1887

Abstract

Summary

We propose a new workflow for surface wave (SW) inversion by combining the two-grid genetic algorithm (GA) and gradient-based full waveform inversion (FWI). The workflow circumvents the notorious requirement of having a “good enough” starting model” in gradient-based SW FWI. At the 1st step of the workflow, without any a-priori information, by employing a coarse inversion grid and by inverting the lower frequencies only of the observed data, GA SW FWI reconstructs the long-wavelength structures of the subsurface. Then, in the next step of the workflow, the GA predicted model is used as the initial model for gradient-based SW FWI. In virtue of the higher efficiency of the gradient-based method, finer inversion grids are adopted and data with higher frequencies can be inverted yielding refined predicted models. We discuss our approach making use of two synthetic examples that reproduce complex near-surface models and we show that fair inversion outcomes are obtained. Models predicted by GA SW FWI are proved to be adequate initial models for gradient-based SW FWI. In addition, the examples confirm the extremely strong impacts that initial models have on gradient-based SW FWI results.

Loading

Article metrics loading...

/content/papers/10.3997/2214-4609.201802567
2018-09-09
2020-04-06
Loading full text...

Full text loading...

References

  1. Aleardi, M. and MazzottiA.
    [2017] 1D elastic full-waveform inversion and uncertainty estimation by means of a hybrid genetic algorithm – Gibbs sampler approach. Geophysical Prospecting, 65, 64–85, doi: 10.1111/1365‑2478.12397.
    https://doi.org/10.1111/1365-2478.12397 [Google Scholar]
  2. Brossier, R., Operto, S. and Virieux, J.
    [2009] Seismic imaging of complex onshore structures by 2D elastic frequency-domain full-waveform inversion. GEOPHYSICS, 74(6), WCC105–WCC118, doi: 10.1190/1.3215771.
    https://doi.org/10.1190/1.3215771 [Google Scholar]
  3. Groos, L., Schäfer, M., Forbriger, T. and Bohlen, T.
    [2017] Application of a complete workflow for 2D elastic full-waveform inversion to recorded shallow-seismic Rayleigh waves. GEOPHYSICS, 82(2), R109–R117, doi: 10.1190/geo2016‑0284.1.
    https://doi.org/10.1190/geo2016-0284.1 [Google Scholar]
  4. Köhn, D., De Nil, D., Kurzmann, A., Przebindowska, A. and Bohlen, T.
    [2012] On the influence of model parametrization in elastic full waveform tomography. Geophys. J. Int., 191, 325–345, doi: 10.1111/j.1365‑246X.2012.05633.x.
    https://doi.org/10.1111/j.1365-246X.2012.05633.x [Google Scholar]
  5. Mazzotti, A., Bienati, N., Stucchi, E., Tognarelli, A., Aleardi, M. and Sajeva, A.
    [2017] Two-grid genetic algorithm full-waveform inversion. The Leading Edge, 35(12), 1068–1075. doi: 10.1190/tle35121068.1.
    https://doi.org/10.1190/tle35121068.1 [Google Scholar]
  6. Sajeva, A., Aleardi, M., Stucchi, E., Bienati, N. and Mazzotti, A.
    [2016] Estimation of acoustic macro models using a genetic full-waveform inversion: Applications to the Marmousi model. Geophysics, 81(4), R173–R184, doi: 10.1190/geo2015‑0198.1.
    https://doi.org/10.1190/geo2015-0198.1 [Google Scholar]
  7. Xing, Z. and Mazzotti, A.
    [2016] Rayleigh waves modelling complexities in the perspective of full waveform inversion of surface waves - synthetic examples. Near Surface Geoscience 2016, Barcelona, Spain, Expanded Abstracts, doi: 10.3997/2214‑4609.201601909.
    https://doi.org/10.3997/2214-4609.201601909 [Google Scholar]
  8. [2017a] Two-grid full waveform Rayleigh wave inversion by means of genetic algorithm with frequency marching. EAGE 2017, Paris, France, Expanded abstracts, doi: 10.3997/2214‑4609.201701412.
    https://doi.org/10.3997/2214-4609.201701412 [Google Scholar]
  9. [2017b] Surface wave FWI on complex models: the robustness of the inversion to assumptions and forward modelling approximations. Near Surface Geoscience 2017, Malmo, Sweden, Expanded abstracts, doi: 10.3997/2214‑4609.201702019.
    https://doi.org/10.3997/2214-4609.201702019 [Google Scholar]
  10. [2018] Two-grid genetic algorithm full waveform inversion of surface waves: two actual data examples. Accepted for EAGE 2018, Copenhagen, Denmark, Expanded abstracts.
    [Google Scholar]
http://instance.metastore.ingenta.com/content/papers/10.3997/2214-4609.201802567
Loading
/content/papers/10.3997/2214-4609.201802567
Loading

Data & Media loading...

This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error