Gravity Data Inversion with Method of Local Corrections for Finite Elements Models

We present a new method for gravity data inversion for the linear problem (reconstruction of density distribution by given gravity field). This is an iteration algorithm based on the ideas of local minimization (also known as local corrections method). Unlike the gradient methods, it does not requir...

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Published in:Geosciences
Main Authors: Petr S. Martyshko, Igor V. Ladovskii, Denis D. Byzov, Alexander G. Tsidaev
Format: Article in Journal/Newspaper
Language:English
Published: MDPI AG 2018
Subjects:
Online Access:https://doi.org/10.3390/geosciences8100373
https://doaj.org/article/5b2c8622d7fc4a49977b8218ea4d657d
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spelling ftdoajarticles:oai:doaj.org/article:5b2c8622d7fc4a49977b8218ea4d657d 2023-05-15T17:55:00+02:00 Gravity Data Inversion with Method of Local Corrections for Finite Elements Models Petr S. Martyshko Igor V. Ladovskii Denis D. Byzov Alexander G. Tsidaev 2018-10-01T00:00:00Z https://doi.org/10.3390/geosciences8100373 https://doaj.org/article/5b2c8622d7fc4a49977b8218ea4d657d EN eng MDPI AG http://www.mdpi.com/2076-3263/8/10/373 https://doaj.org/toc/2076-3263 2076-3263 doi:10.3390/geosciences8100373 https://doaj.org/article/5b2c8622d7fc4a49977b8218ea4d657d Geosciences, Vol 8, Iss 10, p 373 (2018) inverse problem 3D density model joint interpretation Geology QE1-996.5 article 2018 ftdoajarticles https://doi.org/10.3390/geosciences8100373 2022-12-31T12:45:50Z We present a new method for gravity data inversion for the linear problem (reconstruction of density distribution by given gravity field). This is an iteration algorithm based on the ideas of local minimization (also known as local corrections method). Unlike the gradient methods, it does not require a nonlinear minimization, is easier to implement and has better stability. The algorithm is based on the finite element method. The finite element approach in our study means that the medium (part of a lithosphere) is represented as a set of equal rectangular prisms, each with constant density. We also suggest a time-efficient optimization, which speeds up the inversion process. This optimization is applied on the gravity field calculation stage, which is a part of every inversion iteration. Its idea is to replace multiple calculations of the gravity field for all finite elements in all observation points with a pre-calculated set of uniform fields for all distances between finite element and observation point, which is possible for the current data set. Method is demonstrated on synthetic data and real-world cases. The case study area is located on the Timan-Pechora plate. This region is one of the promising oil- and gas-producing areas in Russia. Note that in this case we create a 3D density model using joint interpretation of seismic and gravity data. Article in Journal/Newspaper Pechora Directory of Open Access Journals: DOAJ Articles Geosciences 8 10 373
institution Open Polar
collection Directory of Open Access Journals: DOAJ Articles
op_collection_id ftdoajarticles
language English
topic inverse problem
3D density model
joint interpretation
Geology
QE1-996.5
spellingShingle inverse problem
3D density model
joint interpretation
Geology
QE1-996.5
Petr S. Martyshko
Igor V. Ladovskii
Denis D. Byzov
Alexander G. Tsidaev
Gravity Data Inversion with Method of Local Corrections for Finite Elements Models
topic_facet inverse problem
3D density model
joint interpretation
Geology
QE1-996.5
description We present a new method for gravity data inversion for the linear problem (reconstruction of density distribution by given gravity field). This is an iteration algorithm based on the ideas of local minimization (also known as local corrections method). Unlike the gradient methods, it does not require a nonlinear minimization, is easier to implement and has better stability. The algorithm is based on the finite element method. The finite element approach in our study means that the medium (part of a lithosphere) is represented as a set of equal rectangular prisms, each with constant density. We also suggest a time-efficient optimization, which speeds up the inversion process. This optimization is applied on the gravity field calculation stage, which is a part of every inversion iteration. Its idea is to replace multiple calculations of the gravity field for all finite elements in all observation points with a pre-calculated set of uniform fields for all distances between finite element and observation point, which is possible for the current data set. Method is demonstrated on synthetic data and real-world cases. The case study area is located on the Timan-Pechora plate. This region is one of the promising oil- and gas-producing areas in Russia. Note that in this case we create a 3D density model using joint interpretation of seismic and gravity data.
format Article in Journal/Newspaper
author Petr S. Martyshko
Igor V. Ladovskii
Denis D. Byzov
Alexander G. Tsidaev
author_facet Petr S. Martyshko
Igor V. Ladovskii
Denis D. Byzov
Alexander G. Tsidaev
author_sort Petr S. Martyshko
title Gravity Data Inversion with Method of Local Corrections for Finite Elements Models
title_short Gravity Data Inversion with Method of Local Corrections for Finite Elements Models
title_full Gravity Data Inversion with Method of Local Corrections for Finite Elements Models
title_fullStr Gravity Data Inversion with Method of Local Corrections for Finite Elements Models
title_full_unstemmed Gravity Data Inversion with Method of Local Corrections for Finite Elements Models
title_sort gravity data inversion with method of local corrections for finite elements models
publisher MDPI AG
publishDate 2018
url https://doi.org/10.3390/geosciences8100373
https://doaj.org/article/5b2c8622d7fc4a49977b8218ea4d657d
genre Pechora
genre_facet Pechora
op_source Geosciences, Vol 8, Iss 10, p 373 (2018)
op_relation http://www.mdpi.com/2076-3263/8/10/373
https://doaj.org/toc/2076-3263
2076-3263
doi:10.3390/geosciences8100373
https://doaj.org/article/5b2c8622d7fc4a49977b8218ea4d657d
op_doi https://doi.org/10.3390/geosciences8100373
container_title Geosciences
container_volume 8
container_issue 10
container_start_page 373
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