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Abstract

Summary

Iterative least-squares migration is an expensive process that requires several passes of migration and de-migration. In this paper we focus on how an optimized initial reflectivity model combined with a deconvolution imaging condition can ensure faster convergence. We also incorporate the visco-acoustic effects in the de-blurring process to improve image corrections across and below Q-anomalies. This workflow is demonstrated on a dual-azimuth North Sea dataset, where the aim is to improve the understanding of the Frosk and Bøyla fields, which are characterized by complex and steeply dipping sand systems and areas of weak reflectivity.

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/content/papers/10.3997/2214-4609.201900664
2019-06-03
2024-04-19
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References

  1. Guitton, A.
    [2004] Amplitude and kinematic corrections of migrated images for nonunitary imaging operators. Geophysics, 69(4), 1017–1024
    [Google Scholar]
  2. Korsmo, Ø. and Valenciano, A.
    [2018] Iterative Least-Squares Migration in Practice, Application to a Narrow Azimuth North Sea Dataset. First EAGE/SBGF Workshop on Least-Squares Migration.
    [Google Scholar]
  3. Lu, S., Li, X., Valenciano, A., Chemingui, N. and Cheng, C.
    [2017] Least-Squares Wave-Equation Migration for Broadband Imaging. 79th EAGE Conference and Exhibition.
    [Google Scholar]
  4. Nemeth., T., Wu, C., Schuster, G.T.
    [1999] Least-squares migration of incomplete reflection data. Geophysics, 64(1), 208–221
    [Google Scholar]
  5. Valenciano, A.A.
    [2008] Imaging by wave-equation inversion. PhD thesis, Stanford University.
    [Google Scholar]
  6. Valenciano, A.A. and Chemingui, N.
    [2012] Viscoacoustic imaging: tomographic Q estimation and migration compensation. 82nd SEG Annual Meeting, Expanded Abstracts, 1–5.
    [Google Scholar]
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