1887

Abstract

Summary

The interpolation method based on prediction filter is one of the most effective approaches recently proposed for seismic data reconstruction. However, the number of effective regression equations for estimating the filter coefficients will be less with missing much seismic data. The number of effective regression equations can increase much more using multi-directional and multi-scale prediction-error filter, the accuracy of filter coefficients can increase much more. We developed a new approach to interpolate missing much seismic data based on multi-scale multi-directional prediction-error filtering method. For seismic data which is partial regular missing and partial irregular missing, the proposed method can be used to interpolate missing traces to obtain more accurate results conveniently. The proposed method improves the calculation accuracy and conveniences by applying more effective regression equations from different directions and scales. The applicability and effectiveness of the proposed method are examined by synthetic and field data examples.

Loading

Article metrics loading...

/content/papers/10.3997/2214-4609.201801396
2018-06-11
2020-04-09
Loading full text...

Full text loading...

References

  1. Claerbout, J. F.
    [1992] Earth soundings analysis: Processing versus inversion. Blackwell Scientific Publications.
    [Google Scholar]
  2. Li, C., Liu, G., Hao, Z., Zu, S., Mi, F. and Chen, X.
    [2017] Multidimensional seismic data reconstruction using frequency domain adaptive prediction-error filter. IEEE Transactions on Geoscience and Remote Sensing, to be published. doi: 10.1109/TGRS.2017.2778196
    https://doi.org/10.1109/TGRS.2017.2778196 [Google Scholar]
  3. Liu, G. and Chen, X.
    [2017] Seismic data interpolation using frequency domain complex nonstationary autoregression. Geophysical Prospecting, to be published. doi: 10.1111/1365‑2478.12499.
    https://doi.org/10.1111/1365-2478.12499 [Google Scholar]
  4. Liu, Y. and Fomel, S.
    [2011] Seismic data interpolation beyond aliasing using regularized nonstationary autoregression. Geophysics, 76, V69–V77.
    [Google Scholar]
  5. Spitz, S.
    [1991] Seismic trace interpolation in the f–x domain. Geophysics, 56, 785–794.
    [Google Scholar]
  6. Wang, Y.
    [2002] Seismic trace interpolation in the f–x–y domain. Geophysics, 67, 1232–1239.
    [Google Scholar]
http://instance.metastore.ingenta.com/content/papers/10.3997/2214-4609.201801396
Loading
/content/papers/10.3997/2214-4609.201801396
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