEM)</subject><subject>Optimization</subject><subject>Particle swarm optimization</subject><subject>particle swarm optimization (PSO)</subject><subject>Transient analysis</subject><issn>0196-2892</issn><issn>1558-0644</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><sourceid>RIE</sourceid><recordid>eNo9kF1PwjAUhhujiYj-AONNE6-H_dja9ZIgIAkG4_B6duUMSkaL7SDx3zsC8eok5zzveZMHoUdKBpQS9bKcfhYDRhgbcCo5J_QK9WiW5QkRaXqNeoQqkbBcsVt0F-OWEJpmVPbQ98wdIUTrHfY1frcO8DJoFy24Fo8bMG3wO7120FqDX3Wr8dFq3G4AfxSLZDor8LBZ-2DbzQ5POhRrPPLOGt3gwh-CgXt0U-smwsNl9tHXZLwcvSXzxXQ2Gs4TwxRvk1yDSJXUSuUMasaFkYYLYIQLoUQmhWJMspQrJYBU1arba1PpVS5YxaqV5H30fP67D_7nALEtt12_6ypLJiQjSilJO4qeKRN8jAHqch_sToffkpLyJLI8iSxPIsuLyC7zdM5YAPjnlZQk765_WiptWA</recordid><startdate>2022</startdate><enddate>2022</enddate><creator>Jiao, Junjun</creator><creator>Yang, Haiyan</creator><creator>Chen, Zhi</creator><creator>Gu, Yanyan</creator><creator>Liu, Jianpeng</creator><general>IEEE</general><general>The Institute of Electrical and Electronics Engineers, Inc. (IEEE)</general><scope>97E</scope><scope>RIA</scope><scope>RIE</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7UA</scope><scope>8FD</scope><scope>C1K</scope><scope>F1W</scope><scope>FR3</scope><scope>H8D</scope><scope>H96</scope><scope>KR7</scope><scope>L.G</scope><scope>L7M</scope><orcidid>https://orcid.org/0000-0003-3368-0973</orcidid><orcidid>https://orcid.org/0000-0003-1923-7166</orcidid><orcidid>https://orcid.org/0000-0003-1293-5412</orcidid><orcidid>https://orcid.org/0000-0002-2786-8243</orcidid></search><sort><creationdate>2022</creationdate><title>Inversion of Mine Transient Electromagnetic Data via the PSO-GIS Algorithm From a Conical Source</title><author>Jiao, Junjun ; Yang, Haiyan ; Chen, Zhi ; Gu, Yanyan ; Liu, Jianpeng</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c293t-8ae6497a9982ef236c7c36e20366965769227243996e0bbd036acbad862b2bd73</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2022</creationdate><topic>Accuracy</topic><topic>Algorithms</topic><topic>Coal</topic><topic>Coal mines</topic><topic>Coils</topic><topic>Coils (windings)</topic><topic>Conical source</topic><topic>Convergence</topic><topic>Data models</topic><topic>Drilling</topic><topic>Electric potential</topic><topic>Fuel processing industries</topic><topic>Geoelectricity</topic><topic>Geographical information systems</topic><topic>Inductance</topic><topic>inversion</topic><topic>mine transient electromagnetic (MTEM)</topic><topic>Optimization</topic><topic>Particle swarm optimization</topic><topic>particle swarm optimization (PSO)</topic><topic>Transient analysis</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Jiao, Junjun</creatorcontrib><creatorcontrib>Yang, Haiyan</creatorcontrib><creatorcontrib>Chen, Zhi</creatorcontrib><creatorcontrib>Gu, Yanyan</creatorcontrib><creatorcontrib>Liu, Jianpeng</creatorcontrib><collection>IEEE All-Society Periodicals Package (ASPP) 2005-present</collection><collection>IEEE All-Society Periodicals Package (ASPP) 1998-Present</collection><collection>IEEE Electronic Library (IEL)</collection><collection>CrossRef</collection><collection>Water Resources Abstracts</collection><collection>Technology Research Database</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ASFA: Aquatic Sciences and Fisheries Abstracts</collection><collection>Engineering Research Database</collection><collection>Aerospace Database</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) 2: Ocean Technology, Policy & Non-Living Resources</collection><collection>Civil Engineering Abstracts</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) Professional</collection><collection>Advanced Technologies Database with Aerospace</collection><jtitle>IEEE transactions on geoscience and remote sensing</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Jiao, Junjun</au><au>Yang, Haiyan</au><au>Chen, Zhi</au><au>Gu, Yanyan</au><au>Liu, Jianpeng</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Inversion of Mine Transient Electromagnetic Data via the PSO-GIS Algorithm From a Conical Source</atitle><jtitle>IEEE transactions on geoscience and remote sensing</jtitle><stitle>TGRS</stitle><date>2022</date><risdate>2022</risdate><volume>60</volume><spage>1</spage><epage>12</epage><pages>1-12</pages><issn>0196-2892</issn><eissn>1558-0644</eissn><coden>IGRSD2</coden><abstract>The overlap winding system of coils in a multiturn small loop device in the transient electromagnetic method makes the mutual inductance coefficient large, and the measurement data are seriously affected by the turn-off effect. The conical source has the advantages of low mutual inductance effects and strong secondary fields. This study conducts an inversion of an improved particle swarm optimization (PSO) algorithm for this device. The new PSO algorithm improvement strategy (PSO-GIS algorithm) has the advantages of high success rate of optimization, fast convergence speed, high calculation accuracy, and low calculation elapsed time. The inversion results of the theoretical model and the measured mine data show that the PSO-GIS algorithm does not depend on the initial model setting, and the inversion of the layered full-space geoelectric model has a fast convergence speed and enhanced calculation accuracy. The PSO-GIS algorithm inversion is applied to the measured data of coal mine wells, which can achieve the effect of abnormal separation of roof and floor. The reflection of low-resistivity anomalous bodies is refined, and the drilling verification results agree well with the inversion interpretation. The PSO-GIS algorithm inversion in this article can be applied to the processing of real measured mine data to improve the interpretation effect of full-space inversion of mines.</abstract><cop>New York</cop><pub>IEEE</pub><doi>10.1109/TGRS.2022.3173301</doi><tpages>12</tpages><orcidid>https://orcid.org/0000-0003-3368-0973</orcidid><orcidid>https://orcid.org/0000-0003-1923-7166</orcidid><orcidid>https://orcid.org/0000-0003-1293-5412</orcidid><orcidid>https://orcid.org/0000-0002-2786-8243</orcidid></addata></record> |
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subjects | Accuracy Algorithms Coal Coal mines Coils Coils (windings) Conical source Convergence Data models Drilling Electric potential Fuel processing industries Geoelectricity Geographical information systems Inductance inversion mine transient electromagnetic (MTEM) Optimization Particle swarm optimization particle swarm optimization (PSO) Transient analysis |
title | Inversion of Mine Transient Electromagnetic Data via the PSO-GIS Algorithm From a Conical Source |
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