Joint Inversion of Gravity and Gravity Gradient Data Based on Cross-Gradient Function

Gravity exploration is one of the most commonly used geophysical exploration methods, and it is widely used in the field of mineral resources' exploration and engineering survey benefited from its advantages of large exploration depth, economy, and high efficiency. Gravity and its gradient data...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:IEEE sensors journal 2024-07, Vol.24 (13), p.20940-20948
Hauptverfasser: Qiao, Zhong-Kun, Zhang, Zong-Yu, Hu, Ruo, Shen, Zheng-Hao, Yuan, Peng, Zhou, Hang, Huang, Xin-Yi, Zhou, Fei, Shi, Hui-Yan, Wu, Xue-Min, Wu, Bin, Wang, Xiao-Long, Lin, Qiang
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext bestellen
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
container_end_page 20948
container_issue 13
container_start_page 20940
container_title IEEE sensors journal
container_volume 24
creator Qiao, Zhong-Kun
Zhang, Zong-Yu
Hu, Ruo
Shen, Zheng-Hao
Yuan, Peng
Zhou, Hang
Huang, Xin-Yi
Zhou, Fei
Shi, Hui-Yan
Wu, Xue-Min
Wu, Bin
Wang, Xiao-Long
Lin, Qiang
description Gravity exploration is one of the most commonly used geophysical exploration methods, and it is widely used in the field of mineral resources' exploration and engineering survey benefited from its advantages of large exploration depth, economy, and high efficiency. Gravity and its gradient data reflect the different distribution characteristics of subsurface anomalous objects, and therefore, the single data inversion cannot achieve an accurate identification for the underground objects and suffer from stronger nonuniqueness problems. To accurately identify the location and distribution characteristics of subsurface objects, we first construct models to perform separate inversions of gravity and gravity gradient data, analyze the identification ability of different anomaly components, and then innovatively introduce a cross-gradient function for the joint inversion of two gravity tensor data, {V}_{ {xx}} and {V}_{ {yy}} . The results show that the method combines the advantages of these two components and reflects the horizontal position of the targeted bodies more accurately; meanwhile, the portrayal of the boundary is also closer to the real model. Finally, we apply the above method to the Vinton Dome, and the inversion results recover the accurate spatial location of the Vinton Dome. The practical application results show that the joint cross-gradient inversion of gravity and gravity gradient data is more efficient for spatial location trapping and boundary inscription of subsurface targeted bodies compared with the inversion of individual component.
doi_str_mv 10.1109/JSEN.2024.3398301
format Article
fullrecord <record><control><sourceid>proquest_RIE</sourceid><recordid>TN_cdi_ieee_primary_10533202</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><ieee_id>10533202</ieee_id><sourcerecordid>3073299544</sourcerecordid><originalsourceid>FETCH-LOGICAL-c246t-9a7565079769eca4428c9f80e43301a6ce1f9a9b93e9cba6222175751abc14483</originalsourceid><addsrcrecordid>eNpNkE9Lw0AQxRdRsFY_gOAh4Dl1_2YzR61tbSl60IK3ZbrZQIomdTct9Nt3Q0rxNAPzmzdvHiH3jI4Yo_C0-Jy8jzjlciQE5IKyCzJgSuUp0zK_7HpBUyn09zW5CWFDKQOt9ICsFk1Vt8m83jsfqqZOmjKZedxX7SHBujj3sRaVi-Qrtpi8YHBFEumxb0JIz8PprrZtVLklVyX-BHd3qkOymk6-xm_p8mM2Hz8vU8tl1qaAWmWKatAZOItS8txCmVMnRfwAM-tYCQhrEA7sGjPOOYuuFcO1ZVLmYkgee92tb_52LrRm0-x8HU8aQbXgAErKSLGesp1b70qz9dUv-oNh1HTpmS4906VnTunFnYd-p3LO_eOVEJETRxlFajQ</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>3073299544</pqid></control><display><type>article</type><title>Joint Inversion of Gravity and Gravity Gradient Data Based on Cross-Gradient Function</title><source>IEEE Electronic Library (IEL)</source><creator>Qiao, Zhong-Kun ; Zhang, Zong-Yu ; Hu, Ruo ; Shen, Zheng-Hao ; Yuan, Peng ; Zhou, Hang ; Huang, Xin-Yi ; Zhou, Fei ; Shi, Hui-Yan ; Wu, Xue-Min ; Wu, Bin ; Wang, Xiao-Long ; Lin, Qiang</creator><creatorcontrib>Qiao, Zhong-Kun ; Zhang, Zong-Yu ; Hu, Ruo ; Shen, Zheng-Hao ; Yuan, Peng ; Zhou, Hang ; Huang, Xin-Yi ; Zhou, Fei ; Shi, Hui-Yan ; Wu, Xue-Min ; Wu, Bin ; Wang, Xiao-Long ; Lin, Qiang</creatorcontrib><description><![CDATA[Gravity exploration is one of the most commonly used geophysical exploration methods, and it is widely used in the field of mineral resources' exploration and engineering survey benefited from its advantages of large exploration depth, economy, and high efficiency. Gravity and its gradient data reflect the different distribution characteristics of subsurface anomalous objects, and therefore, the single data inversion cannot achieve an accurate identification for the underground objects and suffer from stronger nonuniqueness problems. To accurately identify the location and distribution characteristics of subsurface objects, we first construct models to perform separate inversions of gravity and gravity gradient data, analyze the identification ability of different anomaly components, and then innovatively introduce a cross-gradient function for the joint inversion of two gravity tensor data, <inline-formula> <tex-math notation="LaTeX">{V}_{ {xx}} </tex-math></inline-formula> and <inline-formula> <tex-math notation="LaTeX">{V}_{ {yy}} </tex-math></inline-formula>. The results show that the method combines the advantages of these two components and reflects the horizontal position of the targeted bodies more accurately; meanwhile, the portrayal of the boundary is also closer to the real model. Finally, we apply the above method to the Vinton Dome, and the inversion results recover the accurate spatial location of the Vinton Dome. The practical application results show that the joint cross-gradient inversion of gravity and gravity gradient data is more efficient for spatial location trapping and boundary inscription of subsurface targeted bodies compared with the inversion of individual component.]]></description><identifier>ISSN: 1530-437X</identifier><identifier>EISSN: 1558-1748</identifier><identifier>DOI: 10.1109/JSEN.2024.3398301</identifier><identifier>CODEN: ISJEAZ</identifier><language>eng</language><publisher>New York: IEEE</publisher><subject>Accelerometers ; Cross-gradient function ; Domes ; Geologic measurements ; Geophysical measurements ; Geophysical methods ; Gravity ; gravity and gradient data ; Horizontal orientation ; Instruments ; Inversions ; joint inversion ; Mineral resources ; Sensors ; Tensors ; Vinton Dome</subject><ispartof>IEEE sensors journal, 2024-07, Vol.24 (13), p.20940-20948</ispartof><rights>Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2024</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c246t-9a7565079769eca4428c9f80e43301a6ce1f9a9b93e9cba6222175751abc14483</cites><orcidid>0000-0003-4837-2586 ; 0000-0002-5073-1085 ; 0009-0008-4802-3443 ; 0000-0001-9111-609X ; 0000-0001-8424-6654 ; 0000-0002-7074-0050</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/10533202$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>314,776,780,792,27901,27902,54733</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/10533202$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Qiao, Zhong-Kun</creatorcontrib><creatorcontrib>Zhang, Zong-Yu</creatorcontrib><creatorcontrib>Hu, Ruo</creatorcontrib><creatorcontrib>Shen, Zheng-Hao</creatorcontrib><creatorcontrib>Yuan, Peng</creatorcontrib><creatorcontrib>Zhou, Hang</creatorcontrib><creatorcontrib>Huang, Xin-Yi</creatorcontrib><creatorcontrib>Zhou, Fei</creatorcontrib><creatorcontrib>Shi, Hui-Yan</creatorcontrib><creatorcontrib>Wu, Xue-Min</creatorcontrib><creatorcontrib>Wu, Bin</creatorcontrib><creatorcontrib>Wang, Xiao-Long</creatorcontrib><creatorcontrib>Lin, Qiang</creatorcontrib><title>Joint Inversion of Gravity and Gravity Gradient Data Based on Cross-Gradient Function</title><title>IEEE sensors journal</title><addtitle>JSEN</addtitle><description><![CDATA[Gravity exploration is one of the most commonly used geophysical exploration methods, and it is widely used in the field of mineral resources' exploration and engineering survey benefited from its advantages of large exploration depth, economy, and high efficiency. Gravity and its gradient data reflect the different distribution characteristics of subsurface anomalous objects, and therefore, the single data inversion cannot achieve an accurate identification for the underground objects and suffer from stronger nonuniqueness problems. To accurately identify the location and distribution characteristics of subsurface objects, we first construct models to perform separate inversions of gravity and gravity gradient data, analyze the identification ability of different anomaly components, and then innovatively introduce a cross-gradient function for the joint inversion of two gravity tensor data, <inline-formula> <tex-math notation="LaTeX">{V}_{ {xx}} </tex-math></inline-formula> and <inline-formula> <tex-math notation="LaTeX">{V}_{ {yy}} </tex-math></inline-formula>. The results show that the method combines the advantages of these two components and reflects the horizontal position of the targeted bodies more accurately; meanwhile, the portrayal of the boundary is also closer to the real model. Finally, we apply the above method to the Vinton Dome, and the inversion results recover the accurate spatial location of the Vinton Dome. The practical application results show that the joint cross-gradient inversion of gravity and gravity gradient data is more efficient for spatial location trapping and boundary inscription of subsurface targeted bodies compared with the inversion of individual component.]]></description><subject>Accelerometers</subject><subject>Cross-gradient function</subject><subject>Domes</subject><subject>Geologic measurements</subject><subject>Geophysical measurements</subject><subject>Geophysical methods</subject><subject>Gravity</subject><subject>gravity and gradient data</subject><subject>Horizontal orientation</subject><subject>Instruments</subject><subject>Inversions</subject><subject>joint inversion</subject><subject>Mineral resources</subject><subject>Sensors</subject><subject>Tensors</subject><subject>Vinton Dome</subject><issn>1530-437X</issn><issn>1558-1748</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2024</creationdate><recordtype>article</recordtype><sourceid>RIE</sourceid><recordid>eNpNkE9Lw0AQxRdRsFY_gOAh4Dl1_2YzR61tbSl60IK3ZbrZQIomdTct9Nt3Q0rxNAPzmzdvHiH3jI4Yo_C0-Jy8jzjlciQE5IKyCzJgSuUp0zK_7HpBUyn09zW5CWFDKQOt9ICsFk1Vt8m83jsfqqZOmjKZedxX7SHBujj3sRaVi-Qrtpi8YHBFEumxb0JIz8PprrZtVLklVyX-BHd3qkOymk6-xm_p8mM2Hz8vU8tl1qaAWmWKatAZOItS8txCmVMnRfwAM-tYCQhrEA7sGjPOOYuuFcO1ZVLmYkgee92tb_52LrRm0-x8HU8aQbXgAErKSLGesp1b70qz9dUv-oNh1HTpmS4906VnTunFnYd-p3LO_eOVEJETRxlFajQ</recordid><startdate>20240701</startdate><enddate>20240701</enddate><creator>Qiao, Zhong-Kun</creator><creator>Zhang, Zong-Yu</creator><creator>Hu, Ruo</creator><creator>Shen, Zheng-Hao</creator><creator>Yuan, Peng</creator><creator>Zhou, Hang</creator><creator>Huang, Xin-Yi</creator><creator>Zhou, Fei</creator><creator>Shi, Hui-Yan</creator><creator>Wu, Xue-Min</creator><creator>Wu, Bin</creator><creator>Wang, Xiao-Long</creator><creator>Lin, Qiang</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>7SP</scope><scope>7U5</scope><scope>8FD</scope><scope>L7M</scope><orcidid>https://orcid.org/0000-0003-4837-2586</orcidid><orcidid>https://orcid.org/0000-0002-5073-1085</orcidid><orcidid>https://orcid.org/0009-0008-4802-3443</orcidid><orcidid>https://orcid.org/0000-0001-9111-609X</orcidid><orcidid>https://orcid.org/0000-0001-8424-6654</orcidid><orcidid>https://orcid.org/0000-0002-7074-0050</orcidid></search><sort><creationdate>20240701</creationdate><title>Joint Inversion of Gravity and Gravity Gradient Data Based on Cross-Gradient Function</title><author>Qiao, Zhong-Kun ; Zhang, Zong-Yu ; Hu, Ruo ; Shen, Zheng-Hao ; Yuan, Peng ; Zhou, Hang ; Huang, Xin-Yi ; Zhou, Fei ; Shi, Hui-Yan ; Wu, Xue-Min ; Wu, Bin ; Wang, Xiao-Long ; Lin, Qiang</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c246t-9a7565079769eca4428c9f80e43301a6ce1f9a9b93e9cba6222175751abc14483</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2024</creationdate><topic>Accelerometers</topic><topic>Cross-gradient function</topic><topic>Domes</topic><topic>Geologic measurements</topic><topic>Geophysical measurements</topic><topic>Geophysical methods</topic><topic>Gravity</topic><topic>gravity and gradient data</topic><topic>Horizontal orientation</topic><topic>Instruments</topic><topic>Inversions</topic><topic>joint inversion</topic><topic>Mineral resources</topic><topic>Sensors</topic><topic>Tensors</topic><topic>Vinton Dome</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Qiao, Zhong-Kun</creatorcontrib><creatorcontrib>Zhang, Zong-Yu</creatorcontrib><creatorcontrib>Hu, Ruo</creatorcontrib><creatorcontrib>Shen, Zheng-Hao</creatorcontrib><creatorcontrib>Yuan, Peng</creatorcontrib><creatorcontrib>Zhou, Hang</creatorcontrib><creatorcontrib>Huang, Xin-Yi</creatorcontrib><creatorcontrib>Zhou, Fei</creatorcontrib><creatorcontrib>Shi, Hui-Yan</creatorcontrib><creatorcontrib>Wu, Xue-Min</creatorcontrib><creatorcontrib>Wu, Bin</creatorcontrib><creatorcontrib>Wang, Xiao-Long</creatorcontrib><creatorcontrib>Lin, Qiang</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>Electronics &amp; Communications Abstracts</collection><collection>Solid State and Superconductivity Abstracts</collection><collection>Technology Research Database</collection><collection>Advanced Technologies Database with Aerospace</collection><jtitle>IEEE sensors journal</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Qiao, Zhong-Kun</au><au>Zhang, Zong-Yu</au><au>Hu, Ruo</au><au>Shen, Zheng-Hao</au><au>Yuan, Peng</au><au>Zhou, Hang</au><au>Huang, Xin-Yi</au><au>Zhou, Fei</au><au>Shi, Hui-Yan</au><au>Wu, Xue-Min</au><au>Wu, Bin</au><au>Wang, Xiao-Long</au><au>Lin, Qiang</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Joint Inversion of Gravity and Gravity Gradient Data Based on Cross-Gradient Function</atitle><jtitle>IEEE sensors journal</jtitle><stitle>JSEN</stitle><date>2024-07-01</date><risdate>2024</risdate><volume>24</volume><issue>13</issue><spage>20940</spage><epage>20948</epage><pages>20940-20948</pages><issn>1530-437X</issn><eissn>1558-1748</eissn><coden>ISJEAZ</coden><abstract><![CDATA[Gravity exploration is one of the most commonly used geophysical exploration methods, and it is widely used in the field of mineral resources' exploration and engineering survey benefited from its advantages of large exploration depth, economy, and high efficiency. Gravity and its gradient data reflect the different distribution characteristics of subsurface anomalous objects, and therefore, the single data inversion cannot achieve an accurate identification for the underground objects and suffer from stronger nonuniqueness problems. To accurately identify the location and distribution characteristics of subsurface objects, we first construct models to perform separate inversions of gravity and gravity gradient data, analyze the identification ability of different anomaly components, and then innovatively introduce a cross-gradient function for the joint inversion of two gravity tensor data, <inline-formula> <tex-math notation="LaTeX">{V}_{ {xx}} </tex-math></inline-formula> and <inline-formula> <tex-math notation="LaTeX">{V}_{ {yy}} </tex-math></inline-formula>. The results show that the method combines the advantages of these two components and reflects the horizontal position of the targeted bodies more accurately; meanwhile, the portrayal of the boundary is also closer to the real model. Finally, we apply the above method to the Vinton Dome, and the inversion results recover the accurate spatial location of the Vinton Dome. The practical application results show that the joint cross-gradient inversion of gravity and gravity gradient data is more efficient for spatial location trapping and boundary inscription of subsurface targeted bodies compared with the inversion of individual component.]]></abstract><cop>New York</cop><pub>IEEE</pub><doi>10.1109/JSEN.2024.3398301</doi><tpages>9</tpages><orcidid>https://orcid.org/0000-0003-4837-2586</orcidid><orcidid>https://orcid.org/0000-0002-5073-1085</orcidid><orcidid>https://orcid.org/0009-0008-4802-3443</orcidid><orcidid>https://orcid.org/0000-0001-9111-609X</orcidid><orcidid>https://orcid.org/0000-0001-8424-6654</orcidid><orcidid>https://orcid.org/0000-0002-7074-0050</orcidid></addata></record>
fulltext fulltext_linktorsrc
identifier ISSN: 1530-437X
ispartof IEEE sensors journal, 2024-07, Vol.24 (13), p.20940-20948
issn 1530-437X
1558-1748
language eng
recordid cdi_ieee_primary_10533202
source IEEE Electronic Library (IEL)
subjects Accelerometers
Cross-gradient function
Domes
Geologic measurements
Geophysical measurements
Geophysical methods
Gravity
gravity and gradient data
Horizontal orientation
Instruments
Inversions
joint inversion
Mineral resources
Sensors
Tensors
Vinton Dome
title Joint Inversion of Gravity and Gravity Gradient Data Based on Cross-Gradient Function
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-02-10T19%3A03%3A03IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_RIE&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Joint%20Inversion%20of%20Gravity%20and%20Gravity%20Gradient%20Data%20Based%20on%20Cross-Gradient%20Function&rft.jtitle=IEEE%20sensors%20journal&rft.au=Qiao,%20Zhong-Kun&rft.date=2024-07-01&rft.volume=24&rft.issue=13&rft.spage=20940&rft.epage=20948&rft.pages=20940-20948&rft.issn=1530-437X&rft.eissn=1558-1748&rft.coden=ISJEAZ&rft_id=info:doi/10.1109/JSEN.2024.3398301&rft_dat=%3Cproquest_RIE%3E3073299544%3C/proquest_RIE%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=3073299544&rft_id=info:pmid/&rft_ieee_id=10533202&rfr_iscdi=true