1887
Volume 50, Issue 2
  • ISSN: 0812-3985
  • E-ISSN: 1834-7533

Abstract

ABSTRACT

Full waveform inversion (FWI) using passive seismic data can use amplitude, phase and travel time information from the data simultaneously. However, at least three challenges are involved in passive seismic full waveform inversion (PSFWI): a low signal-to-noise ratio (SNR), source location uncertainty and an unknown source wavelet. In this study, we propose a method that combines seismic interferometry and a source-independent inversion algorithm to solve these problems. Using seismic interferometry, the original passive seismic data recorded on the surface can be reconstructed into new virtual source records that have a relatively high SNR and certain source location. The source-independent algorithm eliminates the influence of source wavelet error on the final inversion results. Through numerical tests, we discuss the effects of passive source number and recording time on the inversion results and find that increasing the source number or recording time can improve inversion quality. We extract the background velocity model from the results of PSFWI and use it as the initial model of active source FWI. Least square reverse time migration (LSRTM) is then conducted to verify the accuracy of the inverted velocity models. The final results demonstrate that our PSFWI method can construct accurate long-wavelength velocity structures for subsequent active source FWI. The velocity model constructed using our successive inversion strategy can improve the LSRTM results.

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/content/journals/10.1080/08123985.2019.1575644
2019-03-04
2026-01-23
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References

  1. Alali, A., J. Neut, and D. Draganov 2016 Merging active and passive seismic reflection data with interferometry by multidimensional deconvolution. 86th SEG annual meeting, Expanded Abstracts, 5182–186.
    [Google Scholar]
  2. Ali, M.Y., K.A. Berteussen, J. Small, and B. Barkat 2010 Low-frequency passive seismic experiments in Abu Dhabi, United Arab Emirates: implications for hydrocarbon detection. Geophysical Prospecting58: 875–99.
    [Google Scholar]
  3. Berkhout, A.J., and D.J. Verschuur 2009 Integrated imaging with active and passive seismic data. 79th SEG annual meeting, Expanded Abstracts, 1592–6.
    [Google Scholar]
  4. Berkhout, A.J., and D.J. Verschuur 2011 A scientific framework for active and passive seismic imaging, with applications to blended data and micro-earthquake responses. Geophysical Journal International184: 777–92.
    [Google Scholar]
  5. Boullenger, B., A. Verdel, B. Paap, J. Thorbecke, and D. Draganov 2015 Studying CO2 storage with ambient-noise seismic interferometry: A combined numerical feasibility study and field-data example for Ketzin, Germany. Geophysics80, no. 1: Q1–13.
    [Google Scholar]
  6. Chávez-García, F.J., and T. Yokoi 2016 High lateral resolution exploration using surface waves from noise records. Exploration Geophysics47: 123–32.
    [Google Scholar]
  7. Chen, J., and C.A. Zelt 2016 Application of frequency-dependent traveltime tomography and full waveform inversion to realistic near-surface seismic refraction data. Journal of Environmental and Engineering Geophysics21, no. 1: 1–12.
    [Google Scholar]
  8. Chen, J., C.A. Zelt, and P. Jaiswal 2017 Detecting a known near-surface target through application of frequency-dependent traveltime tomography and full-waveform inversion to P-and SH-wave seismic refraction data. Geophysics82, no. 1: R1–17.
    [Google Scholar]
  9. Cheraghi, S., D.J. White, D. Draganov, G. Bellefleur, J.A. Craven, and B. Roberts 2017 Passive seismic reflection interferometry: A case study from the Aquistore CO2 storage site, Saskatchewan, Canada. Geophysics82, no. 3: B79–93.
    [Google Scholar]
  10. Choi, Y., and T. Alkhalifah 2011 Source-independent time-domain waveform inversion using convolved wavefields: Application to the encoded multisource waveform inversion. Geophysics76, no. 5: R125–34.
    [Google Scholar]
  11. Claerbout, J.F. 1968 Synthesis of a layered medium from its acoustic transmission response. Geophysics33, no. 2: 264–9.
    [Google Scholar]
  12. Delaney, E., L. Ermert, K. Sager, A. Kritski, S. Bussat, and A. Fichtner 2017 Passive seismic monitoring with nonstationary noise sources. Geophysics82, no. 4: KS57–70.
    [Google Scholar]
  13. Draganov, D., K. Wapenaar, and J. Thorbecke 2006 Seismic interferometry: Reconstructing the earth’s reflection responses. Geophysics71, no. 4: SI61–70.
    [Google Scholar]
  14. Draganov, D., K. Wapenaar, W. Mulder, J. Singer, and A. Verdel 2007 Retrieval of reflections from seismic background-noise measurements. Geophysical Research Letters34: L04305.
    [Google Scholar]
  15. Draganov, D., X. Campman, J. Thorbecke, A. Verdel, and K. Wapenaar 2009 Reflection images from ambient seismic noise. Geophysics74, no. 5: A63–7.
    [Google Scholar]
  16. Forgues, E., E. Schissele-Rebel, and J. Cotton 2011 Simultaneous active/passive seismic monitoring of steam assisted heavy oil production. 81th SEG annual meeting, Expanded Abstracts, 4082–6.
    [Google Scholar]
  17. Gao, W., M.D. Sacchi, and Z. Li 2017 Microseismic source location via elastic least squares full waveform inversion with a group sparsity constraint. 87th SEG annual meeting, Expanded Abstracts, 2814–9.
    [Google Scholar]
  18. Goertz, A., B. Schechinger, B. Witten, M. Koerbe, and P. Krajewski 2012 Extracting subsurface information from ambient seismic noise – A case study from Germany. Geophysics77, no. 4: KS13–31.
    [Google Scholar]
  19. Hayashi, K. 2017 Application of active and passive surface wave methods to shallow to deep S-wave velocity estimation. 87th SEG annual meeting, Expanded Abstracts, 5202–6.
    [Google Scholar]
  20. James, S.R., H.A. Knox, L. Preston, J.M. Knox, M.C. Grubelich, D.K. King, J.B. Ajo-Franklin, T.C. Johnson, and J.P. Morris 2017 Fracture detection and imaging through relative seismic velocity changes using distributed acoustic sensing and ambient seismic noise. The Leading Edge36, no. 12: 1009–17.
    [Google Scholar]
  21. Kaderli, J., M. McChesney, and S.E. Minkoff 2015 Microseismic event estimation in noisy data via full waveform inversion. 85th SEG annual meeting, Expanded Abstracts, 1159–64.
    [Google Scholar]
  22. Kamei, R., and D. Lumley 2014 Passive seismic imaging and velocity inversion using full wavefield methods. 84th SEG annual meeting, Expanded Abstracts, 2273–77.
    [Google Scholar]
  23. Lee, K.H., and H.J. Kim 2003 Source-independent full-waveform inversion of seismic data. Geophysics68: 2010–15.
  24. Michel, O.J., and I. Tsvankin 2013 Gradient computation for full-waveform inversion of microseismic data in VTI media. 83th SEG annual meeting, Expanded Abstracts, 2238–42.
    [Google Scholar]
  25. Mora, P. 1987 Nonlinear two-dimensional elastic inversion of multioffset seismic data. Geophysics52, no. 9: 1211–28.
    [Google Scholar]
  26. Olivier, G., F. Brenguier, M. Campillo, R. Lynch, and P. Roux 2015 Body-wave reconstruction from ambient seismic noise correlations in an underground mine. Geophysics80, no. 3: KS11–25.
    [Google Scholar]
  27. Olofsson, B. 2010 Marine ambient seismic noise in the frequency range 1-10Hz. The Leading Edge29, no. 4: 418–35.
    [Google Scholar]
  28. Panea, I., V. Mocanu, and C. Lacob 2012 Analysis of passive surface waves from ambient-noise recordings. The Leading Edge31, no. 12: 1484–88.
    [Google Scholar]
  29. Park, C.B., R.D. Miller, N. Ryden, J. Xia, and J. Ivanov 2005 Combined use of active and passive surface waves. Journal of Environmental and Engineering Geophysics10, no. 3: 323–34.
    [Google Scholar]
  30. Plessix, R.E. 2006 A review of the adjoint-state method for computing the gradient of a functional with geophysical applications. Geophysical Journal International167: 495–503.
    [Google Scholar]
  31. Sager, K., L. Ermert, C. Boehm, and A. Fichtner 2018 Towards full waveform ambient noise inversion. Geophysical Journal International212: 566–90.
    [Google Scholar]
  32. Schuster, G.T., and Y. Luo 1991 Wave-equation traveltime inversion. Geophysics56, no. 5: 645–53.
    [Google Scholar]
  33. Schuster, G.T., and J. Rickett 2001 Daylight imaging in V(x,y,z) media. Stanford Exploration Project, Report SEP-105, 209–27.
    [Google Scholar]
  34. Sethi, H.S., and B. Shekar 2017 Full waveform inversion for microseismic events using sparsity constraints. 87th SEG annual meeting, Expanded Abstracts, 2888–92.
    [Google Scholar]
  35. Sheng, J., A. Leeds, M. Buddensiek, and G.T. Schuster 2006 Early arrival waveform tomography on near-surface refraction data. Geophysics71, no. 4: U47–57.
    [Google Scholar]
  36. Sun, J., Z. Xue, T. Zhu, et al. 2016 Full waveform inversion of passive seismic data for sources and velocities. 86th SEG annual meeting, Expanded Abstracts, 1405–10.
    [Google Scholar]
  37. Thorbecke, J.W., and D. Draganov 2011 Finite-difference modeling experiments for seismic interferometry. Geophysics76, no. 6: H1–18.
    [Google Scholar]
  38. Tarantola, A. 1984 Inversion of seismic reflection data in the acoustic approximation. Geophysics49, no. 8: 1259–1266.
    [Google Scholar]
  39. Vesnaver, A., L. Lovisa, and G. Bohm 2010 Joint 3D processing of active and passive seismic data. Geophysical Prospecting58: 831–44.
    [Google Scholar]
  40. Virieux, J., and S. Operto 2009 An overview of full waveform inversion in exploration geophysics. Geophysics74, no. 6: WCC1–26.
    [Google Scholar]
  41. Wang, H., and T. Alkhalifah 2016 Micro-seismic imaging using a source independent full waveform inversion method. 86th SEG annual meeting, Expanded Abstracts, 2596–600.
    [Google Scholar]
  42. Wapenaar, K., and J. Fokkema 2006 Green’s function representations for seismic interferometry. Geophysics71, no. 4: SI33–46.
    [Google Scholar]
  43. Wapenaar, K., J. Neut, and E. Ruigrok 2008 Passive seismic interferometry by multi-dimensional deconvolution. Geophysics73, no. 6: A51–6.
    [Google Scholar]
  44. Wapenaar, K., J. Neut, E. Ruigrok, D. Draganov, J. Hunziker, E. Slob, J. Thorbecke, and R. Snieder 2011 Seismic interferometry by crosscorrelation and multidimensional deconvolution, a systematic comparison. Geophysical Journal International185: 1335–64.
    [Google Scholar]
  45. Wu, R.S., J. Luo, and B. Wu 2014 Seismic envelope inversion and modulation signal model. Geophysics79, no. 3: WA13–24.
    [Google Scholar]
  46. Xu, Y., B. Zhang, Y. Luo, and J. Xia 2013 Surface-wave observation after integrating active and passive source data. The Leading Edge32, no. 6: 634–7.
    [Google Scholar]
  47. Zelt, C.A., and J. Chen 2016 Frequency-dependent traveltime tomography for near-surface seismic refraction data. Geophysical Journal International207: 72–88.
    [Google Scholar]
  48. Zhang, P., L. Han, Q. Liu, Z. Ya-Hong, and C. Xue 2015a Interpolation of seismic data from active and passive sources and their joint migration imaging. Chinese Journal of Geophysics(in Chinese)58, no. 5: 1754–66.
    [Google Scholar]
  49. Zhang, P., L. Han, Y. Zhou, Z. Xu, and Q.-X. Ge 2015b Passive-source multitaper-spectral method based low-frequency data reconstruction for active seismic sources. Applied Geophysics12, no. 4: 585–97.
    [Google Scholar]
  50. Zhang, P., L. Han, H. Gao, et al. 2015c Genetic algorithm full waveform inversion for microseismic location. 85th SEG annual meeting, Expanded Abstracts, 2650–4.
    [Google Scholar]
  51. Zhang, P., L. Han, Z. Jin, et al. 2016 Passive source illumination compensation based full waveform inversion. 78th EAGE Conference & Exhibition, Expanded Abstracts, Th SP1 05.
    [Google Scholar]
  52. 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.
    [Google Scholar]
  53. Zhang, P., L. Han, X. Gong, H. Sun, and B. Mao 2018 Multi-source elastic full waveform inversion based on the anisotropic total variation constraint. Chinese Journal of Geophysics(in Chinese)61, no. 2: 716–32.
    [Google Scholar]
  54. Zhang, X., W. Zhang, and J. Zhang 2014 Elastic full waveform inversion of microseismic data for location and source mechanism. 84th SEG annual meeting, Expanded Abstracts, 2256–60.
    [Google Scholar]
  55. Zhou, C., W. Cai, Y. Luo, G.T. Schuster, and S. Hassanzadeh 1995 Acoustic wave-equation traveltime and waveform inversion of crosshole seismic data. Geophysics60, no. 3: 765–73.
    [Google Scholar]
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