Interpolation with pseudo-primaries: revisited

William Curry

bill@sep.stanford.edu

ABSTRACT

Large gaps may exist in marine data at near offsets. I generate pseudo-primaries by auto-correlating data containing both primary and multiple reflections. These pseudo-primaries are used as training data for a non-stationary prediction-error filter, which is then used to interpolate the missing near offsets. This method yields good results using filters in the t-x domain, whereas f-x domain filters do not fare well at eliminating the crosstalk in the pseudo-primaries.