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...
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Veröffentlicht in: | IEEE sensors journal 2024-07, Vol.24 (13), p.20940-20948 |
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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 |
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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 & 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> |
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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 |
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