1887

Abstract

Summary

Removal of high-amplitude cross-flow noise in marine towed-streamer acquisition is of great interest because cross-flow noise hinders the success of subsequent processing (e.g. EPSI) and migration. However, the removal of cross-flow noise is a challenging process because cross-flow noise dominates steep angles and low-frequency components of the signal. As a result, applying a simple high-pass filter can result in a loss of coherent diving waves and reflected energy. We propose a stable curvelet-based principle- component pursuit approach that does not suffer from this shortcoming because it uses angle- and scale-adaptivity of the curvelet transform in combination with the low-rank property of cross-flow noise. As long as the cross-flow noise exhibits low-rank structure in the curvelet domain, our method successfully separates this signal component from the diving waves and seismic reflectivity, which are well-know to be sparse in the curvelet domain. Experimental results on a common-shot gather extracted from a coil shooting survey in the Gulf of Mexico shows the potential of our approach.

Loading

Article metrics loading...

/content/papers/10.3997/2214-4609.201701055
2017-06-12
2024-04-19
Loading full text...

Full text loading...

References

  1. Aravkin, A., Becker, S., Cevher, V. and Olsen, P.
    [2014] A variational approach to stable principal component pursuit. In: Conference on Uncertainty in Artificial Intelligence (UAI).
    [Google Scholar]
  2. Candes, E.J. and Donoho, D.L.
    [2000] Curvelets: A surprisingly effective nonadaptive representation for objects with edges. Tech. rep., DTIC Document.
    [Google Scholar]
  3. Herrmann, F.J., Calvert, A.J., Hanlon, I., Javanmehri, M., Kumar, R., van Leeuwen, T., Li, X., Smithyman, B., Takougang, E.T and Wason, H.
    [2013] Frugal full-waveform inversion: from theory to a practical algorithm. The Leading Edge, 32(9), 1082–1092.
    [Google Scholar]
  4. Herrmann, F.J. and Hennenfent, G.
    [2008] Non-parametric seismic data recovery with curvelet frames. Geophysical Journal International, 173, 233–248.
    [Google Scholar]
  5. Lin, TT and Herrmann, F.J.
    [2013] Robust estimation of primaries by sparse inversion via one-norm minimization. Geophysics, 78(3), R133–R150.
    [Google Scholar]
  6. Martin, J., Ozbek, A., Combee, L., Lunde, N., Bittleston, S. and Kragh, E.
    [2000] Acquisition of marine point receiver seismic data with a towed streamer. In: Annual Meeting Abstracts, Society of Exploration Geophysicists.
    [Google Scholar]
  7. Moldoveanu, N.
    [2011] Attenuation of high energy marine towed-streamer noise. In: 2011 SEG Annual Meeting. Society of Exploration Geophysicists.
    [Google Scholar]
  8. Neelamani, R., Baumstein, A.I., Gillard, D.G., Hadidi, M.T. and Soroka, W.L.
    [2008] Coherent and random noise attenuation using the curvelet transform. The Leading Edge, 27(2), 240–248.
    [Google Scholar]
  9. Özbek, A.
    [2000] Adaptive beamforming with generalized linear constraints. In: 2000 SEG Annual Meeting. Society of Exploration Geophysicists.
    [Google Scholar]
http://instance.metastore.ingenta.com/content/papers/10.3997/2214-4609.201701055
Loading
/content/papers/10.3997/2214-4609.201701055
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