Mitigating elastic effects in marine 3-D full-waveform inversion

Abstract

SUMMARY The potential of full-waveform inversion (FWI) to recover high-resolution velocity models of the subsurface has been demonstrated in the last decades with its application to field data. But in certain geological scenarios, conventional FWI using the acoustic wave equation fails in recovering accurate models due to the presence of strong elastic effects, as the acoustic wave equation only accounts for compressional waves. This becomes more critical when dealing with land data sets, in which elastic effects are generated at the source and recorded directly by the receivers. In marine settings, in which sources and receivers are typically within the water layer, elastic effects are weaker but can be observed most easily as double mode conversions and through their effect on P-wave amplitudes. Ignoring these elastic effects can have a detrimental impact on the accuracy of the recovered velocity models, even in marine data sets. Ideally, the elastic wave equation should be used to model wave propagation, and FWI should aim to recover anisotropic models of velocity for P waves (vp) and S waves (vs). However, routine three-dimensional elastic FWI is still commercially impractical due to the elevated computational cost of modelling elastic wave propagation in regions with low S-wave velocity near the seabed. Moreover, elastic FWI using local optimization methods suffers from cross-talk between different inverted parameters. This generally leads to incorrect estimation of subsurface models, requiring an estimate of vp/vs that is rarely known beforehand. Here we illustrate how neglecting elasticity during FWI for a marine field data set that contains especially strong elastic heterogeneities can lead to an incorrect estimation of the P-wave velocity model. We then demonstrate a practical approach to mitigate elastic effects in 3-D yielding improved estimates, consisting of using a global inversion algorithm to estimate a model of vp/vs, employing matching filters to remove elastic effects from the field data, and performing acoustic FWI of the resulting data set. The quality of the recovered models is assessed by exploring the continuity of the events in the migrated sections and the fit of the latter with the recovered velocity model.

Elastic full-waveform inversion of 4C ocean-bottom seismic data: Model parameterization analysis

“…For the commonly used model parameterization of seismic velocity (V p , V s ), we can observe the V p model reconstruction only relies on P-P diffracted waves (Figure 1a), which is the same as in the acoustic FWI (Operto et al, 2013). It interprets the applicability of acoustic FWI in achieving a successful V p model reconstruction, when the data have a relatively weak elastic-effect imprint or the elastic effects can be mitigated by a data pre-processing (Agudo et al, 2020). The radiation patterns of the other two parameterizations show additional S-related wave modes are involved in the V p reconstruction (Figures 1b and 1c).…”

Magma Chamber Detected Beneath an Arc Volcano With Full‐Waveform Inversion of Active‐Source Seismic Data

“…These targets will require modeling of irregular land surface either by using finite-element-like solvers (which require a challenging meshing step, e.g., Komatitsch & Tromp, 2002) or the augmented finite-difference method (e.g., Chrapkiewicz, 2021). Whether marine or land, elastic FWI will also require detailed a priori knowledge of the shallow subsurface and/ or suppressing some of the elastic effects present in the data (e.g., Agudo et al, 2020).…”

Two-step full waveform inversion of diving and reflected waves with the diffraction-angle-filtering-based scale-separation technique

“…In acoustic FWI for field data, the inherent anisotropic and elastic properties of the vertical P-wave velocity using the rabbit-ears-shaped kernels, which is less affected by anisotropy. Meanwhile, mono-parameter acoustic inversion cannot fully recover large contrasts of the P-and S-wave impedances (e.g., at the chalk interface) due to amplitude mismatches caused by the PS mode conversion (Agudo et al 2020). For further improvements, we need to perform elastic FWI to simultaneously recover the P-wave and Swave structures by using the inverted P-wave background velocity model as an initial guess.…”