Physically Constrained 2D Joint Inversion of Surface and Body Wave Tomography

Journal Article (2022)
Author(s)

Mohammadkarim Karimpour (Politecnico di Torino)

Evert Slob (TU Delft - Applied Geophysics and Petrophysics)

Laura Valentina Socco (Politecnico di Torino)

Research Group
Applied Geophysics and Petrophysics
Copyright
© 2022 Mohammadkarim Karimpour, E.C. Slob, Laura Valentina Socco
DOI related publication
https://doi.org/10.32389/JEEG21-031
More Info
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Publication Year
2022
Language
English
Copyright
© 2022 Mohammadkarim Karimpour, E.C. Slob, Laura Valentina Socco
Research Group
Applied Geophysics and Petrophysics
Bibliographical Note
Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.@en
Issue number
2
Volume number
27
Pages (from-to)
57-71
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Abstract

Joint inversion of different geophysical methods is a powerful tool to overcome the limitations of individual inversions. Body wave tomography is used to obtain P-wave velocity models by inversion of P-wave travel times. Surface wave tomography is used to obtain S-wave velocity models through inversion of the dispersion curves data. Both methods have inherent limitations. We focus on the joint body and surface waves tomography inversion to reduce the limitations of each individual inversion. In our joint inversion scheme, the Poisson ratio was used as the link between P-wave and S-wave velocities, and the same geometry was imposed on the final velocity models. The joint inversion algorithm was applied to a 2D synthetic dataset and then to two 2D field datasets. We compare the obtained velocity models from individual inversions and the joint inversion. We show that the proposed joint inversion method not only produces superior velocity models but also generates physically more meaningful and accurate Poisson ratio models.

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