1887
Volume 64, Issue 6
  • E-ISSN: 1365-2478

Abstract

ABSTRACT

Four‐dimensional imaging using geophysical data is of increasing interest in the oil and gas industries. While travel‐time and amplitude variations are commonly used to monitor reservoir properties at depth, their interpretation can suffer from a lack of information to decipher the parts played by different parameters. In this context, this study focuses on the slowness and azimuth angle measured at the surface using source and receiver arrays as complementary observables. In the first step, array processing techniques are used to extract both azimuth and incidence angles at the source side (departure angles) and at the receiver side (arrival angles). In the second step, the slowness and angle variations are monitored in a laboratory environment. These new observables are compared with traditional arrival‐time variations when the propagation medium is subject to temperature fluctuations. Finally, field data from a heavy‐oil permanent reservoir monitoring system installed onshore and facing steam injection and temperature variations are investigated. The slowness variations are computed over a period of 152 days. In agreement with Fermat's principle, strong correlations between the slowness and arrival‐time variations are highlighted, as well as good consistency with other techniques and field pressure measurements. Although the temporal variations of slowness and arrival time show the same features, there are still differences that can be considered for further characterization of the physical changes at depth.

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/content/journals/10.1111/1365-2478.12338
2015-11-24
2024-03-28
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References

  1. AlvarezE. and MacBethC.2014. An insightful parametrization for the flatlander's interpretation of time‐lapsed seismic data. Geophysical Prospecting62, 75–96.
    [Google Scholar]
  2. AngelovP., SpetzlerJ. and WapenaarK.2004. Pore pressure and water saturation variations: modification of Landrø’s AVO approach. 74th SEG Meeting, Denver, USA, Expanded Abstracts, 2279–2282.
  3. AsnaashariA.2013. Quantitative 4D (time‐lapse) seismic imaging in complex media using 2D full waveform inversion. PhD thesis, ISTERRE, Université Joseph Fourier, France.
    [Google Scholar]
  4. AsnaashariA., BrossierR., GaramboisS., AudebertF., ThoreP. and VirieuxJ.2014. Time‐lapse seismic imaging using regularized FWI with a prior model: which strategy? Geophysical Prospecting63, 78–98.
    [Google Scholar]
  5. AulanierF., NicolasB., RouxP. and MarsJ.2013a. Time‐angle sensitivity kernels for sound‐speed perturbations in a shallow ocean. Journal of Acoustical Society of America134, 88–96.
    [Google Scholar]
  6. AulanierF., RouxP., NicolasB., BrossierR. and MarsJ.2013b. Shallow water acoustic tomography from angle measurements instead of travel‐time measurements. Journal of the Acoustic Society of America134, 373–379.
    [Google Scholar]
  7. BarkvedO.I., BuerK., KristiansenT.G., KjelstadliR.M. and KommedalJ.H.2005. Permanent seismic monitoring at the Valhall field, Norway. International Petroleum Technology Conference, Doha, Qatar.
  8. BlondinE. and MariJ.L.1986. Detection of gas bubble boundary movement. Geophysical Prospecting34, 73–93.
    [Google Scholar]
  9. BouéP., RouxP., CampilloM. and de CacquerayB.2013. Double beamforming processing in seismic prospecting context. Geophysics78, 101–108.
    [Google Scholar]
  10. BrenguierF., ShapiroN.M., CampilloM., FerrazziniV., DuputelZ., CoutantO.et al. 2008. Towards forecasting volcanic eruptions using seismic noise. Nature Geoscience1, 126–130.
    [Google Scholar]
  11. CampilloM. and PaulA.2003. Long‐range correlations in the diffusive seismic coda. Sciences299, 547–549.
    [Google Scholar]
  12. CottonJ., ForguesE. and HornmanJ.C.2012. Land seismic reservoir monitoring: where is the steam going? 82nd SEG Meeting, Las Vegas, USA, Expanded Abstracts, 1–5.
  13. CottonJ. and ForguesE.2012. Dual‐depth hydrophones for ghost reduction in 4D land monitoring. 82nd SEG Meeting, Las Vegas, USA, Expanded Abstracts, 1–5.
  14. CottonJ., MichouL. and ForguesE.2013. Continuous land seismic reservoir monitoring of thermal EOR in the Netherlands. IOR 2013: From Fundamental Science to Deployment, St. Petersburg, Russia.
  15. CottonJ., MichouL., ForguesE. and HornmanK.2013. Continuous land seismic reservoir monitoring of thermal EOR in the Netherlands. 13th International Congress of the Brazilian Geophysical Society, Rio, Brazil.
  16. DahlenF.A., HungS.‐H. and NoletG.2000. Fréchet kernels for finite‐frequency traveltimes—I. Theory. Geophysical Journal International141, 157–174.
    [Google Scholar]
  17. de CacquerayB.2012. Dispositifs Géophysiques en laboratoire, Onde de surface, traitement et haute densité spatiale. PhD thesis (in French), Université Joseph Fourier, France.
    [Google Scholar]
  18. de CacquerayB., RouxP., CampilloM., CathelineS. and BouéP.2011. Elastic‐wave identification and extraction through array processing: an experimental investigation at the laboratory scale. Journal of Applied Geophysics74, 81–88.
    [Google Scholar]
  19. de CacquerayB., RouxP., CampilloM. and CathelineS.2013. Tracking of velocity variations at depth in the presence of surface velocity fluctuations. Geophysics78, U1–U8.
    [Google Scholar]
  20. EastwoodJ.1993. Temperature‐dependant propagation of P‐ and S‐ waves in Cold Lake oil sands: comparison of theory and experiment. Geophysics6, 863–872.
    [Google Scholar]
  21. EikenO., WaldemarP., SchonewilleM., HaugenG.U. and DuijndamA.1999. A proven concept for acquiring highly repeatable towed streamer seismic data. 61st EAGE Conference and Exhibition, Helsinki, Finland.
  22. EriksrudM.2014. Seabed permanent reservoir monitoring (PRM) – A valid 4D seismic technology for fields in the North Sea. First Break32, 67–73.
    [Google Scholar]
  23. FloricichM., MacBethC., StammeijerJ., StaplesR., EvansA. and DijksmanC.2006. A new technique for pressure‐saturation separation from time‐lapse seismic: Schiehallion Case Study. 68th Annual Conference and Exhibition, EAGE, Extended Abstracts, E017.
  24. FolstadP.G., BertrandA., LyngnesB., HallerN. and GrandiA.2013. Ekofisk permanent seismic monitoring: results after first two years. 75th EAGE Conference, London, U.K.
  25. ForguesE. and SchisseléE.2010. Benefits of hydrophones for land seismic monitoring. 72nd EAGE Conference & Exhibition, Barcelona, Spain, B034.
  26. ForguesE., Schisselé‐RebelE. and CottonJ.2011. Simultaneous active/ passive seismic monitoring of steam assisted heavy oil production. 73rd EAGE Conference and Exhibition, Vienna, Austria.
  27. HadziioannouC., LaroseE., BaigA., RouxP. and CampilloM.2011. Improving temporal resolution in ambient noise monitoring of seismic speed. Journal of Geophysical Research116, B07304.
    [Google Scholar]
  28. HermansenH.2008. The Ekofisk field: achieving three times the original value. 19th World Petroleum Congress, Madrid, Spain. 19, 3966.
  29. HornmanJ.C., Van PoptaJ., DidragaC. and DijkermanH.2012. Continuous monitoring of thermal EOR at Schoonebeek for intelligent reservoir management. SPE International Intelligent Energy Conference.
  30. IturbeI., RouxP., NicolasB., VirieuxJ. and MarsJ.2009a. Shallow water acoustic tomography performed from a double beamforming algorithm. IEEE Journal of Oceanic Engineering34, 140–149.
    [Google Scholar]
  31. IturbeI., RouxP., VirieuxJ. and NicolasB.2009b. Travel‐time sensitivity kernels versus diffraction patterns obtained through double‐beamforming in shallow water. Journal of the Acoustical Society of America126, 713–720.
    [Google Scholar]
  32. JohnstonD.H., EastwoodJ.E., ShyehJ.J., VauthrinR., KhanM. and StanleyL.2000. Using legacy seismic data in an integrated time‐lapse study: Lena field, Gulf of Mexico. The Leading Edge19, 294–302.
    [Google Scholar]
  33. KraghE. and ChristieP.2002. Seismic repeatability, normalized RMS, and predictability. The Leading Edge21, 640–647.
    [Google Scholar]
  34. KrügerF., WeberM., ScherbaumF. and SchlittenhardtJ.1996. Analysis of asymmetric multipathing with a generalization of the double‐beam method. Bulletin of the Seismological Society of America86, 737–749.
    [Google Scholar]
  35. LandrøM.2001. Discrimination between pressure and fluid saturation changes from time‐lapse seismic data. Geophysics66, 836–844.
    [Google Scholar]
  36. LandrøM. and StammeijerJ.2004. Quantitative estimation of compaction and velocity changes using 4D impedance and traveltime changes. Geophysics69, 949–957.
    [Google Scholar]
  37. Le TouzéG., NicolasB., MarsJ., RouxP. and OudomphengB.2012. Double‐capon and double‐MUSICAL for arrival separation and observable estimation in an acoustic waveguide. EURASIP Journal on Advances in Signal Processing187, 1–13.
    [Google Scholar]
  38. LuoY. and SchusterG.T.1991. Wave‐equation traveltime inversion. Geophysics56, 645–653.
    [Google Scholar]
  39. MarandetC., RouxP., NicolasB. and MarsJ.2011. Target detection and localization in shallow water: an experimental demonstration of the acoustic barrier problem at the laboratory scale. Journal of the Acoustical Society of America129, 85–97.
    [Google Scholar]
  40. MarqueringH., DahlenF.A. and NoletG.1999. Three‐dimension al sensitivity kernels for finite‐frequency traveltimes: the banana‐doughnut paradox. Geophysical Journal International137, 805–815.
    [Google Scholar]
  41. MeadowsM.A.2001. Enhancements to Landrø’s method for separating time‐lapse pressure and saturation changes. SEG 71st Meeting, San Antonio, USA, Expanded Abstracts, 1652–1655.
  42. MeunierJ. and HuguetF.1998. Céré‐la‐Ronde: a laboratory for time lapse seismic monitoring in the Paris Basin. The Leading Edge17, 1388–1394.
    [Google Scholar]
  43. MichouL., ColéouT. and LafetY.2013. 4D seismic inversion on continuous land seismic reservoir monitoring of thermal EOR. 75th EAGE Conference and Exhibition, London, U.K.
  44. MontelliR., NoletG., DahlenF.A. and MastersG.2006. A catalogue of deep mantle plumes: New results from finite frequency tomography. Geochemistry, Geophysics, Geosystems7(11).
    [Google Scholar]
  45. NurA., TosayaC. and Vo‐ThanhD.1984. Seismic monitoring of thermal enhanced oil recovery processes. 54th SEG Meeting, Atlanta, USA, 337–340.
  46. PoupinetG., EllsworthW.L. and FréchetJ.1984. Monitoring velocity variations in the crust using earthquakes doublets: an application to the Calaveras Fault, California. Journal of Geophysical Research155, 1021–1041.
    [Google Scholar]
  47. RickettJ. and LumleyD.E.1998. A cross equalization processing flow for off‐the‐shelf 4D seismic data. 68th SEG Meeting, Expanded Abstracts.
  48. RossC.P., CunninghamG.B. and WeberD.P.1996. Inside the cross‐equalization black box. The Leading Edge15, 1233–1240.
    [Google Scholar]
  49. RostS. and ThomasC.2002. Array seismology: methods and applications. Reviews of Geophysics40(3), 2–1.
    [Google Scholar]
  50. RoustiauA., ColéouT., MacheclerI., AyzenbergM., FayemendyC., SkjeiN.et al. 2013. 4D petrophysical seismic inversion ‐ case studies. 75th EAGE Conference and Exhibition, London, U.K.
  51. RouxP., CornuelleB.D., KupermanW.A. and HodgkissW.S.2008. The structure of ray‐like arrivals in a shallow‐water waveguide. Journal of the Acoustical Society of America124, 3430–3439.
    [Google Scholar]
  52. RouxP., KupermanW.A., CornuelleB.D., AulanierF., HodgkissW.S. and SongH.C.2013. Analyzing sound speed fluctuations in shallow water from group‐velocity versus phase‐velocity data representation. The Journal of the Acoustical Society of America133, 1945–1952.
    [Google Scholar]
  53. SchisseléE., ForguesE., EchappéJ., MeunierJ., de PellegarsO. and HubansC.2009. Seismic Repeatability – Is There a Limit? 71st EAGE Conference and Exhibition, Extended Abstracts, V021.
  54. Sens‐SchönfelderC. and WeglerU.2006. Passive image interferometry and seasonal variations of seismic velocities at Merapi Volcano, Indonesia. Geophysical Research Letters33, L21302.
    [Google Scholar]
  55. ShabelanskyA., MalcolmA. and FehlerM.2012. Monitoring Seismic Attenuation Changes Using a 4D Relative Spectrum Method in Athabsca Heavy Oil Reservoir, Canada, pp. 6. Earth Resources Laboratory Massachusetts Institute of Technology.
    [Google Scholar]
  56. ShapiroN.M. and CampilloM.2004. Emergence of broadband Rayleigh waves from correlation of the ambient seismic noise. Geophysical Research Letters31(7), 1–4.
    [Google Scholar]
  57. SkarsoulisE.K. and CornuelleB.D.2004. Travel‐time sensitivity kernels in ocean acoustic tomography. Journal of the Acoustical Society of America116, 227–238.
    [Google Scholar]
  58. SukhovichA., RouxP. and WatheletM.2010. Geoacoustic inversion performed from two source‐receive arrays in shallow water. Journal of the Acoustical Society of America128, 702–710.
    [Google Scholar]
  59. TraniM., ArtsR., LeeuwenburghO. and BrouwerJ.2011. Estimation of changes in saturation and pressure from 4D seismic and AVO and time‐shift analysis. Geophysics76(2), C1–C7.
    [Google Scholar]
  60. WeberM., DavisJ.‐P., ThomasC., KrügerF., ScherbaumF., SchlittenhardtJ.et al. 1996. The structure of the lowermost mantle as determined from using seismic arrays. In: Seismic Modeling of the Earth's Structure (eds E.Boschi , G.Ekström and A.Morelli ), pp. 399–442. Istituto Nazionale di Geofisica e Vulcanologia, Rome, Italy.
    [Google Scholar]
  61. WoodwardW.1992. Wave‐equation tomography. Geophysics57, 15–26.
    [Google Scholar]
  62. YilmazO.1987. Seismic Data Processing, Vols. 1 and 2. Society of Exploration Geophysicists.
    [Google Scholar]
  63. ZhengY., FangX., FehlerM. and BurnsD.2011. Double‐beam stacking to infer seismic properties of fractured reservoirs. 81st SEG Meeting, San Antonio, USA, Expanded Abstracts, 1809–1813.
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