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Communication Dans Un Congrès Année : 2022

Parameterization Analysis in Elastic Full-Waveform Inversion of Multi-Component Seismic Data

Résumé

Main objectives This study analyses the influence of different model parameterizations in the elastic full-waveform inversion of multi-component ocean-bottom seismic data, so as to design an effective FWI workflow to reconstruct P-and S-wave velocity models of the subsurface jointly and robustly, applicable in scenarios of both weak and strong elastic effects. New aspects covered We analyse the pros and cons of three different model parameterizations in the elastic full-waveform inversion and build hierarchical FWI workflows over different parameter classes and data components for multi-component ocean-bottom seismic data. Poisson's ratio is used as the indicator to design the overburden models that produce elastic effects varying from weak to strong in the robustness test of the proposed inversion workflows. An effective hierarchical elastic FWI workflow is found for reconstructing P-and S-wave velocity models jointly and robustly in scenarios of both weak and strong elastic effects.
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Dates et versions

hal-03852657 , version 1 (15-11-2022)

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Jian Cao, Romain Brossier, Ludovic Métivier. Parameterization Analysis in Elastic Full-Waveform Inversion of Multi-Component Seismic Data. 83rd EAGE Annual Conference & Exhibition, Jun 2022, Madrid, Spain. pp.1-5, ⟨10.3997/2214-4609.202210274⟩. ⟨hal-03852657⟩
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