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Regularization of the Least-Squares Problem

Visual inspection of Figure [*] motivates the two forms of regularization utilized in this paper. Find any first-order multiple on the section marked ``NMO for Primaries''. Notice that the corresponding event on the first- and second-order pseudo-primary panels, originally second- and third-order multiples, respectively, all have a different moveout. In fact, the only events which are kinematically consistent across all offsets are the flattened primary and pseudo-primaries. The other events, all crosstalk, are inconsistent between panels. Therefore, the first regularization operator seeks to penalize the difference between the 34#34, at fixed 22#22. To account for the dissimilarity of the AVO of primaries and multiples, this difference is taken at different offsets, as defined in equation ([*]). Written in the form of a model residual vector, this difference is:  
 35#35 (11)

The third index in equation ([*]), i, ranges from 0 to np-1, where np is the highest order multiple modeled in the inversion [see equation ([*])].

The second form of regularization used in this paper is the more obvious of the two: a difference operator along offset. This difference exploits the fact that all non-primaries are not flat after NMO. Again, we can write this difference in the form of a model residual vector:  
 36#36 (12)
The second regularization is applied to all the 34#34. A similar approach is used by () to regularize prestack depth migration in the angle domain.


next up previous print clean
Next: Combined Data and Model Up: methodology Previous: Consistency of the Data
Stanford Exploration Project
6/7/2002