1887

Abstract

Summary

Seismic data from land acquisitions are dominated by highly energetic surface waves (SW), showing complex behaviour when interacting with local structures. SW analysis is, therefore, an important tool for accurate near-surface imaging, even if most of the conventional SW analysis techniques are limited by the lateral invariance assumption. This study attempts to enhance the resolution of shallow targets reconstruction by integrating SW dispersion curves (DC) analysis techniques with a spectral element based elastic full-waveform inversion (FWI) workflow. Multi-parameter elastic FWI tests have been conducted over a synthetic dataset related to a benchmark model that mirrors the characteristics of a real test site. The initial S-and P-wave velocity (Vs and Vp) models have been retrieved by DC analysis with increasing detail resolution. The FWI results showed a better model reconstruction when starting from a more detailed initial model, obtained using the full-DC analysis. Further, we improved the initial Vs model (reconstructed from SW information) by a preliminary mono-parameter FWI step. Starting from this improved initial configuration, we obtained more accurate results when performing the multi-parameter FWI.

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/content/papers/10.3997/2214-4609.201900976
2019-06-03
2019-12-09
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References

  1. Bergamo, P., Boiero, D. and Socco, L.V.
    [2012]. Retrieving 2D structures from surface-waves data by means of space-varying windowing. Geophysics, 77(4), EN39–EN51.
    [Google Scholar]
  2. Khosro Anjom, F., Arabi, A., Socco, L.V. and Comina, C.
    [2017]. Application of a method to determine S and P wave velocities from surface waves data analysis in presence of sharp lateral variations. 36th GNGTS Annual Meeting, Extended Abstracts, 632–635.
    [Google Scholar]
  3. Métivier, L. and Brossier, R.
    [2016]. The seiscope optimization toolbox: A large-scale non-linear optimization library based on reverse communication. Geophysics, 81(2), F11–F25.
    [Google Scholar]
  4. Socco, L.V., Comina, C. and Khosro Anjom, F.
    [2017a]. Time-average velocity estimation through surface-wave analysis: Part 1 - S-wave velocity. Geophysics, 82(3), U49–U59.
    [Google Scholar]
  5. Socco, L.V. and Comina, C.
    [2017]. Time-average velocity estimation through surface-wave analysis: Part 2 — P-wave velocity. Geophysics, 82(3), U61–U73.
    [Google Scholar]
  6. Socco, L.V, Khosro Anjom, F., Comina, C. and Teodor, D.
    [2017b]. P and S-wave velocity models from surface wave dispersion curves data transform. 87th SEG International Annual Meeting, Extended Abstracts, 5197–5200.
    [Google Scholar]
  7. Teodor, D., Comina, C, Socco, L.V, Brossier, R, Trinh, P.-T. and Virieux, J.
    [2017]. Initial model design for Full-Waveform Inversion - Preliminary elastic modeling from surface waves data analysis. 36th GNGTS Annual Meeting, Extended Abstracts, 733–756.
    [Google Scholar]
  8. Trinh, P.-T., Brossier, R, Métivier, L., Virieux, J. and Wellington, P.
    [2017]. Bessel smoothing filter for spectral element mesh. Geophysical Journal International, 209(3), 1489–1512.
    [Google Scholar]
  9. Trinh, P.-T., Brossier, R, Metivier, L., Tavard, L. and Virieux, J.
    [2019]. Efficient time-domain 3D elastic and visco-elastic FWI using a spectral-element method on flexible Cartesian-based mesh. Geophysics, 84(1), R75–R97.
    [Google Scholar]
  10. Virieux, J. and Operto, S.
    [2009]. An overview of full waveform inversion in exploration geophysics. Geophysics, 74(6), WCC1–WCC26.
    [Google Scholar]
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