Probabilistic approach to Gramian inversion of multiphysics data
We consider a probabilistic approach to the joint inversion of multiphysics data based on Gramian constraints. The multiphysics geophysical survey represents the most effective technique for geophysical exploration because different physical data reflect distinct physical properties of the various c...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2023-02-01
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| Series: | Frontiers in Earth Science |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/articles/10.3389/feart.2023.1127597/full |
| _version_ | 1828003317742043136 |
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| author | Michael S. Zhdanov Michael Jorgensen Michael Jorgensen Mo Tao |
| author_facet | Michael S. Zhdanov Michael Jorgensen Michael Jorgensen Mo Tao |
| author_sort | Michael S. Zhdanov |
| collection | DOAJ |
| description | We consider a probabilistic approach to the joint inversion of multiphysics data based on Gramian constraints. The multiphysics geophysical survey represents the most effective technique for geophysical exploration because different physical data reflect distinct physical properties of the various components of the geological system. By joint inversion of the multiphysics data, one can produce enhanced subsurface images of the physical properties distribution, which improves our ability to explore natural resources. One powerful method of joint inversion is based on Gramian constraints. This technique enforces the relationships between different model parameters during the inversion process. We demonstrate that the Gramian can be interpreted as a determinant of the covariance matrix between different physical models representing the subsurface geology in the framework of the probabilistic approach to inversion theory. This interpretation opens the way to use all the power of the modern probability theory and statistics in developing novel methods for joint inversion of the multiphysics data. We apply the developed joint inversion methodology to inversion of gravity gradiometry and magnetic data in the Nordkapp Basin, Barents Sea to image salt diapirs. |
| first_indexed | 2024-04-10T06:56:44Z |
| format | Article |
| id | doaj.art-0d58a297340947058fb43a89625a0956 |
| institution | Directory Open Access Journal |
| issn | 2296-6463 |
| language | English |
| last_indexed | 2024-04-10T06:56:44Z |
| publishDate | 2023-02-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Earth Science |
| spelling | doaj.art-0d58a297340947058fb43a89625a09562023-02-28T07:06:11ZengFrontiers Media S.A.Frontiers in Earth Science2296-64632023-02-011110.3389/feart.2023.11275971127597Probabilistic approach to Gramian inversion of multiphysics dataMichael S. Zhdanov0Michael Jorgensen1Michael Jorgensen2Mo Tao3Consortium for Electromagnetic Modeling and Inversion, University of Utah, Salt LakeCity, UT, United StatesConsortium for Electromagnetic Modeling and Inversion, University of Utah, Salt LakeCity, UT, United StatesTechnoImaging, Salt LakeCity, UT, United StatesConsortium for Electromagnetic Modeling and Inversion, University of Utah, Salt LakeCity, UT, United StatesWe consider a probabilistic approach to the joint inversion of multiphysics data based on Gramian constraints. The multiphysics geophysical survey represents the most effective technique for geophysical exploration because different physical data reflect distinct physical properties of the various components of the geological system. By joint inversion of the multiphysics data, one can produce enhanced subsurface images of the physical properties distribution, which improves our ability to explore natural resources. One powerful method of joint inversion is based on Gramian constraints. This technique enforces the relationships between different model parameters during the inversion process. We demonstrate that the Gramian can be interpreted as a determinant of the covariance matrix between different physical models representing the subsurface geology in the framework of the probabilistic approach to inversion theory. This interpretation opens the way to use all the power of the modern probability theory and statistics in developing novel methods for joint inversion of the multiphysics data. We apply the developed joint inversion methodology to inversion of gravity gradiometry and magnetic data in the Nordkapp Basin, Barents Sea to image salt diapirs.https://www.frontiersin.org/articles/10.3389/feart.2023.1127597/full3Dinversionprobabilisticmultiphysicsgravitymagnetic |
| spellingShingle | Michael S. Zhdanov Michael Jorgensen Michael Jorgensen Mo Tao Probabilistic approach to Gramian inversion of multiphysics data Frontiers in Earth Science 3D inversion probabilistic multiphysics gravity magnetic |
| title | Probabilistic approach to Gramian inversion of multiphysics data |
| title_full | Probabilistic approach to Gramian inversion of multiphysics data |
| title_fullStr | Probabilistic approach to Gramian inversion of multiphysics data |
| title_full_unstemmed | Probabilistic approach to Gramian inversion of multiphysics data |
| title_short | Probabilistic approach to Gramian inversion of multiphysics data |
| title_sort | probabilistic approach to gramian inversion of multiphysics data |
| topic | 3D inversion probabilistic multiphysics gravity magnetic |
| url | https://www.frontiersin.org/articles/10.3389/feart.2023.1127597/full |
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