Multiparameter 2-D viscoelastic full-waveform inversion of Rayleigh waves: a field experiment at Krauthausen test site. Issue 1 (16th February 2023) - Gao, Lingli; Pan, Yudi; Rieder, Andreas; Bohlen, Thomas; Mao, Weijian
SUMMARY: Full-waveform inversion (FWI) has been proven to be an effective tool for high-resolution multiparameter imaging of the shallow subsurface. It has been shown that the Gauss–Newton (GN) optimization method uses the off-diagonal information contained in the Hessian matrix and can increase resolution and mitigate crosstalk in multiparameter viscoelastic FWI. In this work, we demonstrate the advantages of GN viscoelastic FWI over the conventional FWI with a conjugate gradient optimization method by using synthetic examples. We also investigate the potential of shallow seismic-wave 2-D viscoelastic FWI as a method for high-resolution hydrogeological characterization. The GN viscoelastic FWI is applied to two orthogonal profiles acquired at the Krauthausen natural laboratory (Germany). The groundwater table is located at around 2 m, which nicely agrees with an abrupt increase of P -wave velocity in the inverted results. FWI also reveals a low S -wave velocity layer at the depth of 4–6 m with high Poisson's ratio values close to 0.5, which corresponds to a saturated sand layer known from previous studies. A K -mean cluster analysis is used to further analyse the multiparameter FWI results. By considering the derived Poisson's ratio, P - and S -wave velocities, we convert the complex relationship between the multivariate data into a lithological meaningful zonation of the shallow subsurface. By comparing the lithological units in the alluvial aquifer with the cone penetration tests clusters, we conclude that the divided facies describe valuable characterization information about the heterogeneity and connectivity of the aquifer. This experiment indicates that the multiparameter models derived by viscoelastic FWI contain useful information for high-resolution aquifer characterization, and the potential of multiparameter FWI combined with cluster analysis in shallow subsurface characterization is encouraging.