1887
Volume 52, Issue 2
  • ISSN: 0812-3985
  • E-ISSN: 1834-7533

Abstract

Full waveform inversion (FWI) is an efficient tool to build the subsurface velocity models. However conventional FWI suffers from the cycle skipping problem, which causes FWI to fail in converging to the global minimum. A good initial model can mitigate this problem, but it is hard to be provided. Low frequencies in the observed data are helpful to recover the low-wavenumber components of the subsurface velocity models, which can provide good initial models. However, field data usually lack low frequencies because of the physical limitation of the instruments or the environmental noise. In addition, multiscale approach may not work well to tackle the cycle skipping problem when there isn’t sufficient low-frequency information in the observed data. Therefore, we proposed an amplitude increment coding-based data selection method to find which parts of the data are mismatched, and set these parts of data to 0 to mitigate the cycle skipping problem. In this case, we use the global-correlation misfit function which behaves better in mitigating the interference of the incorrect amplitude information and highlighting the phase information with weaker nonlinearity. In addition, the amplitude increment coding-based data selection method can be combined with the encoded blended-source scheme to improve computational efficiency. Numerical tests on Marmousi model demonstrate that FWI with an amplitude increment-based data selection method can generate convergent results when the observed data lack low frequencies.

© 2020 Australian Society of Exploration Geophysicists
Loading

Article metrics loading...

/content/journals/10.1080/08123985.2020.1795638
2021-03-04
2026-01-13

  • From This Site

    /content/journals/10.1080/08123985.2020.1795638
    dcterms_title,dcterms_subject,pub_keyword
    -contentType:Journal -contentType:Contributor -contentType:Concept -contentType:Institution
    10
    5
Loading full text...

Full text loading...

References

  1. Alkhalifah, T., and Y.Choi. 2014. From tomography to full-waveform inversion with a single objective function. Geophysics79: R55–61. doi:10.1190/geo2013-0291.1.
     [Google Scholar]
  2. Bai, J., D.Yingst, R.Bloor, and J.Leveille. 2014. Viscoacoustic waveform inversion of velocity structures in the time domain. Geophysics79: R103–19. doi:10.1190/geo2013-0030.1.
     [Google Scholar]
  3. Biondi, B., and W.W.Symes. 2004. Angle-domain common-image gathers for migration velocity analysis by wavefield-continuation imaging. Geophysics69: 1283–98. doi:10.1190/1.1801945.
     [Google Scholar]
  4. Bishop, T.N., K.P.Bube, R.T.Cutler, R.T.Langan, P.L.Love, J.R.Resnick, R.T.Shuey, D.A.Spindler, and H.W.Wyld. 1985. Tomographic determination of velocity and depth in laterally varying media. Geophysics50: 903–23. doi:10.1190/1.1441970.
     [Google Scholar]
  5. Boonyasiriwat, C., and G.Schuster. 2010. 3D multisource full-waveform inversion using dynamic random phase encoding. SEG Technical Program Expanded Abstracts2010, doi:10.1190/1.3513025.
     [Google Scholar]
  6. Bozdağ, E., J.Trampert, and J.Tromp. 2011. Misfit functions for full waveform inversion based on instantaneous phase and envelope measurements. Geophysical Journal International185: 845–70. doi:10.1111/j.1365-246X.2011.04970.x.
     [Google Scholar]
  7. Bunks, G., F.M.Saleck, S.Zaleski, and G.Chavent. 1995. Multiscale seismic waveform inversion. Geophysics60: 1457–73. doi:10.1190/1.1443880.
     [Google Scholar]
  8. Chi, B., L.Dong, and Y.Liu. 2014. Full waveform inversion method using envelope objective function without low frequency data. Journal of Applied Geophysics109: 36–46. doi:10.1016/j.jappgeo.2014.07.010.
     [Google Scholar]
  9. Choi, Y., and T.Alkhalifah. 2011. Source-independent time-domain waveform inversion using convolved wavefields: Application to the encoded multisource waveform inversion. Geophysics76: R125–34. doi:10.1190/geo2010-0210.1.
     [Google Scholar]
  10. Choi, Y., and T.Alkhalifah. 2012. Application of multi-source waveform inversion to marine streamer data using the global correlation norm. Geophysical Prospecting60: 748–58. doi:10.1111/j.1365-2478.2012.01079.x.
     [Google Scholar]
  11. Choi, Y., and T.Alkhalifah. 2018. Time-domain full-waveform inversion of exponentially damped wavefield using the deconvolution-based objective function. Geophysics83: R77–88. doi:10.1190/geo2017-0057.1.
     [Google Scholar]
  12. Datta, D., and M.K.Sen. 2016. Estimating a starting model for full-waveform inversion using a global optimization method. Geophysics81: R211–23. doi:10.1190/geo2015-0339.1.
     [Google Scholar]
  13. Dong, S., L.Han, Y.Hu, and Y.Yin. 2020. Full waveform inversion based on a local traveltime correction and 0-mean cross-correlation-based misft function. Acta Geophysica68: 29–50. doi:10.1007/s11600-019-00388-x.
     [Google Scholar]
  14. Engquist, B., B.D.Froese, and Y.Yang. 2016. Optimal transport for seismic full waveform inversion. Communications in Mathematical Sciences14: 2309–30. doi:10.4310/CMS.2016.v14.n8.a9.
     [Google Scholar]
  15. Gauthier, O., J.Virieux, and A.Tarantola. 1986. Two-dimensional nonlinear inversion of seismic waveforms: numerical results. Geophysics51: 1387–403. doi:10.1190/1.1442188.
     [Google Scholar]
  16. Hu, W.2014. FWI without low frequency data-beat tone inversion. SEG Technical Program Expanded Abstracts2014, doi:10.1190/segam2014-0978.1.
     [Google Scholar]
  17. Hu, Y., L.Han, P.Zhang, and Q.Ge. 2018. Time-frequency domain multi-scale full waveform inversion based on adaptive non-stationary phase correction. EAGE Technical Program Extended Abstracts2018, doi:10.3997/2214-4609.201800891.
     [Google Scholar]
  18. Justice, J.H., A.A.Vassiliou, S.Singh, J.D.Logel, P.A.Hansen, B.R.Hall, P.R.Hutt, and J.J.Solanki. 1989. Acoustic tomography for enhancing oil recovery. The Leading Edge8: 12–19. doi:10.1190/1.1439605.
     [Google Scholar]
  19. Kaneko, S., I.Murase, and S.Igarashi. 2002. Robust image registration by increment sign correlation. Pattern Recognition35 no. 10: 2223–34. doi:10.1016/s0031-3203(01)00177-7.
     [Google Scholar]
  20. Krebs, J.R., J.E.Anderson, D.Hinkley, R.Neelamani, S.Lee, A.Baumstein, and M.-D.Lacasse. 2009. Fast full-wavefield seismic inversion using encoded sources. Geophysics74: WCC177–88. doi:10.1190/1.3230502.
     [Google Scholar]
  21. Lailly, P.1983. The seismic inverse problem as a sequence of before stack migrations. Conference on Inverse Scattering: Theory and Application, 206–20, SIAM, Philadelphia, USA.
  22. Lee, K.H., and H.J.Kim. 2003. Source-independent full-waveform inversion of seismic data. Geophysics68: 2010–15. doi:10.1190/1.1635054.
     [Google Scholar]
  23. Leung, S., and J.Qian. 2006. An adjoint state method for three-dimensional transmission traveltime tomography using first-arrivals. Communications in Mathematical Sciences4 no. 1: 249–66. doi:10.4310/CMS.2006.v4.n1.a10.
     [Google Scholar]
  24. Li, Y., Y.Choi, T.Alkhalifah, Z.Li, and K.Zhang. 2018. Full-waveform inversion using a nonlinearly smoothed wavefield. Geophysics83: R117–27. doi:10.1190/geo2017-0312.1.
     [Google Scholar]
  25. Liu, Y., B.He, H.Lu, Z.Zhang, B.Xiao, and Y.Zheng. 2018. Full-intensity waveform inversion. Geophysics83 no. 6: R649–58. doi:10.1190/GEO2017-0682.1.
     [Google Scholar]
  26. Liu, Y., J.Teng, T.Xu, Y.Wang, Q.Liu, and J.Badal. 2017. Robust time-domain full waveform inversion with normalized zero-lag cross-correlation objective function. Geophysical Journal International209: 106–22. doi:10.1093/gji/ggw485.
     [Google Scholar]
  27. Luo, Y., and G.T.Schuster. 1991. Wave-equation traveltime inversion. Geophysics56: 645–53. doi:10.1190/1.1443081.
     [Google Scholar]
  28. Luo, J., and R.-S.Wu. 2015. Seismic envelope inversion: Reduction of local minima and noise resistance. Geophysical Prospecting63: 597–614. doi:10.1111/1365-2478.12208.
     [Google Scholar]
  29. Ma, Y., Y.Wu, L.Cao, Y.Luo, and H.Liu. 2016. Full-traveltime inversion. Geophysics81 no. 5: R261–74. doi:10.1190/segam2016-13780303.1.
     [Google Scholar]
  30. MoghaddamP., P., H.Keers, F.Herrmann, and W.Mulder. 2013. A new optimization approach for source-encoding full-waveform inversion. Geophysics78 no. 3: R125–32. doi:10.1190/geo2012-0090.1.
     [Google Scholar]
  31. Pan, W., and L.Huang. 2018. Elastic-wave-equation traveltime tomography in anisotropic media using differential measurements of long-offset data. SEG Technical Program Expanded Abstracts2018: 5233–7. doi:10.1190/segam2018-2997226.1.
     [Google Scholar]
  32. Sajeva, A., M.Aleardi, E.Stucchi, N.Bienati, and A.Mazzotti. 2016. Estimation of acoustic macro models using a genetic full-waveform inversion: Applications to the Marmousi model. Geophysics81: R173–84. doi:10.1190/geo2015-0198.1.
     [Google Scholar]
  33. Schuster, G.T., X.Wang, Y.Huang, W.Dai, and C.Boonyasiriwat. 2011. Theory of multisource crosstalk reduction by phase-encoded statics. Geophysical Journal International184: 1289–303. doi:10.1111/j.1365-246X.2010.04906.x.
     [Google Scholar]
  34. Shin, C., and Y.Ho Cha. 2009. Waveform inversion in the Laplace-Fourier domain. Geophysical Journal International177: 1067–79. doi:10.1111/j.1365-246X.2009.04102.x.
     [Google Scholar]
  35. Sun, B., and T.Alkhalifah. 2019. Adaptive traveltime inversion. Geophysics84: U13–29. doi:10.1190/geo2018-0595.1.
     [Google Scholar]
  36. Sun, H., and L.Demanet. 2018. Low frequency extrapolation with deep learning. SEG Technical Program Expanded Abstracts2018, doi:10.1190/segam2018-2997928.1.
     [Google Scholar]
  37. Symes, W.W.2008. Migration velocity analysis and waveform inversion. Geophysical Prospecting56: 765–90. doi:10.1111/j.1365-2478.2008.00698.x.
     [Google Scholar]
  38. Symes, W.W., and J.J.Carazzone. 1991. Velocity inversion by differential semblance optimization. Geophysics56: 654–63. doi:10.1190/1.1443082.
     [Google Scholar]
  39. Tarantola, A.1984. Linearized inversion of seismic reflection data. Geophysical Prospecting32: 998–1015. doi:10.1111/j.1365-2478.1984.tb00751.x.
     [Google Scholar]
  40. Virieux, J., and S.Operto. 2009. An overview of full-waveform inversion in exploration geophysics. Geophysics74: WCC1–26. doi:10.1190/1.3238367.
     [Google Scholar]
  41. Wang, G., S.Yuan, and S.Wang. 2019. Retrieving low-wavenumber information in FWI: An efficient solution for cycle skipping. IEEE Geoscience and Remote Sensing Letters16: 1125–29. doi:10.1109/lgrs.2019.2892998.
     [Google Scholar]
  42. Wang, M., Y.Xie, W.Xu, K.Xin, B.Chuah, F.Loh, T.Manning, and S.Wolfarth. 2016. Dynamic-warping full-waveform inversion to overcome cycle skipping. SEG Technical Program Expanded Abstracts2016, doi:10.1190/segam2016-13855951.1.
     [Google Scholar]
  43. Warner, M., and L.Guasch. 2014. Adaptive waveform inversion: theory. SEG Technical Program Expanded Abstracts2014, doi:10.1190/segam2014-0371.1.
     [Google Scholar]
  44. Wu, R.-S., J.Luo, and B.Wu. 2014. Seismic envelope inversion and modulation signal model. Geophysics79: WA13–24. doi:10.1190/geo2013-0294.1.
     [Google Scholar]
  45. Xu, S., D.Wang, F.Chen, Y.Zhang, and G.Lambare. 2012. Full waveform inversion for reflected seismic data. EAGE Technical Program Extended Abstracts2012, doi:10.3997/2214-4609.20148725.
     [Google Scholar]
  46. Xuan, Y., Z.Zhang, Y.Hu, and L.Han. 2017. Adaptive full-waveform inversion based on nonstationary phase correction in TTI media. SEG Technical Program Expanded Abstracts2017, doi:10.1190/segam2017-17731894.1.
     [Google Scholar]
  47. Zhang, P., L.Han, Z.Xu, F.Zhang, and Y.Wei. 2017. Sparse blind deconvolution based low-frequency seismic data reconstruction for multiscale full waveform inversion. Journal of Applied Geophysics139: 91–108. doi:10.1016/j.jappgeo.2017.02.021.
     [Google Scholar]
  48. Zhang, P., R.-S.Wu, and L.Han. 2018. Source-independent seismic envelope inversion based on the direct envelope Fréchet derivative. Geophysics80 no. 6: R581–95. doi:10.1190/geo2017-0360.1.
     [Google Scholar]
  49. Zhang, P., R.-S.Wu, and L.Han. 2019. Seismic envelope inversion based on hybrid scale separation for data with strong noises. Pure and Applied Geophysics176: 165–88. doi:10.1007/s00024-018-2025-4.
     [Google Scholar]
  50. Zhou, B., and S.A.Greenhalgh. 2003. Crosshole seismic inversion with normalized full-waveform amplitude data. Geophysics68: 1320–30. doi:10.1190/1.1598125.
     [Google Scholar]
  51. Zhou, C., G.Schuster, and S.Hassanzadeh. 1994. Elastic wave equation travel time and waveform inversion of crosshole seismic data. Geophysics60 no. 3: 765–73. doi:10.4133/1.2922126.
     [Google Scholar]
  52. Zhu, H., and S.Fomel. 2016. Building good starting models for full-waveform inversionusing adaptive matching filtering misfit. Geophysics81: U61–72. doi:10.1190/geo2015-0596.1.
     [Google Scholar]
/content/journals/10.1080/08123985.2020.1795638
Loading
Full waveform inversion with an amplitude increment coding-based data selection
Exploration Geophysics 52, 189 (2021); https://doi.org/10.1080/08123985.2020.1795638
/content/journals/10.1080/08123985.2020.1795638
/content/journals/10.1080/08123985.2020.1795638
Loading

Data & Media loading...

  • Article Type: Research Article
Keyword(s): Acoustic; amplitude; full waveform; inversion; time-domain

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