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Discussion

The processing method outlined in this paper is mainly applicable to the situations when the 4-D effects translate into significant slowness variations, for example in cases where pressure changes lead to release of gas in solution and consequently to a drop in velocity. Furthermore, the method is strongly dependent on the quality of the recorded data and also on the quality of the 4-D pre-processing.

We must insure that our definition of the image perturbation is mainly a product of the slowness model perturbation. Much care needs to be taken to eliminate all acquisition differences between the repeat surveys and all processing differences of the different datasets. An ideal case consists of fixed acquisition (permanent water-bottom receivers, for example) and identical seismic processing.

Correct handling of amplitude data in migration is as important as in any method addressing reservoir-related properties. However, in this method we are mainly concerned with the differences between repeat images and not as much interested in their absolute magnitude. Therefore, this method is likely to be robust with respect to the accuracy of the more or less accurate migration amplitudes. This particular subject, however, requires careful further analysis.

 
dslow
dslow
Figure 4
Slowness perturbation: scenario 1 on the left and scenario 2 on the right.
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bslow
bslow
Figure 5
Slowness perturbation obtained using the adjoint of operator ${\bf L}$ in Equation (1).
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islow
islow
Figure 6
Slowness perturbation obtained using the least-squares inverse of the operator ${\bf L}$ in Equation (1).
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next up previous print clean
Next: Conclusions Up: Sava et al.: 4-D Previous: Example
Stanford Exploration Project
11/11/2002