Full waveform inversion (FWI) applications on 3D ocean bottom cable (OBC) data fromthe Valhall oil field in the North Sea have demonstrated the importance of appropriately ac-counting for attenuation. The Valhall field contains unconsolidated shallow sediments anda low velocity anomaly in its center - indicative of gas clouds - which have a significantattenuation imprint on the data. The challenge in which we are interested is to performtime-domain visco-acoustic 3D FWI, which requires more sophisticated tools than in thefrequency domain wherein attenuation can be incorporated in a straightforward manner.The benefit of employing a visco-acoustic, instead of a purely acoustic, modeling engineis illustrated. We show that, in the frequency band employed (2.5 - 7.0 Hz), it is betterto reconstruct velocity only keeping attenuation fixed, because simultaneous inversion ofvelocity and quality factor Q does not provide reliable Q-updates. We design an efficienttime-domain workflow combining a random source decimation algorithm, modeling usingstandard linear solid mechanisms, and wavefield preconditioning. Our results are similarto those obtained from state-of-the-art frequency-domain algorithms, at a lower computa-tional cost compared to conventional checkpointing techniques. We clearly illustrate theimprovement in terms of imaging and data fit achieved when accounting for attenuation.
Full waveform inversion, a high-resolution seismic imaging method, is known to require sufficiently accurate initial models to converge toward meaningful estimations of the subsurface mechanical properties. This limitation is due to the non-convexity of the least-squares distance with respect to kinematic mismatch. We propose a comparison of five misfit functions promoted recently to mitigate this issue: adaptive waveform inversion, instantaneous envelope, normalized integration, and two methods based on optimal transport. We explain which principles these methods are based on and illustrate how they are designed to better handle kinematic mismatch than a least-squares misfit function. By doing so, we can exhibit specific limitations of these methods in canonical cases. We further assess the interest of these five approaches for application to field data based on a synthetic Marmousi case study. We illustrate how adaptive waveform inversion and the two methods based on optimal transport possess interesting properties, making them appealing strategies applicable to field data. Another outcome is the definition of generic tools to compare misfit functions for full-waveform inversion.
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