1887
Volume 65, Issue 2
  • E-ISSN: 1365-2478

Abstract

ABSTRACT

Hydrocarbon production and fluid injection affect the level of subsurface stress and physical properties of the subsurface, and can cause reservoir‐related issues, such as compaction and subsidence. Monitoring of oil and gas reservoirs is therefore crucial. Time‐lapse seismic is used to monitor reservoirs and provide evidence of saturation and pressure changes within the reservoir. However, relative to background velocities and reflector depths, the time‐lapse changes in velocity and geomechanical properties are typically small between consecutive surveys. These changes can be measured by using apparent displacement between migrated images obtained from recorded data of multiple time‐lapse surveys. Apparent displacement measurements by using the classical cross‐correlation method are poorly resolved. Here, we propose the use of a phase‐correlation method, which has been developed in satellite imaging for sub‐pixel registration of the images, to overcome the limitations of cross‐correlation. Phase correlation provides both vertical and horizontal displacements with a much better resolution. After testing the method on synthetic data, we apply it to a real dataset from the Norne oil field and show that the phase‐correlation method can indeed provide better resolution.

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2016-08-25
2024-03-29
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References

  1. AarreV.2008. On the presence, and possible causes, of apparent lateral shifts below the Nome reservoir. 78th SEG meeting, Las Vegas, USA, Expanded Abstracts, 3174–3178.
  2. BerthierE., VadonH., BaratouxD., ArnaudY., VincentC., FeiglK.et al. 2005. Surface motion of mountain glaciers derived from satellite optical imagery. Remote Sensing Environment95, 14–28.
    [Google Scholar]
  3. BinetR. and BollingerL.2005. Horizontal coseismic deformation of the 2003 Bam (Iran) earthquake measured from SPOT‐5 THR satellite imagery. Geophysical Research Letters32(2), L02307.1–L02307.4.
    [Google Scholar]
  4. BlaciM. and ForooshH.2006. Subpixel estimation of shifts directly in the Fourier domain. IEEE Transactions on Image Processing15, 1965–1972.
    [Google Scholar]
  5. CarcioneJ.M., LandrøM., GangiA. and CavalliniF.2007. Determining the dilation factor in 4D monitoring of compacting reservoirs by rock‐physics models. Geophysical Prospecting55(6), 793–804.
    [Google Scholar]
  6. CrippenR. and BlomR.1991. Measurement of subresolution terrain displacements using SPOT panchromatic imagery. In: Proceedings of the IEEE International Geoscience and Remote Sensing Society Symposium Vol.3, pp. 1667–1670.
    [Google Scholar]
  7. Dong‐MinW., Dong‐ChulP., IlhwanC., TaikyeongJ. and YunsikL.2010. Effects of the change of window size on the performance of correlation‐based stereo. In: Information Networking and Automation (ICINA), International Conference Vol. 2, 364–368.
  8. ForooshH., ZerubiaJ.B. and BerthodM.2002. Extension of phase‐correlation to subpixel registration. IEEE Transactions on Image Processing11(3), 188–200.
    [Google Scholar]
  9. GonzalezR.C. and WoodsR.E.2002. Digital Image Processing, 2nd edn. Pearson Education, Singapore.
    [Google Scholar]
  10. HaleD.2009. A method for estimating apparent displacement vectors from time‐lapse seismic images. Geophysics74(5), V99–V107.
    [Google Scholar]
  11. HallS.2006. A methodology for 7D warping and deformation monitoring using time‐lapse seismic data. Geophysics71(4), O21–O31.
    [Google Scholar]
  12. HallS.A., MacBethC., BarkvedO.I. and WildP.2005. Cross‐matching with interpreted warping of 3D streamer and 3D ocean‐bottom‐cable data at Valhall for time‐lapse assessment. Geophysical Prospecting53, 283–297.
    [Google Scholar]
  13. HatchellP. and BourneS.2005a. Rocks under strain: Strain‐induced time‐lapse time shifts are observed for depleting reservoirs. The Leading Edge24, 1222–1225.
    [Google Scholar]
  14. HatchellP. and BourneS.2005b. Measuring reservoir compaction using time‐lapse time shifts. 75th SEG meeting, Houston, USA, Expanded Abstracts, 2500–2504.
  15. HawkinsK., HoweS., HollingworthS., ConroyG., Ben‐BrahimL., TindleC.et al. 2007. Production‐induced stresses from time‐lapse time shifts: A geomechanics case study from Franklin and Elgin fields. The Leading Edge26, 655–662.
    [Google Scholar]
  16. JohnstonD.H.2013. Practical Applications of Time‐Lapse Seismic Data. Distinguished Instructor Series.Society of Exploration Geophysicists.
    [Google Scholar]
  17. KraghE. and ChristieP.2002. Seismic repeatability, normalized rms and predictability. The Leading Edge21, 640–647.
    [Google Scholar]
  18. KuglinC.D. and HinesD.C.1975. The phase correlation image alignment method. In: IEEE Proceedings of the International Conference on Cybernetics and Society, pp. 163–165.
  19. LandrøM., SolheimO.A., HildeE., EkrenB.O. and StronenL.K.1999. The Gullfaks 4D seismic study. Petroleum Geoscience5, 213–226.
    [Google Scholar]
  20. LeprinceS., BarbotS., AyoubF. and AvouacJ.P.2008. Automatic and precise ortho‐rectification, coregistration, and subpixel correlation of satellite images, application to ground deformation measurements. IEEE Transactions on Geoscience and Remote Sensing45(6), 1529–1558.
    [Google Scholar]
  21. LewisJ.P.1995. Fast template matching. Vision Interface95(120123), 15–19.
    [Google Scholar]
  22. McPhersonG.2013. Statistics in Scientific Investigation: Its Basis, Application and Interpretation. Springer‐Verlag.
    [Google Scholar]
  23. NickelM., SchlafJ. and SønnelandL.2003. New tools for 4D seismic analysis in compacting reservoirs. Petroleum Geoscience9, 53–59.
    [Google Scholar]
  24. NickelM. and SønnelandL.1999. Nonrigid matching of migrated time‐lapse seismic. 69th SEG Meeting, Houston, USA, Expanded Abstracts, 872–875.
  25. OppenheimA., SchaferR. and BuckJ.1999. Discrete‐Time Signal Processing, 2nd edn.Prentice‐Hall, Upper Saddle River, NJ.
    [Google Scholar]
  26. OsdalB. and AlsosT.2002. Seismic modelling of eclipse simulations and comparison with real 4D data at the Norne field. 64th Annual Conference and Exhibition, EAGE, Extended Abstracts, A29.
  27. OsdalB., HusbyO., AronsenH.A., ChenN. and AlsosT.2006. Mapping the fluid front and pressure buildup using 4D data on Norne field. The Leading Edge25, 1134–1141.
    [Google Scholar]
  28. PressW.H., TeukolskyS.A., VetterlingW.T. and FlanneryB.P.1996. Numerical Recipes in Fortran 90: the Art of Parallel Scientific Computing. Cambridge University Press. FORTRAN Numerical Recipes.
    [Google Scholar]
  29. PuymbroeckN. V., MichelR., BinetR., AvouacJ. P. and TabouryJ.2000. Measuring earthquakes from optical satellite images. Applied Optics39, 3486–3494.
    [Google Scholar]
  30. 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]
  31. RøsterT., StovasA. and LandrøM.2006. Estimation of layer thickness and velocity changes using 4d prestack seismic data. Geophysics71(6), S219–S234.
    [Google Scholar]
  32. TomarG., SinghS. and MontagnerJ.P.2014. Sub‐sample time shift and displacement measurement by phase‐correlation in time‐lapse seismic. 76th EAGE Conference and Exhibition, Amsterdam, Extended Abstract, WE P06–03.
  33. TzimiropoulosG., ArgyriouV. and StathakiT.2008. A frequency domain approach to roto‐translation estimation using gradient cross‐correlation. In: Proceedings of the IEEE British Machine Vision Conference, pp. 1–10.
  34. YilmazÖ.2001. Seismic Data Analysis. Society of Exploration Geophysicists.
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  • Article Type: Research Article
Keyword(s): Cross‐correlation; Monitoring; Phase correlation; Seismic; Time lapse

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