1887
Volume 52, Issue 5
  • ISSN: 0812-3985
  • E-ISSN: 1834-7533

Abstract

Pre-stack Q migration can eliminate the absorption effect and accurately image underground structures, which is conducive to subsequent reservoir interpretation and hydrocarbon prediction. However, the instability of Q migration amplifies high-frequency noise, which seriously reduces the imaging quality. To solve the instability problem, this paper studies the stability conditions for Q migration in the frequency domain. The generalised standard linear solid (GSLS) model can well describe the attenuation characteristics of underground media by combining different basic rheological models. Based on the Von Neumann stability analysis for the finite difference scheme combined with parameter settings in the GSLS model, this paper focuses on the stability of frequency domain Q migration and theoretically deduces the stability conditions suitable for the GSLS model. The given stability conditions can be directly implemented in the frequency domain Q migration process and constrain only the maximum reference angle frequency rather than the wave field frequencies, which avoids the Gibbs effect like the high-frequency cut method. In addition, the stability conditions can be adjusted adaptively with the computed frequencies, without the problem of over- or insufficient compensation. The model and practical application indicate that based on the GSLS model and its stability conditions, the attenuation effect can be compensated stably, lost energy and frequencies can be recovered, and high-quality imaging results are obtained.

© 2020 Australian Society of Exploration Geophysicists
Loading

Article metrics loading...

/content/journals/10.1080/08123985.2020.1844543
2021-09-03
2026-01-20

  • From This Site

    /content/journals/10.1080/08123985.2020.1844543
    dcterms_title,dcterms_subject,pub_keyword
    -contentType:Journal -contentType:Contributor -contentType:Concept -contentType:Institution
    10
    5
Loading full text...

Full text loading...

References

  1. Bickel, S.H., and R.R.Natarajan. 1985. Plane-wave Q deconvolution. Geophysics50: 1426–39. doi: 10.1190/1.1442011
     https://doi.org/10.1190/1.1442011 [Google Scholar]
  2. Braga, I.L.S., and F.S.Moraes. 2013. High-resolution gathers by inverse Q filtering in the wavelet domain. Geophysics78: V53–61. doi: 10.1190/geo2011‑0508.1
     https://doi.org/10.1190/geo2011-0508.1 [Google Scholar]
  3. Cao, D.2008. Method research of multiscale seismic data modeling and inversion. PhD, China University of Petroleum (EastChina).
  4. Chu, C., C.Phillips, and P.L.Stoffa. 2010. Frequency domain modeling using implicit spatial finite difference Operators. SEG Technical Program Expanded Abstracts 3076–80.
  5. Clarke, G.K.1968. Time-varying deconvolution filters. Geophysics33: 936–44. doi: 10.1190/1.1439987
     https://doi.org/10.1190/1.1439987 [Google Scholar]
  6. Dai, N., and G.F.West. 1994. Inverse Q migration. SEG Technical Program Expanded Abstracts, 1418–21.
  7. Deng, F., and G.A.Mcmechan. 2007. True-amplitude prestack depth migration. Geophysics72: S155–S66. doi: 10.1190/1.2714334
     https://doi.org/10.1190/1.2714334 [Google Scholar]
  8. Futterman, W.I.1962. Dispersive body waves. Journal of Geophysical Research67: 5279–91. doi: 10.1029/JZ067i013p05279
     https://doi.org/10.1029/JZ067i013p05279 [Google Scholar]
  9. Gray, S.H., and K.J.Marfurt. 1995. Migration from topography: improving the near-surface image. Canadian Journal of Exploration Geophysics31: 18–24.
     [Google Scholar]
  10. Griffiths, L.J., F.R.Smolka, and L.D.Trembly. 1977. Adaptive deconvolution: a new technique for processing time-varying seismic data. Geophysics42: 742–59. doi: 10.1190/1.1440743
     https://doi.org/10.1190/1.1440743 [Google Scholar]
  11. Guo, P., H.Guan, R.Nammour, B.Duquet, and G.McMechan. 2017. A stable Q compensation approach for adjoint seismic imaging by pseudodifferential scaling. SEG Technical Program Expanded Abstracts 4566–71.
  12. Hargreaves, N.D.1991. Inverse Q filtering by Fourier transform. Geophysics56: 519–27. doi: 10.1190/1.1443067
     https://doi.org/10.1190/1.1443067 [Google Scholar]
  13. James, D.I., and R.J.Knight. 2003. Removal of wavelet dispersion from ground-penetrating radar data. Geophysics68: 960–70. doi: 10.1190/1.1581068
     https://doi.org/10.1190/1.1581068 [Google Scholar]
  14. Jo, C., C.Shin, and J.H.Suh. 1996. An optimal 9-point, finite-difference, frequency-space, 2-D scalar wave extrapolator. Geophysics61: 315–621. doi: 10.1190/1.1443979
     https://doi.org/10.1190/1.1443979 [Google Scholar]
  15. Liu, L., H.Liu, and H.W.Liu. 2013. Optimal 15-point finite difference forward modeling in frequency-space domain. Chinese Journal of Geophysics56: 644–52.
     [Google Scholar]
  16. Liu, Y., Z.Li, G.Yang, and Q.Liu. 2019. An improved method to estimate Q based on the logarithmic spectrum of moving peak points. Interpretation7: T255–T63. doi: 10.1190/INT‑2017‑0234.1
     https://doi.org/10.1190/INT-2017-0234.1 [Google Scholar]
  17. Lupinacci, W., A.Peixoto de Franco, S.Oliveira, and F.Sergio de Moraes. 2016. A combined time-frequency filtering strategy for Q-factor compensation of poststack seismic data. Geophysics82: V1–6. doi: 10.1190/geo2015‑0470.1
     https://doi.org/10.1190/geo2015-0470.1 [Google Scholar]
  18. Lysmer, J., and L.A.Drake. 1972. A finite element method for seismology. Methods in Computational Physics: Advances in Research and Applications11: 181–216.
     [Google Scholar]
  19. Marfurt, K.J.1984. Accuracy of finite-difference and finite-element modeling of the scalar and elastic wave equations. Geophysics49: 533–49. doi: 10.1190/1.1441689
     https://doi.org/10.1190/1.1441689 [Google Scholar]
  20. Margrave, G.F., M.P.Lamoureux, and D.C.Henley. 2011. Gabor deconvolution: estimating reflectivity by nonstationary deconvolution of seismic data. Geophysics76: W15–30. doi: 10.1190/1.3560167
     https://doi.org/10.1190/1.3560167 [Google Scholar]
  21. Mulder, W.A., and R.E.Plessix. 2008. Exploring some issues in acoustic full waveform inversion. Geophysical Prospecting56: 827–41. doi: 10.1111/j.1365‑2478.2008.00708.x
     https://doi.org/10.1111/j.1365-2478.2008.00708.x [Google Scholar]
  22. Oliveira, S.A.M., and W.M.Lupinacci. 2013. L1 norm inversion method for deconvolution in attenuating media. Geophysical Prospecting61: 771–7. doi: 10.1111/1365‑2478.12002
     https://doi.org/10.1111/1365-2478.12002 [Google Scholar]
  23. Pratt, R.G., and M.H.Worthington. 1990. Inverse theory applied to multi-source cross-hole tomography. Part 1: acoustic wave-equation method. Geophysical Prospecting38: 287–310. doi: 10.1111/j.1365‑2478.1990.tb01846.x
     https://doi.org/10.1111/j.1365-2478.1990.tb01846.x [Google Scholar]
  24. Qingzhong, L.1994. High resolution seismic data processing. Beijing: Petroleum Industry Press.
  25. Shin, C., K.Yoon, K.J.Marfurt, K.Park, D.Yang, H.Y.Lim, S.Chung, and S.Shin. 2001. Efficient calculation of a partial-derivative wavefield using reciprocity for seismic imaging and inversion. Geophysics66: 1856–63. doi: 10.1190/1.1487129
     https://doi.org/10.1190/1.1487129 [Google Scholar]
  26. Shin, J., H.Jun, D.J.Min, and C.Shin. 2017. Frequency-domain waveform modelling and inversion for coupled media using a symmetric impedance matrix. Geophysical Prospecting65: 170–83. doi: 10.1111/1365‑2478.12423
     https://doi.org/10.1111/1365-2478.12423 [Google Scholar]
  27. Tian, K.2014. Study on method of forward modeling and reverse time migration in viscous media. PhD, China University of Petroleum (Huadong).
  28. Tieyuan, Z., J.M.Harris, and B.Biondi. 2014. Q-compensated reverse-time migration. Geophysics79: S77–87. doi: 10.1190/geo2013‑0344.1
     https://doi.org/10.1190/geo2013-0344.1 [Google Scholar]
  29. Traynin, P., J.Liu, and J.M.Reilly. 2008. Amplitude and bandwidth recovery beneath gas zones using Kirchhoff prestack depth Q-migration. SEG Technical Program Expanded Abstracts, 3713.
  30. Ursin, B., and T.Toverud. 2002. Comparison of seismic dispersion and attenuation models. Studia Geophysica Et Geodaetica46: 293–320. doi: 10.1023/A:1019810305074
     https://doi.org/10.1023/A:1019810305074 [Google Scholar]
  31. Wang, Y.2002. A stable and efficient approach of inverse Q filtering. Geophysics67: 657–63. doi: 10.1190/1.1468627
     https://doi.org/10.1190/1.1468627 [Google Scholar]
  32. Wang, Y.2006. Inverse Q-filter for seismic resolution enhancement. Geophysics71: V51–60. doi: 10.1190/1.2192912
     https://doi.org/10.1190/1.2192912 [Google Scholar]
  33. Wang, Y.2007. Inverse Q-filtered migration. Geophysics73: S1–6. doi: 10.1190/1.2806924
     https://doi.org/10.1190/1.2806924 [Google Scholar]
  34. Wang, Y.2008. Seismic inverse Q filtering. Oxford: Blackwell.
  35. Wang, Y., H.Zhou, H.Chen, and Y.Chen. 2017. Adaptive stabilization for Q-compensated reverse time migration. Geophysics82: EN1–11. doi: 10.1190/geo2015‑0534.1
     https://doi.org/10.1190/geo2015-0534.1 [Google Scholar]
  36. Wei, Q., S.Chen, and X.Li. 2018. An improved stabilization inverse Q filtering via shaping regularization scheme. SEG Technical Program Expanded Abstracts 5048–52.
  37. Xie, Y., K.Xin, J.Sun, C.Notfors, A.K.Biswal, and M.K.Balasubramaniam. 2009. 3D Prestack depth migration with compensation for frequency dependent absorption and dispersion. SEG Technical Program Expanded Abstracts 2919–23.
  38. Yilmaz, O.2001. Seismic data analysis. False.
  39. Zhang, G., X.Wang, and Z.He. 2015. A stable and self-adaptive approach for inverse Q-filter. Journal of Applied Geophysics116: 236–46. doi: 10.1016/j.jappgeo.2015.03.012
     https://doi.org/10.1016/j.jappgeo.2015.03.012 [Google Scholar]
  40. Zhang, J., and K.Wapenaar. 2002. Wavefield extrapolation and prestack depth migration in anelastic inhomogeneous media. Geophysical Prospecting50: 629–43. doi: 10.1046/j.1365‑2478.2002.00342.x
     https://doi.org/10.1046/j.1365-2478.2002.00342.x [Google Scholar]
  41. Zhang, J., J.Wu, and X.Li. 2013. Compensation for absorption and dispersion in prestack migration: an effective Q approach. Geophysics78: S1–S14. doi: 10.1190/geo2012‑0128.1
     https://doi.org/10.1190/geo2012-0128.1 [Google Scholar]
  42. Zhang, Y., P.Zhang, and H.Zhang. 2010. Compensating for visco-acoustic effects in reverse-time migration. SEG Technical Program Expanded Abstracts, 3160–4.
  43. Zhao, Z., and M.K.Sen. 2019. Frequency domain double plane wave least squares reverse time migration. Geophysical Prospecting67: 2061–84. doi: 10.1111/1365‑2478.12803
     https://doi.org/10.1111/1365-2478.12803 [Google Scholar]
  44. Zhu, T.2014. Time-reverse modelling of acoustic wave propagation in attenuating media. Geophysical Journal International197: 483–94. doi: 10.1093/gji/ggt519
     https://doi.org/10.1093/gji/ggt519 [Google Scholar]
/content/journals/10.1080/08123985.2020.1844543
Loading
An adaptive stability condition for Q migration in the frequency domain based on the GSLS model
Exploration Geophysics 52, 525 (2021); https://doi.org/10.1080/08123985.2020.1844543
/content/journals/10.1080/08123985.2020.1844543
/content/journals/10.1080/08123985.2020.1844543
Loading

Data & Media loading...

  • Article Type: Research Article
Keyword(s): Attenuation; frequency domain; high-resolution; migration; Q; reverse-time

Most Cited This Month Most Cited RSS feed

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