1887
Volume 50, Issue 2
  • E-ISSN: 1365-2478

Abstract

ABSTRACT

Time‐lapse seismic surveying has become an accepted tool for reservoir monitoring applications, thus placing a high premium on data repeatability. One factor affecting data repeatability is the influence of the rough sea‐surface on the ghost reflection and the resulting seismic wavelets of the sources and receivers. During data analysis, the sea‐surface is normally assumed to be stationary and, indeed, to be flat. The non‐flatness of the sea‐surface introduces amplitude and phase perturbations to the source and receiver responses and these can affect the time‐lapse image.

We simulated the influence of rough sea‐surfaces on seismic data acquisition. For a typical seismic line with a 48‐fold stack, a 2‐m significant‐wave‐height sea introduces RMS errors of about 5–10% into the stacked data. This level of error is probably not important for structural imaging but could be significant for time‐lapse surveying when the expected difference anomaly is small. The errors are distributed differently for sources and receivers because of the different ways they are towed. Furthermore, the source wavelet is determined by the sea shape at the moment the shot is fired, whereas the receiver wavelet is time‐varying because the sea moves significantly during the seismic record.

Loading

Article metrics loading...

/content/journals/10.1046/j.1365-2478.2002.00311.x
2002-11-23
2020-04-02
Loading full text...

Full text loading...

References

  1. CarterD.J.T., ChallenorP.G., EwingJ.A., PittE.G., SrokoszM.A. and TuckerM.J.1986. Estimating Wave Climate Parameters for Engineering Applications . HMSO OTH 86228.
  2. ClayS.C. and MedwinH.1977. Acoustical Oceanography , p. 544. Wiley Interscience.
    [Google Scholar]
  3. DragosetB., HargreavesN. and LarnerK.1987. Air‐gun source instabilities. Geophysics52, 1229–1251.
    [Google Scholar]
  4. EikenO., WaldemarP., ChonewilleM., UltveitG. and DuijndamA.1999. A proven concept for acquiring highly repeatable towed streamer data. 61st EAGE conference, Helsinki, Finland, Extended Abstracts, 1‐40.
  5. HasselmannD.E., DunckelM. and EwingJ.A.1980. Directional wave spectra observed during JONSWAP 1973. Journal of Physical Oceanography10, 1264–1280.DOI: 10.1175/1520-0485(1980)010<1264:DWSODJ>2.0.CO;2
    [Google Scholar]
  6. HasselmannK., BarnettT.P., BouwsE., CarlsonH., CartwrightD.E., EnkeK.et al.1973. Measurements of wind‐wave growth and swell decay during the joint North Sea wave project (JONSWAP). Dt. Hydrogr. Z., Reihe A (8), 12, 95.
    [Google Scholar]
  7. HastingsF.D., SchneiderJ.B. and BroschatS.L.1995. A Monte Carlo FDTD technique for rough surface scattering. IEEE Transactions on Antennae and Propagation43, 1183–1191.
    [Google Scholar]
  8. JovanovichD.B., SumnerR.D. and Akins‐EasterlinS.L.1983. Ghosting and marine signature deconvolution: a prerequisite for detailed seismic interpretation. Geophysics48, 1468–1485.
    [Google Scholar]
  9. KinsmanB.1983. Wind Waves: Their Generation and Propagation on the Ocean Surface , 2nd edn. Dover Publications, Inc.
    [Google Scholar]
  10. KosterK., GabrielsP., HartungM., VerbeekJ., DeinumG. and StaplesR.2000. Time‐lapse seismic surveys in the North Sea and their business impact. The Leading Edge19, 286–293.
    [Google Scholar]
  11. KraghE. and CombeeL.2000. Using a seismic reflector for resolving streamer depth and sea‐surface profiles. First Break18, 463–467.DOI: 10.1046/j.1365-2397.2000.00463.x
    [Google Scholar]
  12. KraghE. and LawsR.M.2001. Rough seas and statistical deconvolution. 63rd EAGE conference, Amsterdam, The Netherlands, Extended Abstracts, A022.
  13. LabiancaF.M. and HarperE.Y.1977. Connection between various small‐waveheight solutions to the problem of scattering from the ocean surface. Journal of the Acoustical Society of America62, 1144–1157.
    [Google Scholar]
  14. MitsuyasuH.M., TasaiF., SuharaT., MizunoS., OhkusuM., HondaT. and RikiishiK.1975. Observations of the directional spectrum of ocean waves using a clover‐leaf buoy. Journal of Physical Oceanography5, 750–761.
    [Google Scholar]
  15. PiersonW.J. and MoskowitzL.1964. A proposed spectral form for fully developed wind seas based on the similarity theory of S.A. Kitaigorodskii. Journal of Geophysical Research69, 5181–5190.
    [Google Scholar]
  16. RobertssonJ.O.A.1996. A numerical free‐surface condition for elastic/viscoelastic finite‐difference modeling in the presence of topography. Geophysics61, 1921–1934.
    [Google Scholar]
  17. RobertssonJ.O.A., BlanchJ.O. and SymesW.W.1994. Viscoelastic finite‐difference modelling. Geophysics59, 1444–1456.
    [Google Scholar]
  18. ThorsosE.I.1987. The validity of the Kirchhoff approximation for rough surface scattering using a Gaussian roughness spectrum. Journal of the Acoustical Society of America83, 78–92.
    [Google Scholar]
  19. ThorsosE.I.1990. Acoustic scattering from a ‘Pierson–Moskowitz’ sea‐surface. Journal of the Acoustical Society of America88, 335–349.
    [Google Scholar]
http://instance.metastore.ingenta.com/content/journals/10.1046/j.1365-2478.2002.00311.x
Loading
/content/journals/10.1046/j.1365-2478.2002.00311.x
Loading

Data & Media loading...

  • Article Type: Research Article
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