Applying SEP's latest tricks to the multiple suppression problem

Robert G. Clapp and Morgan Brown

bob@sep.stanford.edu, morgan@sep.stanford.EDU

ABSTRACT

Two methods for suppressing multiples are proposed. In the first, multiple suppression is expressed as a signal to noise separation problem. The problem is solved in the time domain using space-varying Prediction Error Filters (PEFs). The second method shows how greater separation between primaries and multiples can be obtained by velocity space inversion using a Huber functional rather than the standard L₂ functional. Early results of both methods are encouraging.