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Pseudotime domain joint diving-reflected FWI using graph-space optimal transport

Abstract : Reflection waveform inversion (RWI) updates the the P-wave velocity ($V_p$) macromodel beyond the depths sampled by diving waves, by exploiting wide scattering angle wavepaths in a reflective subsurface. Joint diving and reflection waveform inversion (JFWI) combines RWI and early-arrival waveform inversion (EWI), thereby constraining the shallow subsurface whilst enriching the low-wavenumber content of the deep $V_p$ model with reflections. In depth-domain $V_p$ inversion, ensuring consistency between reflectors positions and model kinematics comes at the cost of repeated least-square migrations, combined with carefully designed offset weighting. In order to efficiently address such co-dependency between reflective and kinematic parameters, we propose to cast JFWI in the pseudotime domain. As the velocity is updated, the reflectors are passively repositioned consistently with $V_p$, honoring the zerooffset two-way-time seismic invariant, and keeping the shortspread reflections in phase. By combining a pseudotime approach with a graph-space optimal transport (GSOT) objective function, we show that it's possible to reconstruct a complex velocity macromodel from short offset 2D reflection data containing surface-related multiples and ghosts, starting from a 1D initial guess; compared to a depth-domain inversion, the computing cost is reduced of one order of magnitude, associated with a significant saving in man-time, thanks to a simpler design of data weighting and inversion strategy.
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Contributor : Ludovic Métivier Connect in order to contact the contributor
Submitted on : Tuesday, October 26, 2021 - 5:06:28 PM
Last modification on : Friday, January 14, 2022 - 3:41:20 AM
Long-term archiving on: : Thursday, January 27, 2022 - 8:10:58 PM


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Giuseppe Provenzano, Wei Zhou, Romain Brossier, Ludovic Métivier. Pseudotime domain joint diving-reflected FWI using graph-space optimal transport. First International Meeting for Applied Geoscience & Energy, Sep 2021, Denver, United States. pp.797-801, ⟨10.1190/segam2021-3583318.1⟩. ⟨hal-03404578⟩



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