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Data regularization is an important problem when using
migration methods that rely on the data being on a regular
mesh. Traditional methods that apply the adjoint of a continuation
operation such as AMO can lead to poor amplitude information
in the regularized (and later migrated) cube. By setting
up the regularization problem as inverse problem the amplitudes
in the regular model space are significantly improved.
The problem can be made computationally acceptable by
intelligent parallelization and regularization choices.

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** Up:** R. Clapp: AMO regularization:
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Stanford Exploration Project

10/14/2003