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Multiple suppression in the angle domain with non-stationary prediction-error filters

Seth Haines, Antoine Guitton, and Paul Sava

shaines@pangea.stanford.edu, antoine@sep.stanford.edu, paul@sep.stanford.edu

ABSTRACT

Non-stationary Prediction Error Filters (PEF's) present an effective approach for separating multiples from primaries in the angle domain. The choice of models to be used for estimation of the PEF's has a substantial impact on the final result, but is not an obvious decision. Muting in the parabolic radon transform (PRT) domain produces an effective multiple model, but the corresponding primary model must be massaged in order to minimize remaining multiple energy and achieve a satisfactory result.



 
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Stanford Exploration Project
7/8/2003