Decimetric-resolution stochastic inversion of shallow marine seismic reflection data: Dedicated strategy and application to a geohazard case study

Abstract

Characterization of the top 10-50 m of the subseabed is key for landslide hazard assessment, offshore structure engineering design and underground gas-storage monitoring. In this paper, we present a methodology for the stochastic inversion of ultra-high-frequency (UHF, 0.2- 4.0 kHz) pre-stack seismic reflection waveforms, designed to obtain a decimetric-resolution remote elastic characterization of the shallow sediments with minimal pre-processing and little a priori information. We use a genetic algorithm in which the space of possible solutions is sampled by explicitly decoupling the short and longwavelengths of the P-wave velocity model. This approach, combined with an objective function robust to cycle skipping, outperforms a conventional model parametrization when the ground-truth is offset from the centre of the search domain. The robust P-wave velocity model is used to precondition the width of the search range of the multiparameter elastic inversion, thereby improving the efficiency in highdimensional parametrizations. Multiple independent runs provide a set of independent results from which the reproducibility of the solution can be estimated. In a real data set acquired in Finneidfjord, Norway, we also demonstrate the sensitivity of UHF seismic inversion to shallow subseabed anomalies that play a role in submarine slope stability. Thus, the methodology has the potential to become an important practical tool for marine ground model building in spatially heterogeneous areas, reducing the reliance on expensive and time-consuming coring campaigns for geohazard mitigation in marine areas.