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An optimal transport distance for full-waveform inversion: Application to the 2014 Chevron benchmark data set

Abstract : Mitigating cycle skipping in full waveform inversion is a long term issue. In this study, a modification of the misfit function based on an optimal transport distance is proposed. A specific numerical strategy based on the Kantorovich-Rubinstein norm and a proximal splitting algorithm is designed to compute this misfit function and its gradient efficiently. An example of application on the Marmousi model shows that the optimal transport misfit function is more robust to cycle skipping than the conventional L2 misfit function. When applied to the Chevron 2014 benchmark data-set, a reliable velocity estimation is computed, using only a multi-scale strategy in frequency, while the L2 misfit function is trapped into a local minimum following the same workflow.
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https://hal.archives-ouvertes.fr/hal-02009564
Contributor : Ludovic Métivier Connect in order to contact the contributor
Submitted on : Wednesday, February 6, 2019 - 2:03:34 PM
Last modification on : Saturday, January 15, 2022 - 3:51:06 AM

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Ludovic Métivier, Romain Brossier, Edouard Oudet, Quentin Mérigot, Jean Virieux. An optimal transport distance for full-waveform inversion: Application to the 2014 Chevron benchmark data set. SEG Technical Program Expanded Abstracts 2016, Oct 2016, Dallas, United States. pp.1278-1283, ⟨10.1190/segam2016-13870096.1⟩. ⟨hal-02009564⟩

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