ABSTRACT

Multiple elimination remains one of the key challenges in seismic data processing. Data-driven multiple prediction schemes, such as Surface-related Multiple Elimination (SRME) and Interbed Multiple elimination (IME), have proven to be effective methods to remove complex multiples from the data because they do not make use of any a priori information about the subsurface geology. However, great care must be taken in the prediction and subtraction stages. This paper discusses some of the current best practices and recent experiences. Using the most accurate multiple prediction schemes, excellent results can be obtained using standard subtraction implementations. Sophisticated adaptive subtraction schemes that utilize improved separation of multiples and primaries using different mathematical domains, and / or user-constrained adaptive subtraction schemes may provide the means to improve results further.

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