1887

Abstract

Summary

The algorithm of time-lapse velocity anomalies reconstruction using cross-well data is presented. Accurate reconstruction of time-lapse velocity anomalies in inter-well space is important to understand Enhanced Oil Recovery processes. Conventional approaches invert first arrival time delay into a velocity change and hence results significantly depend on the quality of data picking. Moreover, the cross-hole tomography has limited lateral resolution due to specific acquisition geometry. proposed to optimize the functional based on the linear combination of weighted norm of correlation of time-lapse reflection images and direct arrivals. Such approach is stable with respect to phase changes in the data and the lateral resolution is improved by using reflections. Application of the method to synthetic and field data reveals the potential of this algorithm and helps to improve on the data interpretation consistency.

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/content/papers/10.3997/2214-4609.20141473
2014-06-16
2024-03-29
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References

  1. Abakumov, I., D.Kiyashchenko, and B.Kashtan
    [2012] A correlation-based cross-well time-lapse velocity analysis. Presented at the 74th EAGE Conference & Exhibition.
    [Google Scholar]
  2. Byrd, R. H., P.Lu, and J.Nocedal
    [1995] A limited memory algorithm for bound constrained optimization. SIAM Journal on Scientific and Statistical Computing, 16, 1190–1208.
    [Google Scholar]
  3. de Hoop, M. V., and R. D.van der Hilst
    [2005] On sensitivity kernels for ‘wave equation’ transmission tomography. Geophysical Journal International, 160, 621–633.
    [Google Scholar]
  4. Kiyashchenko, D., K.Mehta, J.Lopez, A.Maamari, R.Adawi, and G.Rocco
    [2011] Time-lapse down-hole seismic surveys for deep EOR target monitoring in south Oman. 81st SEG Annual Meeting, 4244–4248.
    [Google Scholar]
  5. Leung, S., and J.Qian
    [2006] An adjoint-state method for three-dimensional transmission traveltime tomography using first arrivals. Communications in Math and Science, 4, 249–266.
    [Google Scholar]
  6. Nasyrov, D., D.Kiyashchenko, Y.Kiselev, B.Kashtan, and V.Troyan
    [2009] Multiple migration of VSP data for velocity analysis. 79th SEG Annual Meeting, 4164–4168.
    [Google Scholar]
  7. Plessix, R.-E.
    [2006] A review of the adjoint-state method for computing the gradient of a functional with geophysical applications. Geophysical Journal International, 167, 495–503.
    [Google Scholar]
  8. Schuster, G. T.
    [1996] Resolution limits for cross-well migration and traveltime tomography. Geophysical Journal International, 127427–440.
    [Google Scholar]
  9. Spetzler, J., D.Sijacic, and K.Wolf
    [2007] Application of a linear finite-frequency theory to time-lapse cross-well tomography in ultrasonic and numerical experiments. Geophysics, 72, 19–27.
    [Google Scholar]
  10. van Leeuwen, T., and W. A.Mulder
    [2010] A correlation-based misfit criterion for wave-equation traveltime tomography. Geophysical Journal International, 182, 1383–1394.
    [Google Scholar]
  11. Zhao, H.
    [2005] A fast sweeping method for eikonal equations. Mathematics of computation, 74, 603–627.
    [Google Scholar]
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