1887

Abstract

Summary

Full Waveform Inversion (FWI) is a high-resolution seismic imaging tool, based on an iterative data fitting procedure. In this research, we focus on a near-surface application using three-component sources and three-component receivers (9C). The target is the Ettlingen Line, a defensive trench line located at Rheinstetten, Germany. In this work, we describe the first application of 3D elastic FWI method to a dense 3D dataset equipped with 9C. In practice, due to the limited number of equipment, the acquisition has been split into six parts (each part has the all source locations but only part of receiver locations). This separation leads to an inconsistent dataset concerning both amplitudes and phases. Therefore, a first step has led to the application of matching filter to homogenize the dataset. Several FWI strategies such as Vp − Vs parameter binding, gradient Bessel smoothing, and multi-scale approach have been considered during the inversion process to ensure a good convergence. Starting from a homogeneous model, we can achieve significant improvement in data-fit as well as a realistic reconstructed model. The location and dimension of the trench match with the previous experiments based on the inversion of surface wave dispersion curves with an additional increase in resolution.

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/content/papers/10.3997/2214-4609.201900994
2019-06-03
2020-07-07
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References

  1. Häusler, M., Schmelzbach, C. and Sollberger, D.
    [2018] The Galperin source: A novel efficient multicomponent seismic source. Geophysics, 83(6), P19–P27.
    [Google Scholar]
  2. Köhn, D., Wilken, D., De Nil, D., Wunderlich, T., Rabbel, W. and Werther, L.
    [2018] 2D full waveform inversion applied to a strongly-dispersive Love wave field dataset. In: 80th EAGE Conference and Exhibition2018.
    [Google Scholar]
  3. Lang, K. et al.
    [1907] Die Ettlinger Linien und ihre Geschichte. Selbstverlag der Stadt Ettlingen.
    [Google Scholar]
  4. Pan, Y., Schaneng, S., Steinweg, T. and Bohlen, T.
    [2018] Estimating S-wave velocities from 3D 9-component shallow seismic data using local Rayleigh-wave dispersion curves – A field study. Journal of Applied Geophysics, 159, 532–539.
    [Google Scholar]
  5. Pratt, R.G.
    [1999] Seismic waveform inversion in the frequency domain, part I : theory and verification in a physical scale model. Geophysics, 64, 888–901.
    [Google Scholar]
  6. Smith, J.A., Borisov, D., Cudney, H., Miller, R.D., Modrak, R., Moran, M., Peterie, S.L., Sloan, S.D., Tromp, J. and Wang, Y.
    [2018] Tunnel Detection At Yuma Proving Ground, Arizona, USA. Part 2: 3D Full-Waveform Inversion Experiments. Geophysics, 84(1), 1–98.
    [Google Scholar]
  7. Trinh, P.T., Brossier, R., Métivier, L., Tavard, L. and Virieux, J.
    [2019] Efficient 3D time-domain elastic and viscoelastic Full Waveform Inversion using a spectral-element method on flexible Cartesian-based mesh. Geophysics, 84(1), R75–R97.
    [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. Wegscheider, S.
    [2017] Abbildung der Ettlinger Linie auf dem Segelflugplatz Rheinstetten mittels Georadar. Master's thesis, Karlsruhe Institute of Technology.
    [Google Scholar]
  10. Wittkamp, F., Athanasopoulos, N. and Bohlen, T.
    [2018] Individual and joint 2-D elastic full-waveform inversion of Rayleigh and Love waves. Geophysical Journal International, 216(1), 350–364.
    [Google Scholar]
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