Gradient-based Seismic Inversion using a Finite Frequency Assumption for Imaging Velocity and Attenuation
Résumé
Various studies operated seismic methods for imaging landslide structures. Among them, different approaches can be used to process the data, analyze and exploit the different kind of waves associated to particular propagation phenomena. Ferucci et al. (2000) used the late arrivals of P-waves to produce a reflective seismic section of the landslide. Glade et al. (2005) used the refracted waves to delimit main landslide's layers. Grandjean et al. (2011) studied the first arrival traveltimes to recover P-wave velocity distribution across landslides. Finally, based on the work of Virieux and Operto (2009), Romdhane et al. (2011) showed the possibility to perform a full elastic waveform inversion (FWI) on a real dataset acquired over an earthflow. All those methods are more or less based on strong approximations and require complex data preprocessing. The issue of recovering the structural image of a landslide from the seismic velocity field estimated with an accurate, but not too unstable, method is thus posed. To solve it, we choose to revisit first arrival tomography approach which is a good compromise between the strong assumptions featuring simple refraction methods and the complexity of FWI approach when used in very heterogeneous soils. The proposed method is based on a gradient / Hessian formulation (Tarantola, 1987) to ensure an optimum convergence of the velocity model. We only use here the first arrivals of the seismic signal due to direct or refracted waves. Nevertheless, we show that some regularization strategies allow detecting sharp velocity variations tending to reach FWI inversion performances.