Using non-diagonal data covariances in geophysical inversion

SUMMARY We present a new approach that allows for the inversion of quantities derived from the observed data using non-diagonal data covariance matrices. For example, we can invert approximations of apparent resistivity and phase instead of magnetotelluric impedance using this methodology. Compared...

Full description

Saved in:
Bibliographic Details
Published in:Geophysical journal international 2020-08, Vol.222 (2), p.1023-1033
Main Authors: Moorkamp, Max, Avdeeva, Anna
Format: Article
Language:English
Citations: Items that this one cites
Online Access:Request full text
Tags: Add Tag
No Tags, Be the first to tag this record!
cited_by
cites cdi_FETCH-LOGICAL-c259t-7a41596a95196a37abf2bc81abb23d4ffe44addfa15e4da7b98554d8c6cde4f63
container_end_page 1033
container_issue 2
container_start_page 1023
container_title Geophysical journal international
container_volume 222
creator Moorkamp, Max
Avdeeva, Anna
description SUMMARY We present a new approach that allows for the inversion of quantities derived from the observed data using non-diagonal data covariance matrices. For example, we can invert approximations of apparent resistivity and phase instead of magnetotelluric impedance using this methodology. Compared to the direct inversion of these derived quantities, the proposed methodology has two advantages: (i) If an inversion algorithm allows for the specification of a full data covariance matrix, users can invert for arbitrary derived quantities by specifying the appropriate covariance matrix instead of having to rely on the inversion code to have implemented this feature. (ii) It is fully compatible with the assumptions of least-squares optimization and thus avoids potential issues with bias when inverting quantities that are nonlinear functions of the original data, We discuss the theory of this approach and show an example using magnetotelluric data. However, the same method can be applied to other types of geophysical data, for example gravity gradient measurements.
doi_str_mv 10.1093/gji/ggaa235
format article
fullrecord <record><control><sourceid>oup_TOX</sourceid><recordid>TN_cdi_crossref_primary_10_1093_gji_ggaa235</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><oup_id>10.1093/gji/ggaa235</oup_id><sourcerecordid>10.1093/gji/ggaa235</sourcerecordid><originalsourceid>FETCH-LOGICAL-c259t-7a41596a95196a37abf2bc81abb23d4ffe44addfa15e4da7b98554d8c6cde4f63</originalsourceid><addsrcrecordid>eNp9j0tLAzEYRYMoOFZX_oFZuZHYZPKYCbiR4gsKbix0N3yTlyk1GZJa6L93pF27uXdxDxcOQreUPFCi2Nxvwtx7gIaJM1RRJgVuuFyfo4ooIbHgZH2JrkrZEEI55V2FHlclRF_HFLEJ4FOEbW1gB7VOe8gBoralDrH2No1fhxL0tIe4t7mEFK_RhYNtsTennqHVy_Pn4g0vP17fF09LrBuhdrgFToWSoASdkrUwuGbQHYVhaJjhzlnOwRgHVFhuoB1UJwQ3nZbaWO4km6H746_OqZRsXT_m8A350FPS_4n3k3h_Ep_ouyOdfsZ_wV9_eFuZ</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype></control><display><type>article</type><title>Using non-diagonal data covariances in geophysical inversion</title><source>Oxford Journals Open Access Collection</source><creator>Moorkamp, Max ; Avdeeva, Anna</creator><creatorcontrib>Moorkamp, Max ; Avdeeva, Anna</creatorcontrib><description>SUMMARY We present a new approach that allows for the inversion of quantities derived from the observed data using non-diagonal data covariance matrices. For example, we can invert approximations of apparent resistivity and phase instead of magnetotelluric impedance using this methodology. Compared to the direct inversion of these derived quantities, the proposed methodology has two advantages: (i) If an inversion algorithm allows for the specification of a full data covariance matrix, users can invert for arbitrary derived quantities by specifying the appropriate covariance matrix instead of having to rely on the inversion code to have implemented this feature. (ii) It is fully compatible with the assumptions of least-squares optimization and thus avoids potential issues with bias when inverting quantities that are nonlinear functions of the original data, We discuss the theory of this approach and show an example using magnetotelluric data. However, the same method can be applied to other types of geophysical data, for example gravity gradient measurements.</description><identifier>ISSN: 0956-540X</identifier><identifier>EISSN: 1365-246X</identifier><identifier>DOI: 10.1093/gji/ggaa235</identifier><language>eng</language><publisher>Oxford University Press</publisher><ispartof>Geophysical journal international, 2020-08, Vol.222 (2), p.1023-1033</ispartof><rights>The Author(s) 2020. Published by Oxford University Press on behalf of The Royal Astronomical Society. 2020</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c259t-7a41596a95196a37abf2bc81abb23d4ffe44addfa15e4da7b98554d8c6cde4f63</cites><orcidid>0000-0002-7879-1346</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,1604,27924,27925</link.rule.ids><linktorsrc>$$Uhttps://dx.doi.org/10.1093/gji/ggaa235$$EView_record_in_Oxford_University_Press$$FView_record_in_$$GOxford_University_Press</linktorsrc></links><search><creatorcontrib>Moorkamp, Max</creatorcontrib><creatorcontrib>Avdeeva, Anna</creatorcontrib><title>Using non-diagonal data covariances in geophysical inversion</title><title>Geophysical journal international</title><description>SUMMARY We present a new approach that allows for the inversion of quantities derived from the observed data using non-diagonal data covariance matrices. For example, we can invert approximations of apparent resistivity and phase instead of magnetotelluric impedance using this methodology. Compared to the direct inversion of these derived quantities, the proposed methodology has two advantages: (i) If an inversion algorithm allows for the specification of a full data covariance matrix, users can invert for arbitrary derived quantities by specifying the appropriate covariance matrix instead of having to rely on the inversion code to have implemented this feature. (ii) It is fully compatible with the assumptions of least-squares optimization and thus avoids potential issues with bias when inverting quantities that are nonlinear functions of the original data, We discuss the theory of this approach and show an example using magnetotelluric data. However, the same method can be applied to other types of geophysical data, for example gravity gradient measurements.</description><issn>0956-540X</issn><issn>1365-246X</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2020</creationdate><recordtype>article</recordtype><recordid>eNp9j0tLAzEYRYMoOFZX_oFZuZHYZPKYCbiR4gsKbix0N3yTlyk1GZJa6L93pF27uXdxDxcOQreUPFCi2Nxvwtx7gIaJM1RRJgVuuFyfo4ooIbHgZH2JrkrZEEI55V2FHlclRF_HFLEJ4FOEbW1gB7VOe8gBoralDrH2No1fhxL0tIe4t7mEFK_RhYNtsTennqHVy_Pn4g0vP17fF09LrBuhdrgFToWSoASdkrUwuGbQHYVhaJjhzlnOwRgHVFhuoB1UJwQ3nZbaWO4km6H746_OqZRsXT_m8A350FPS_4n3k3h_Ep_ouyOdfsZ_wV9_eFuZ</recordid><startdate>20200801</startdate><enddate>20200801</enddate><creator>Moorkamp, Max</creator><creator>Avdeeva, Anna</creator><general>Oxford University Press</general><scope>AAYXX</scope><scope>CITATION</scope><orcidid>https://orcid.org/0000-0002-7879-1346</orcidid></search><sort><creationdate>20200801</creationdate><title>Using non-diagonal data covariances in geophysical inversion</title><author>Moorkamp, Max ; Avdeeva, Anna</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c259t-7a41596a95196a37abf2bc81abb23d4ffe44addfa15e4da7b98554d8c6cde4f63</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2020</creationdate><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Moorkamp, Max</creatorcontrib><creatorcontrib>Avdeeva, Anna</creatorcontrib><collection>CrossRef</collection><jtitle>Geophysical journal international</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Moorkamp, Max</au><au>Avdeeva, Anna</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Using non-diagonal data covariances in geophysical inversion</atitle><jtitle>Geophysical journal international</jtitle><date>2020-08-01</date><risdate>2020</risdate><volume>222</volume><issue>2</issue><spage>1023</spage><epage>1033</epage><pages>1023-1033</pages><issn>0956-540X</issn><eissn>1365-246X</eissn><abstract>SUMMARY We present a new approach that allows for the inversion of quantities derived from the observed data using non-diagonal data covariance matrices. For example, we can invert approximations of apparent resistivity and phase instead of magnetotelluric impedance using this methodology. Compared to the direct inversion of these derived quantities, the proposed methodology has two advantages: (i) If an inversion algorithm allows for the specification of a full data covariance matrix, users can invert for arbitrary derived quantities by specifying the appropriate covariance matrix instead of having to rely on the inversion code to have implemented this feature. (ii) It is fully compatible with the assumptions of least-squares optimization and thus avoids potential issues with bias when inverting quantities that are nonlinear functions of the original data, We discuss the theory of this approach and show an example using magnetotelluric data. However, the same method can be applied to other types of geophysical data, for example gravity gradient measurements.</abstract><pub>Oxford University Press</pub><doi>10.1093/gji/ggaa235</doi><tpages>11</tpages><orcidid>https://orcid.org/0000-0002-7879-1346</orcidid><oa>free_for_read</oa></addata></record>
fulltext fulltext_linktorsrc
identifier ISSN: 0956-540X
ispartof Geophysical journal international, 2020-08, Vol.222 (2), p.1023-1033
issn 0956-540X
1365-246X
language eng
recordid cdi_crossref_primary_10_1093_gji_ggaa235
source Oxford Journals Open Access Collection
title Using non-diagonal data covariances in geophysical inversion
url http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-02T22%3A05%3A03IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-oup_TOX&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Using%20non-diagonal%20data%20covariances%20in%20geophysical%20inversion&rft.jtitle=Geophysical%20journal%20international&rft.au=Moorkamp,%20Max&rft.date=2020-08-01&rft.volume=222&rft.issue=2&rft.spage=1023&rft.epage=1033&rft.pages=1023-1033&rft.issn=0956-540X&rft.eissn=1365-246X&rft_id=info:doi/10.1093/gji/ggaa235&rft_dat=%3Coup_TOX%3E10.1093/gji/ggaa235%3C/oup_TOX%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-c259t-7a41596a95196a37abf2bc81abb23d4ffe44addfa15e4da7b98554d8c6cde4f63%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_id=info:pmid/&rft_oup_id=10.1093/gji/ggaa235&rfr_iscdi=true