1887
Volume 48, Issue 2
  • ISSN: 0812-3985
  • E-ISSN: 1834-7533

Abstract

[

We have developed an automatic first-arrival picking method that combines extended super-virtual interferometry with quality control. The field data examples show that the proposed method yields stacked sections of similar quality to those obtained by laborious and costly manual picking.

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Static correction is a crucial step of seismic data processing for onshore play, which frequently has a complex near-surface condition. The effectiveness of the static correction depends on an accurate determination of first-arrival traveltimes. However, it is difficult to accurately auto-pick the first arrivals for data with low signal-to-noise ratios (SNR), especially for those measured in the area of the complex near-surface. The technique of the super-virtual interferometry (SVI) has the potential to enhance the SNR of first arrivals. In this paper, we develop the extended SVI with (1) the application of the reverse correlation to improve the capability of SNR enhancement at near-offset, and (2) the usage of the multi-domain method to partially overcome the limitation of current method, given insufficient available source-receiver combinations. Compared to the standard SVI, the SNR enhancement of the extended SVI can be up to 40%. In addition, we propose a quality control procedure, which is based on the statistical characteristics of multichannel recordings of first arrivals. It can auto-correct the mispicks, which might be spurious events generated by the SVI. This procedure is very robust, highly automatic and it can accommodate large data in batches. Finally, we develop one automatic first-arrival picking method to combine the extended SVI and the quality control procedure. Both the synthetic and the field data examples demonstrate that the proposed method is able to accurately auto-pick first arrivals in seismic traces with low SNR. The quality of the stacked seismic sections obtained from this method is much better than those obtained from an auto-picking method, which is commonly employed by the commercial software.

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/content/journals/10.1071/EG14120
2017-06-01
2026-01-14
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References

  1. Alshuhail A. Aldawood A. Hanafy S. 2012 Application of super-virtual seismic refraction interferometry to enhance first arrivals: a case study from Saudi Arabia: The Leading Edge 31 34 39 10.1190/1.3679326
    https://doi.org/10.1190/1.3679326 [Google Scholar]
  2. An, S. P., Liang, X. H., Hu, T., and Peng, G. X., 2014, Application of improved interferometry on low SNR data to auto-pick first arrivals: 76th Conference and Exhibition, EAGE, Extended Abstracts, We D201 14.
  3. Bharadwaj P. Schuster G. Mallinson I. Dai W. 2012 Theory of super-virtual refraction interferometry: Geophysical Journal International 188 263 273 10.1111/j.1365‑246X.2011.05253.x
    https://doi.org/10.1111/j.1365-246X.2011.05253.x [Google Scholar]
  4. Boschetti J. Dentith M. D. List R. D. 1996 A fractal-based algorithm for detecting first arrivals on seismic traces: Geophysics 61 1095 1102 10.1190/1.1444030
    https://doi.org/10.1190/1.1444030 [Google Scholar]
  5. Coppens F. 1985 First arrival picking on common-offset trace collections for automatic estimation of static corrections: Geophysical Prospecting 33 1212 1231 10.1111/j.1365‑2478.1985.tb01360.x
    https://doi.org/10.1111/j.1365-2478.1985.tb01360.x [Google Scholar]
  6. Dong, S., He, R., and Schuster, G. T., 2006a, Interferometric prediction and least squares subtraction of surface waves: 76th SEG Technical Program, Expanded Abstracts, 2783–2786.
  7. Dong, S., Sheng, J., and Schuster, G. T., 2006b, Theory and practice of refraction interferometry: 76th SEG Technical Program, Expanded Abstracts, 3021–3025.
  8. Draganov D. Wapenaar K. Thorbecke J. 2006 Seismic interferometry: reconstructing the earth’s reflection response: Geophysics 71 SI61 SI70 10.1190/1.2209947
    https://doi.org/10.1190/1.2209947 [Google Scholar]
  9. Holland P. W. Welsch R. E. 1977 Robust regression using iteratively reweighted least-squares: Communications in Statistics. Theory and Methods 6 813 827 10.1080/03610927708827533
    https://doi.org/10.1080/03610927708827533 [Google Scholar]
  10. Ikelle L. T. 2006 A construct of internal multiples from surface data only: the concept of virtual seismic events: Geophysical Journal International 164 383 393 10.1111/j.1365‑246X.2006.02857.x
    https://doi.org/10.1111/j.1365-246X.2006.02857.x [Google Scholar]
  11. Key S. C. Smithson S. B. 1990 New approach to seismic-reflection event detection and velocity determination: Geophysics 55 1057 1069 10.1190/1.1442918
    https://doi.org/10.1190/1.1442918 [Google Scholar]
  12. Leśniak A. Niitsuma H. 1998 Time-frequency coherency analysis of three-component crosshole seismic data for arrival detection: Geophysics 63 1847 1857 10.1190/1.1444477
    https://doi.org/10.1190/1.1444477 [Google Scholar]
  13. Liu H. Huang W. Li Y. 2014 Seismic-while-drilling data processing with seismic interferometry in the Daqing Oilfield experiment: Exploration Geophysics 45 164 170 10.1071/EG13078
    https://doi.org/10.1071/EG13078 [Google Scholar]
  14. Mallinson I. Bharadwaj P. Schuster G. Jakubowicz H. 2011 Enhanced refractor imaging by super-virtual interferometry: The Leading Edge 30 546 550 10.1190/1.3589113
    https://doi.org/10.1190/1.3589113 [Google Scholar]
  15. Mikesell D. van Wijk K. Calvert A. Haney M. 2009 The virtual refraction: useful spurious energy in seismic interferometry: Geophysics 74 A13 A17 10.1190/1.3095659
    https://doi.org/10.1190/1.3095659 [Google Scholar]
  16. Mousa W. A. Al-Shuhail A. A. Al-Lehyani A. 2011 A new technique for first-arrival picking of refracted seismic data based on digital image segmentation: Geophysics 76 V79 V89 10.1190/geo2010‑0322.1
    https://doi.org/10.1190/geo2010-0322.1 [Google Scholar]
  17. Murat M. Rudman A. 1992 Automated first arrival picking: a neural network approach: Geophysical Prospecting 40 587 604 10.1111/j.1365‑2478.1992.tb00543.x
    https://doi.org/10.1111/j.1365-2478.1992.tb00543.x [Google Scholar]
  18. Sabbione J. Velis D. 2010 Automatic first-breaks picking: new strategies and algorithms: Geophysics 75 V67 V76 10.1190/1.3463703
    https://doi.org/10.1190/1.3463703 [Google Scholar]
  19. Saragiotis, C. D., and Alkhalifah, T., 2012, Automatic first-break picking using the instantaneous traveltime attribute: 74th EAGE Conference and Exhibition incorporating SPE EUROPEC 2012, Extended Abstracts, I025.
  20. Saragiotis C. D. Hadjileontiadis L. J. Rekanos I. T. Panas S. M. 2004 Automatic P phase picking using maximum kurtosis and k-statistics criteria: IEEE Geoscience and Remote Sensing Letters 1 147 151 10.1109/LGRS.2004.828915
    https://doi.org/10.1109/LGRS.2004.828915 [Google Scholar]
  21. Snieder R. Wapenaar K. Larner K. 2006 Spurious multiples in seismic interferometry of primaries: Geophysics 71 SI111 SI124 10.1190/1.2211507
    https://doi.org/10.1190/1.2211507 [Google Scholar]
  22. van Wijk, K., Calvert, A., Haney, M., Mikesell, D., and Snieder, R., 2008, The critical angle in seismic interferometry: 78th SEG Technical Program, Expanded Abstracts, 2737–2741.
  23. Wapenaar K. Fokkema J. 2006 Green’s function representations for seismic interferometry: Geophysics 71 SI33 SI46 10.1190/1.2213955
    https://doi.org/10.1190/1.2213955 [Google Scholar]
  24. Yung S. K. Ikelle L. T. 1997 An example of seismic time picking by third-order bicoherence: Geophysics 62 1947 1952 10.1190/1.1444295
    https://doi.org/10.1190/1.1444295 [Google Scholar]
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