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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
Figure 4 Slowness perturbation: scenario 1
on the left and scenario 2 on the right.
bslow
Figure 5 Slowness perturbation obtained
using the adjoint of operator in Equation ().
islow
Figure 6 Slowness perturbation obtained
using the least-squares inverse of the operator
in Equation ().
Next: Conclusions
Up: R. Clapp: STANFORD EXPLORATION
Previous: Example
Stanford Exploration Project
11/11/2002