Multiparameter 2-D viscoelastic full-waveform inversion of Rayleigh waves: a field experiment at Krauthausen test site

Author:

Gao Lingli1,Pan Yudi234ORCID,Rieder Andreas5,Bohlen Thomas6,Mao Weijian1

Affiliation:

1. Research Center for Computational and Exploration Geophysics, State Key Laboratory of Geodesy and Earth’s Dynamics, Innovation Academy of Precision Measurement Technology and Science, Chinese Academy of Sciences , Wuhan 430077, China

2. School of Geodesy and Geomatics, Wuhan University , Wuhan 430079, China

3. Key Laboratory of Geospace Environment and Geodesy, Ministry of Education, Wuhan University , Wuhan 430079, China

4. Hubei Luojia Laboratory , Wuhan 430079, China

5. Institute for Applied and Numerical Mathematics, Karlsruhe Institute of Technology (KIT) , Karlsruhe 76131, Germany

6. Geophysical Institute, Karlsruhe Institute of Technology (KIT) , Karlsruhe 76187, Germany

Abstract

SUMMARYFull-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.

Funder

Natural Science Foundation of China

German Research Foundation

Publisher

Oxford University Press (OUP)

Subject

Geochemistry and Petrology,Geophysics

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