1887

Abstract

Summary

A key task in 4D seismic analysis is to resolve changes in subsurface velocity ΔV/V that affect both imaging in the monitor data and our interpretation of time-lapse amplitudes. This study introduces a new approach to recover ΔV/V using a Gaussian mixture model. The Gaussians are found to be better representative of the property fields than other choices such as B-splines. This approach is tested by application to a North Sea field, where geomechanical effects are active. Recovery of ΔV/V from three different time-shift estimates, using three approaches is firstly compared with Gaussian reconstruction. A second comparison estimates ΔV/V directly from the trace data. In these tests, the new approach compares favourably in the presence of noise, and is relatively simple to implement.

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/content/papers/10.3997/2214-4609.201701204
2017-06-12
2024-04-19
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References

  1. Hale, D.
    [2009] A method for estimating apparent displacement vectors from time-lapse seismic images. Geophysics, 74(5), V99–V107.
    [Google Scholar]
  2. Hansen, P.C.
    [1994] Regularization Tools: A Matlab package for analysis and solution of discrete ill-posed problems. Numerical Algorithms, 6(1), 1–35.
    [Google Scholar]
  3. Reynolds, D.
    [2009] Gaussian Mixture Models. Encyclopedia of Biometrics, 659–663.
    [Google Scholar]
  4. Rickett, J., Duranti, L., Hudson, T., Regel, B. and Hodgson, N.
    [2007] 4D time strain and the seismic signature of geomechanical compaction at Genesis. The Leading Edge, 26, 644–647.
    [Google Scholar]
  5. Whitcombe, D.N., Paramo, P., Philip, N., Toomey, A. and Linn, T.R.S.
    [2010] The correlated leakage method - It’s application to better quantify timing shifts on 4D data. 72nd EAGE Conference & Exhibition incorporating SPE EUROPEC, Extended Abstract, B037.
    [Google Scholar]
  6. Williamson, P.R., Cherrett, A.J. and Sexton, P.A.
    [2007] A New Approach to Warping for Quantitative Time-Lapse Characterisation. 69th EAGE Conference & Exhibition, Extended Abstract, P064.
    [Google Scholar]
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