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Abstract

Summary

We present a two-step procedure to full-waveform inversion (FWI) that combines a stochastic, genetic algorithm optimization and a subsequent gradient-based inversion with the aim to estimate a high-resolution P-wave velocity (Vp) model of the shallow seabed layers. In particular, we take advantage of the broad band frequency content of the seismic well-site (WSS) data to extend the frequency range up to 70 Hz. The first step is a genetic algorithm optimization aimed at deriving a reliable starting model for the subsequent gradient-based FWI. The lack of low frequencies and the limited maximum offset of the WSS acquisition, make the GA inversion particularly crucial as it provides a Vp field that contains the low-medium wavelengths of the subsurface compressional velocity field. These wavelengths are essential to attenuate the risk for the following gradient-based FWI of being trapped into local minima. The gradient-based FWI is performed in the acoustic approximation thus inverting for the Vp only. This two-step procedure yields a final Vp model characterized by an improved resolution with respect to the outcomes of GA-FWI and many fine details of the layering. The fair match between the reflections kinematics in the actual and predicted data supports the reliability of the final model.

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/content/papers/10.3997/2214-4609.201602146
2016-09-04
2024-04-19

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References

  1. Aleardi, M., Tognarelli, A., and Mazzotti, A.
    [2015]. Characterization of Shallow Marine Sediments by Means of High Resolution Velocity Analysis and Stochastic 1D FWI. 21st European Meeting of Environmental and Engineering Geophysics, DOI: 10.3997/2214‑4609.201413804.
     https://doi.org/10.3997/2214-4609.201413804 [Google Scholar]
  2. Aleardi, M., and Mazzotti, A.
    [2016]. 1D Elastic full-waveform inversion and uncertainty estimation by means of hybrid genetic algorithm-Gibbs sampler approach. Accepted for publication in Geophysical Prospecting.
     [Google Scholar]
  3. Mallick, S., and Dutta, N. C.
    [2002]. Shallow water flow prediction using prestack waveform inversion of conventional 3D seismic data and rock modeling. The Leading Edge, 21(7), 675–680.
     [Google Scholar]
  4. Sajeva, A., Aleardi, M., Mazzotti, A., Stucchi, E., and Galuzzi, B.
    [2014]. Comparison of Stochastic Optimization Methods on Two Analytic Objective Functions and on a 1D Elastic FWI. 76th EAGE Conference and Exhibition 2014, 16–19 June 2014, Amsterdam, DOI: 10.3997/2214‑4609.20140857.
     https://doi.org/10.3997/2214-4609.20140857 [Google Scholar]
  5. TognarelliA., Stucchi, E.M., Bienati, N., Sajeva, A., Aleardi, M., and Mazzotti, A.
    [2015]. Two grid stochastic Full Waveform Inversion of 2D Marine Seismic Data. 77th EAGE Conference and Exhibition 2015, 1–4 June 2015, Madrid, DOI: 10.3997/2214‑4609.201413197.
     https://doi.org/10.3997/2214-4609.201413197 [Google Scholar]
  6. Virieux, J., and Operto, S.
    [2009]. An overview of full-waveform inversion in exploration geophysics. Geophysics, 74(6), WCC1–WCC26.
     [Google Scholar]
  7. Sajeva, A., Aleardi, M., Stucchi, E., Binati, N., Mazzotti, A.
    [2016]. Estimation of acoustic macro-models using genetic full-waveform inversion: applications to the Marmousi model. Accepted for publication in Geophysics.
     [Google Scholar]
http://instance.metastore.ingenta.com/content/papers/10.3997/2214-4609.201602146
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Estimation of a High Resolution P-wave Velocity Model of the Seabed Layers by Means of Global and a Gradient-based FWI
Conference Proceedings 2016, 1 (2016); https://doi.org/10.3997/2214-4609.201602146
/content/papers/10.3997/2214-4609.201602146
/content/papers/10.3997/2214-4609.201602146
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