1887
Volume 63 Number 1
  • E-ISSN: 1365-2478

Abstract

ABSTRACT

Full‐waveform inversion is an appealing technique for time‐lapse imaging, especially when prior model information is included into the inversion workflow. Once the baseline reconstruction is achieved, several strategies can be used to assess the physical parameter changes, such as parallel difference (two separate inversions of baseline and monitor data sets), sequential difference (inversion of the monitor data set starting from the recovered baseline model) and double‐difference (inversion of the difference data starting from the recovered baseline model) strategies. Using synthetic Marmousi data sets, we investigate which strategy should be adopted to obtain more robust and more accurate time‐lapse velocity changes in noise‐free and noisy environments. This synthetic application demonstrates that the double‐difference strategy provides the more robust time‐lapse result. In addition, we propose a target‐oriented time‐lapse imaging using regularized full‐waveform inversion including a prior model and model weighting, if the prior information exists on the location of expected variations. This scheme applies strong prior model constraints outside of the expected areas of time‐lapse changes and relatively less prior constraints in the time‐lapse target zones. In application of this process to the Marmousi model data set, the local resolution analysis performed with spike tests shows that the target‐oriented inversion prevents the occurrence of artefacts outside the target areas, which could contaminate and compromise the reconstruction of the effective time‐lapse changes, especially when using the sequential difference strategy. In a strongly noisy case, the target‐oriented prior model weighting ensures the same behaviour for both time‐lapse strategies, the double‐difference and the sequential difference strategies and leads to a more robust reconstruction of the weak time‐lapse changes. The double‐difference strategy can deliver more accurate time‐lapse variation since it can focus to invert the difference data. However, the double‐difference strategy requires a preprocessing step on data sets such as time‐lapse binning to have a similar source/receiver location between two surveys, while the sequential difference needs less this requirement. If we have prior information about the area of changes, the target‐oriented sequential difference strategy can be an alternative and can provide the same robust result as the double‐difference strategy.

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/content/journals/10.1111/1365-2478.12176
2014-10-14
2024-03-29
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References

  1. AbubakarA., HuW., HabashyT.M. and van den BergP.M.2009. Application of the finite‐difference contrast‐source inversion algorithm to seismic full‐waveform data. Geophysics74(6), WCC47–WCC58.
    [Google Scholar]
  2. AsnaashariA., BrossierR., GaramboisS., AudebertF., ThoreP., and VirieuxJ.2011. Sensitivity analysis of time‐lapse images obtained by differential waveform inversion with respect to reference model. SEG Technical Program Expanded Abstracts30(1), 2482–2486.
    [Google Scholar]
  3. AsnaashariA., BrossierR., GaramboisS., AudebertF., ThoreP. and VirieuxJ.2012. Time‐lapse imaging using regularized FWI: a robustness study. SEG Technical Program Expanded Abstracts31(1), 1–5.
    [Google Scholar]
  4. AsnaashariA., BrossierR., GaramboisS., AudebertF., ThoreP. and VirieuxJ.2013. Regularized seismic Full‐waveform inversion with prior model information. Geophysics78(2), R25–R36.
    [Google Scholar]
  5. AyeniG. and BiondiB.2010. Target‐oriented joint least‐squares migration/inversion of time‐lapse seismic data sets. Geophysics75(3), R61–R73.
    [Google Scholar]
  6. BansalR., RouthP., KrebsJ.LeeS., BaumsteinA., AndersonJ., et al. 2013. Full wavefield inversion of ocean bottom node data. EAGE Technical Program Expanded Abstracts 2013, We1104.
    [Google Scholar]
  7. BerengerJ‐P.1994. A perfectly matched layer for absorption of electromagnetic waves. Journal of Computational Physics114, 185–200.
    [Google Scholar]
  8. BrossierR., OpertoS. and VirieuxJ.2009. Seismic imaging of complex onshore structures by 2D elastic frequency‐domain full‐waveform inversion. Geophysics74(6), WCC105–WCC118.
    [Google Scholar]
  9. BunksC., SalekF.M., ZaleskiS. and ChaventG.1995. Multiscale seismic waveform inversion. Geophysics60(5), 1457–1473.
    [Google Scholar]
  10. ByrdR.H., LuP. and NocedalJ.1995. A limited memory algorithm for bound constrained optimization. SIAM Journal on Scientific and Statistical Computing16, 1190–1208.
    [Google Scholar]
  11. CalvertR.2005. Insights and methods for 4D reservoir monitoring and characterization. SEG Distinguished Instructor Series No. 8.
  12. CohenJ.K. and Stockwell, Jr.J.W.2008. CWP/SU: Seismic Unix release No. 41: an open source software package for seismic research and processing. Center for Wave Phenomena, Colorado School of Mines.
  13. Day‐LewisF.D., HarrisJ.M. and GorelickS.M.2002. Time‐lapse inversion of crosswell radar data. Geophysics67(6), 1740–1752.
    [Google Scholar]
  14. Day‐LewisF.D., Lane, Jr.J.W.J., HarrisJ.M. and GorelickS.M.2003. Time‐lapse imaging of saline‐tracer transport in fractured rock using difference‐attenuation radar tomography. Water Resources Research, 39(10), 1290.
    [Google Scholar]
  15. DenliH. and HuangL.2009. Double‐difference elastic waveform tomography in the time domain. SEG Technical Program Expanded Abstracts28(1), 2302–2306.
    [Google Scholar]
  16. FangY., CheneyM. and RoeckerR.2010. Imaging from sparse measurements. Geophysical Journal International180(3), 1289–1302.
    [Google Scholar]
  17. FichtnerA. and TrampertJ.2011. Resolution analysis in full waveform inversion. Geophysical Journal International187, 1604–1624.
    [Google Scholar]
  18. GosseletA. and SinghS.2008. 2D full waveform inversion in time‐lapse mode: CO2 quantification at Sleipner. EAGE 70th Conference and Exhibition, Expanded abstracts, W075.
    [Google Scholar]
  19. GotJ.L., MonteillerV., VirieuxJ. and OpertoS.2008. Potential and limits of double‐difference tomographic methods. Geophysical Prospecting56(4), 477–491.
    [Google Scholar]
  20. GuittonA.2011. A blocky regularization scheme for full waveform inversion. SEG Technical Program Expanded Abstracts30(1), 2418–2422.
    [Google Scholar]
  21. HallS.A.2006. A methodology for 7D warping and deformation monitoring using time‐lapse seismic data. Geophysics71(4), O21–O31.
    [Google Scholar]
  22. HerrmannF.J., ErlanggaY.A. and LinT.T.Y.2009. Compressive simultaneous full‐waveform simulation. Geophysics74(4), A35–A40.
    [Google Scholar]
  23. HuW., AbubakarA. and HabashyT.M.2009. Simultaneous multifrequency inversion of full‐waveform seismic data. Geophysics, 74(2), R1–R14.
    [Google Scholar]
  24. LandrøM.2001. Discrimination between pressure and fluid saturation changes from time‐lapse seismic data. Geophysics66(3), 836–844.
    [Google Scholar]
  25. Le StunffY. and GrenierD.1998. Taking into account a priori information in 3D tomography. SEG Technical Program Expanded Abstracts, Vol. 17, 1875–1878.
    [Google Scholar]
  26. LiangL., AbubakarA. and HabashyT.M.2012. Joint inversion of time‐lapse crosswell electromagnetic, seismic, and production data for reservoir monitoring and characterization. SEG Technical Program Expanded Abstracts, Vol. 31(1), 1–7.
    [Google Scholar]
  27. LorisI., DoumaH., NoletG., DaubechiesI. and RegoneC.2010. Nonlinear regularization techniques for seismic tomography. Journal of Computational Physics229, 890–905.
    [Google Scholar]
  28. LuR., LazaratosS., WangK., ChaY.H., ChikichevI. and ProsserR.2013. High‐resolution elastic FWI for reservoir characterization. EAGE Technical Program Expanded Abstracts 2013, Th1002.
    [Google Scholar]
  29. LumleyD., AdamsD., WrightR., MarkusD. and ColeS.2008. Seismic monitoring of CO2 geo‐sequestration: realistic capabilities and limitations. SEG Technical Program Expanded Abstracts, vol. 27(1), 2841–2845.
    [Google Scholar]
  30. LumleyD.E.2001. Time‐lapse seismic reservoir monitoring. Geophysics66(1), 50–53.
    [Google Scholar]
  31. MaY., HaleD., GongB. and MengZ. (Joe)2012. Image‐guided sparse‐model full waveform inversion. Geophysics77(4), R189–R198.
    [Google Scholar]
  32. MartinG.S., WileyR. and MarfurtK.J.2006. Marmousi2: An elastic upgrade for Marmousi. The Leading Edge25(2), 156–166.
    [Google Scholar]
  33. MenkeW.1984. Geophysical Data Analysis: Discrete Inverse Theory. Academic Press, Inc., Orlando, USA.
    [Google Scholar]
  34. MillerC.R., RouthP.S., BrostenT.R. and McNamaraJ.P.2008. Application of time‐lapse ERT imaging to watershed characterization. Geophysics73(3), G7–G17.
    [Google Scholar]
  35. MonteillerV., GotJ.‐L., VirieuxJ. and OkuboP.2005. An efficient algorithm for double‐difference tomography and location in heterogeneous media, with an application to the Kilauea volcano. Journal of Geophysical Research110(B12306).
    [Google Scholar]
  36. OldenborgerG.A., KnollM., RouthP. and LaBrecqueD.2007. Time‐lapse ERT monitoring of an injection/withdrawal experiment in a shallow unconfined aquifer. Geophysics72(4), F177–F187.
    [Google Scholar]
  37. PlessixR.E.2006. A review of the adjoint‐state method for computing the gradient of a functional with geophysical applications. Geophysical Journal International167(2), 495–503.
    [Google Scholar]
  38. PlessixR.E., MicheletS., RynjaH., KuehlH., PerkinsC., de MaagJ.W. and HatchellP.2010. Some 3D applications of full waveform inversion. Expanded Abstracts, EAGE.
    [Google Scholar]
  39. PrattR.G.1999. Seismic waveform inversion in the frequency domain, part I : theory and verification in a physic scale model. Geophysics, 64, 888–901.
    [Google Scholar]
  40. QueißerM. and SinghS.C.2013. Full waveform inversion in the time lapse mode applied to CO2 storage at sleipner. Geophysical Prospecting61(3), 537–555.
    [Google Scholar]
  41. RamirezA., DailyW., LaBrecqueD., OwenE., and ChesnutD.1993. Monitoring an underground steam injection process using electrical resistance tomography. Water Resources Research29(1), 73–87.
    [Google Scholar]
  42. RickettJ.E. and LumleyD.E.2001. Cross‐equalization data processing for time‐lapse seismic reservoir monitoring: A case study from the Gulf of Mexico. Geophysics66(4), 1015–1025.
    [Google Scholar]
  43. RomdhaneA., RavautC. and QuerendezE.2012. CO2 monitoring at the Sleipner field with full waveform inversion. Geophysical Research Abstracts, EGU 2012, vol. 14.
  44. ShippR.M. and SinghS.C.2002. Two‐dimensional full wavefield inversion of wide‐aperture marine seismic streamer data. Geophysical Journal International151, 325–344.
    [Google Scholar]
  45. SinghaK. and GorelickS.M.2005. Saline tracer visualized with three‐dimensional electrical resistivity tomography: Field‐scale spatial moment analysis. Water Resources Research41(5), W05023.
    [Google Scholar]
  46. TarantolaA.1984. Linearized inversion of seismic reflection data. Geophysical Prospecting32, 998–1015.
    [Google Scholar]
  47. TarantolaA.2005. Inverse Problem theory and methods for model parameter estimation, Society for Industrial and Applied Mathematics, Philadelphia.
  48. ThoreP., AlloucheH., LysP.O. and TarrassI.2010. Retrieving 4D signal in complex media using the full waveform inversion paradigm. 72nd EAGE Conference & Exhibition, EAGE.
  49. TikhonovA. and ArseninV.1977. Solution of ill‐posed problems, Winston, Washington, DC.
    [Google Scholar]
  50. TuraA. and LumleyD.E.1999. Estimating pressure and saturation changes from timelapse AVO data. SEG Technical Program Expanded Abstracts 1999, 1655–1658.
  51. VirieuxJ. and OpertoS.2009. An overview of full waveform inversion in exploration geophysics. Geophysics74(6), WCC1–WCC26.
    [Google Scholar]
  52. WaldhauserF. and EllsworthW.L.2000. A double‐difference earthquake location algorithm: method and application to the northern Hayward fault, California. Bulletin of the Seismological Society of America90(6), 1353–1368.
    [Google Scholar]
  53. WangC., YingstD., BloorR. and LeveilleJ.2012. VTI waveform inversion with practical strategies: Application to 3D real data. SEG Technical Program Expanded Abstracts 2012, 1–6.
    [Google Scholar]
  54. WatanabeT., ShimizuS., AsakawaE. and MatsuokaT.2004. Differential waveform tomography for time‐lapse crosswell seismic data with application to gas hydrate production monitoring. SEG Technical Program Expanded Abstracts23(1), 2323–2326.
    [Google Scholar]
  55. WilliamsonP.R., CherrettA.J. and SextonP.A.2007. A new approach to warping for quantitative time‐lapse characterisation. EAGE Technical Program Expanded Abstracts 2007, p. P064.
    [Google Scholar]
  56. ZhangH., and ThurberC.H.2003. Double difference tomography: The method and its application to the Hayward fault, California. Bulletin of the Seismological Society of America93(5), 1875–1889.
    [Google Scholar]
  57. ZhouR., HuangL. and RutledgeJ.2010. Microseismic event location for monitoring CO2 injection using double‐difference tomography. The Leading Edge29(2), 208–213.
    [Google Scholar]
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  • Article Type: Research Article
Keyword(s): Full waveform; Inversion; Monitoring; Seismic; Time‐lapse

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