1887

Abstract

Summary

We discuss the reasons for adaptive de-ghosting and its advantages. The success of broadband processing relies on de-ghosting accuracy, and because the parameters of the physical process determining the ghost reflection are not precisely known, de-ghosting cannot be purely deterministic. The physical entities determining the receiver ghost are the sea surface, the receiver depth and the water velocity and for de-ghosting purposes they can be represented by an effective ghost delay-time and sea surface reflection coefficient.

The de-ghosting optimisation metric we employ is based on the kurtosis of the data-autocorrelation. The kurtosis is a statistical measure often used to associate a measure of “peakedness” to a random variable. A synthetic example characterizes the main features of the adaptive procedure proposed, which can be sequenced in two steps. The optimisation of the ghost delay-time is robust to errors in the reflection coefficient and to noise, Therefore, it should be performed first. The reflection coefficient estimate is more sensitive to noise and requires the delay-time to be optimized in advance, and can therefore be carried out as a second step. A real data example demonstrates the applicability of the proposed method.

Loading

Article metrics loading...

/content/papers/10.3997/2214-4609.201413186
2015-06-01
2024-03-28
Loading full text...

Full text loading...

References

  1. Cambois, G. and Hargreaves, N.D.
    [1994] Zero-phase conversion of marine seismic data using one-parameter phase filters and kurtosis maximization. 64th Annual SEG Meeting Expanded Abstracts, 1591–1594.
    [Google Scholar]
  2. Grion, S., Azmi, A., Pollatos, J., Riddalls, N. and Williams, R. G.
    [2013] Broadband processing with calm and rough seas: observations from a North Sea survey. 83rd Annual SEG Meeting Expanded Abstracts, 226–230.
    [Google Scholar]
  3. MasoomzadehH., WoodburnN. and Hardwick, A.
    [2013] Broadband processing of linear streamer data. 83rd Annual SEG Meeting Expanded Abstracts, 4635–4639.
    [Google Scholar]
  4. Orji, O., Sollner, W. and Gelius, L., J.
    [2013] Sea surface reflection coefficient estimation. 83rd Annual SEG Meeting Expanded Abstracts, 51–55.
    [Google Scholar]
  5. Van der Baan, M.
    [2008] Time-varying wavelet estimation and deconvolution by kurtosis maximization, Geophysics, 73 (2), V11–V18.
    [Google Scholar]
  6. Wang, P., Ray, S., Peng, C., Li, Y., Poole, G.
    [2013] Premigration deghosting for marine streamer data using a bootstrap approach in Tau-P domain. 83rd Annual SEG Meeting Expanded Abstracts, 4221–4225.
    [Google Scholar]
http://instance.metastore.ingenta.com/content/papers/10.3997/2214-4609.201413186
Loading
/content/papers/10.3997/2214-4609.201413186
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