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An objective function for full-waveform inversion based on frequency-dependent offset-preconditioning

Full-waveform inversion (FWI) is a powerful technique to obtain high-resolution subsurface models, from seismic data. However, FWI is an ill-posed problem, which means that the solution is not unique, and therefore the expert use of the information is required to mitigate the FWI ill-posedness, espe...

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Autores principales: da Silva, Sérgio Luiz E. F., Carvalho, Pedro T. C., da Costa, Carlos A. N., de Araújo, João M., Corso, Gilberto
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7592739/
https://www.ncbi.nlm.nih.gov/pubmed/33112904
http://dx.doi.org/10.1371/journal.pone.0240999
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author da Silva, Sérgio Luiz E. F.
Carvalho, Pedro T. C.
da Costa, Carlos A. N.
de Araújo, João M.
Corso, Gilberto
author_facet da Silva, Sérgio Luiz E. F.
Carvalho, Pedro T. C.
da Costa, Carlos A. N.
de Araújo, João M.
Corso, Gilberto
author_sort da Silva, Sérgio Luiz E. F.
collection PubMed
description Full-waveform inversion (FWI) is a powerful technique to obtain high-resolution subsurface models, from seismic data. However, FWI is an ill-posed problem, which means that the solution is not unique, and therefore the expert use of the information is required to mitigate the FWI ill-posedness, especially when wide-aperture seismic acquisitions are considered. In this way, we investigate the multiscale frequency-domain FWI by using a weighting operator according to the distances between each source-receiver pair. In this work, we propose a weighting operator that acts on the data misfit as preconditioning of the objective function that depends on the source-receiver distance (offset) and the frequency used during the inversion. The proposed operator emphasizes information from long offsets, especially at low frequencies, and as a consequence improves the update of deep geological structures. To demonstrate the effectiveness of our proposal, we perform numerical simulations on 2D acoustic Marmousi2 case study, which is widely used in seismic imaging tests, considering three different scenarios. In the first two ones, we have used an acquisition geometry with a maximum offset of 4 and 8 km, respectively. In the last one, we have considered all-offsets. The results show that our proposal outperforms similar strategies, for all scenarios, providing more reliable quantitative subsurface models. In fact, our inversion result has the lowest error and the highest similarity to the true model than similar approaches.
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spelling pubmed-75927392020-11-02 An objective function for full-waveform inversion based on frequency-dependent offset-preconditioning da Silva, Sérgio Luiz E. F. Carvalho, Pedro T. C. da Costa, Carlos A. N. de Araújo, João M. Corso, Gilberto PLoS One Research Article Full-waveform inversion (FWI) is a powerful technique to obtain high-resolution subsurface models, from seismic data. However, FWI is an ill-posed problem, which means that the solution is not unique, and therefore the expert use of the information is required to mitigate the FWI ill-posedness, especially when wide-aperture seismic acquisitions are considered. In this way, we investigate the multiscale frequency-domain FWI by using a weighting operator according to the distances between each source-receiver pair. In this work, we propose a weighting operator that acts on the data misfit as preconditioning of the objective function that depends on the source-receiver distance (offset) and the frequency used during the inversion. The proposed operator emphasizes information from long offsets, especially at low frequencies, and as a consequence improves the update of deep geological structures. To demonstrate the effectiveness of our proposal, we perform numerical simulations on 2D acoustic Marmousi2 case study, which is widely used in seismic imaging tests, considering three different scenarios. In the first two ones, we have used an acquisition geometry with a maximum offset of 4 and 8 km, respectively. In the last one, we have considered all-offsets. The results show that our proposal outperforms similar strategies, for all scenarios, providing more reliable quantitative subsurface models. In fact, our inversion result has the lowest error and the highest similarity to the true model than similar approaches. Public Library of Science 2020-10-28 /pmc/articles/PMC7592739/ /pubmed/33112904 http://dx.doi.org/10.1371/journal.pone.0240999 Text en © 2020 da Silva et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
da Silva, Sérgio Luiz E. F.
Carvalho, Pedro T. C.
da Costa, Carlos A. N.
de Araújo, João M.
Corso, Gilberto
An objective function for full-waveform inversion based on frequency-dependent offset-preconditioning
title An objective function for full-waveform inversion based on frequency-dependent offset-preconditioning
title_full An objective function for full-waveform inversion based on frequency-dependent offset-preconditioning
title_fullStr An objective function for full-waveform inversion based on frequency-dependent offset-preconditioning
title_full_unstemmed An objective function for full-waveform inversion based on frequency-dependent offset-preconditioning
title_short An objective function for full-waveform inversion based on frequency-dependent offset-preconditioning
title_sort objective function for full-waveform inversion based on frequency-dependent offset-preconditioning
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7592739/
https://www.ncbi.nlm.nih.gov/pubmed/33112904
http://dx.doi.org/10.1371/journal.pone.0240999
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