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Communication Dans Un Congrès Année : 2022

Emancipating Fwi Imaging from Traveltime Tomography in Valhall Via Optimal Transport Joint Full Waveform Inversion

Résumé

In the Valhall field ocean-bottom-cable (OBC) dataset, a wide literature have shown that FWI enriches an traveltime-based initial velocity model with geologically meaningful details, improving the imaging of shallow multi-layered low velocity zones and complex deep structures. The quality of traveltime prediction in the starting model makes it possible to use a least-square objective function without cycle skipping. However, building such a starting model requires time-consuming and subjective phase picking and labelling. In this work, we propose a robust velocity-model building workflow starting from a one-dimensional initial guess, which combines: joint diving and reflection FWI (JFWI), to obtain deep velocity updates while constraining the shallow portions of the model; a graph space optimal transport objective function to prevent cycle-skipping; a pseudotime reformulation of the JFWI gradient enforcing velocity-reflectivity consistency. Subject to minimal pre-processing, a satisfactory model reconstruction is achieved despite a very simple starting model, as demonstrated by ground-truth fit and data prediction. JFWI contributes significantly to reconstructing the model at depths larger than 2 Km, while GSOT attenuates the risk of cycle skipping compared to a least-square approach, on the road to a full emancipation of FWI from the use of accurate starting models based on traveltime tomography.
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Dates et versions

hal-03852666 , version 1 (10-11-2023)

Identifiants

Citer

Giuseppe Provenzano, Romain Brossier, Ludovic Métivier, Arnaud Pladys. Emancipating Fwi Imaging from Traveltime Tomography in Valhall Via Optimal Transport Joint Full Waveform Inversion. 83rd EAGE Annual Conference & Exhibition, Jun 2022, Madrid, Spain. pp.1-5, ⟨10.3997/2214-4609.202210395⟩. ⟨hal-03852666⟩
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