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...
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Online Access: | http://dx.doi.org/10.3389/feart.2023.1127597 https://www.frontiersin.org/articles/10.3389/feart.2023.1127597/full |
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crfrontiers:10.3389/feart.2023.1127597 2024-09-15T17:57:56+00:00 Probabilistic approach to Gramian inversion of multiphysics data Zhdanov, Michael S. Jorgensen, Michael Tao, Mo 2023 http://dx.doi.org/10.3389/feart.2023.1127597 https://www.frontiersin.org/articles/10.3389/feart.2023.1127597/full unknown Frontiers Media SA https://creativecommons.org/licenses/by/4.0/ Frontiers in Earth Science volume 11 ISSN 2296-6463 journal-article 2023 crfrontiers https://doi.org/10.3389/feart.2023.1127597 2024-07-30T04:05:33Z 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. Article in Journal/Newspaper Barents Sea Nordkapp Nordkapp Basin Frontiers (Publisher) Frontiers in Earth Science 11 |
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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. |
format |
Article in Journal/Newspaper |
author |
Zhdanov, Michael S. Jorgensen, Michael Tao, Mo |
spellingShingle |
Zhdanov, Michael S. Jorgensen, Michael Tao, Mo Probabilistic approach to Gramian inversion of multiphysics data |
author_facet |
Zhdanov, Michael S. Jorgensen, Michael Tao, Mo |
author_sort |
Zhdanov, Michael S. |
title |
Probabilistic approach to Gramian inversion of multiphysics data |
title_short |
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_sort |
probabilistic approach to gramian inversion of multiphysics data |
publisher |
Frontiers Media SA |
publishDate |
2023 |
url |
http://dx.doi.org/10.3389/feart.2023.1127597 https://www.frontiersin.org/articles/10.3389/feart.2023.1127597/full |
genre |
Barents Sea Nordkapp Nordkapp Basin |
genre_facet |
Barents Sea Nordkapp Nordkapp Basin |
op_source |
Frontiers in Earth Science volume 11 ISSN 2296-6463 |
op_rights |
https://creativecommons.org/licenses/by/4.0/ |
op_doi |
https://doi.org/10.3389/feart.2023.1127597 |
container_title |
Frontiers in Earth Science |
container_volume |
11 |
_version_ |
1810434158183317504 |