Seismic imaging using matched filters for operator weighting

Jeffrey Karl Beckett


Given a particular statistical measure of signal to noise (S/N), the `matched filter' is an ideal linear filter for maximizing the S/N ratio of a signal amongst random, white noise. A matched filter approach to event detection in prestack migration is proposed, where `signal' is defined as a particular amplitude variation with offset (AVO) reflection coefficient surface, and all other AVO response surfaces are considered `noise'. Matched filtering of the prestack data with the signal illuminates reflection events whose AVO response curve matches that of the signal; other reflection energy is suppressed. Matched filter imaging enhances the detection of Class 2 AVO events, and results in an overall S/N improvement over conventional P-SV wave prestack migration.

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