Abstract
Fold reduction for high‐fold data is often necessary due to cost considerations. In the presence of multiples, fold reduction can also improve multiple suppression. By keeping the differences between adjacent squared offsets constant, hyperbolic moveouts are approximately transformed to linear moveouts after fold reduction; dip filtering can then remove multiples more effectively. This approach to multiple suppression is especially attractive if fold must be reduced anyway to save the cost of dip moveout (DMO) or prestack migration. Usually fold is reduced by partial stacking. Approximately, mis‐stacking due to moveout error and reflection‐point smearing in partial stacking are proportional to squared offset. Therefore to a good approximation, optimal partial stacking for multiple suppression, as well as DMO or prestack migration, can be accomplished in the same processing step.
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