Indirect joint petrophysical inversion of shallow-seismic and multi-offset ground-penetrating radar field data

Author:

Qin Tan123,Bohlen Thomas3,Pan Yudi12ORCID

Affiliation:

1. School of Geodesy and Geomatics, Wuhan University , 430072 Wuhan , China

2. Key Laboratory of Geospace Environment and Geodesy, Ministry of Education, Wuhan University , 430072 Wuhan , China

3. Geophysical Institute, Karlsruhe Institute of Technology , 76187 Karlsruhe , Germany

Abstract

SUMMARY In near-surface surveys, shallow-seismic and ground-penetrating radar (GPR) full-waveform inversions (FWIs) have received increasing attention because of their ability to reconstruct high-resolution subsurface models. However, they have different sensitivities to the same targets and thus may yield conflicting geophysical parameter models. To solve this issue, we have developed an indirect joint petrophysical inversion (JPI) integrating shallow-seismic and multi-offset GPR data. These data are used to reconstruct porosity and saturation whereby we use only strong sensitivities between petrophysical and geophysical parameters. To promote its field application, we proposed an input strategy to avoid measuring rock matrix parameters and make indirect JPI more robust. We apply indirect JPI to the field data acquired in Rheinstetten, Germany and find that it reveals the mechanical, electrical and petrophysical properties more reliably than individual inversions. The reconstructed models are assessed by direct-push technology, borehole sample measurements and migrated GPR image. Indirect JPI can fit seismic and GPR observed data simultaneously and provide consistent multiparameter models, which are hard to achieve by FWIs and individual petrophysical inversions. We also find that the method is robust when there are uncertainties in petrophysical a priori information. Overall, the field example proves the great potential of using indirect JPI to solve real-world problems.

Funder

China Scholarship Council

Natural Science Foundation of Hubei Province

China Postdoctoral Science Foundation

Fundamental Research Funds for the Central Universities

Publisher

Oxford University Press (OUP)

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