Event detection in prestack migration using matched filters

Jeff. K. Beckett and John C. Bancroft

ABSTRACT

Given a particular statistical measure of signal-to-noise (S/N), the "matched filter" is the ideal linear filter for maximizing the S/N ratio of a signal amongst random, white noise. A matched-filter approach to prestack imaging is proposed, where "signal" is defined as a particular AVO reflection coefficient surface, and all other AVO response surfaces are considered "noise". Cross-correlation 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 of synthetic P-wave data enhances the detection of Class 2 AVO events. Preliminary tests on converted wave (PSV) synthetic data yield superior imaging, due to noise cancellation at near offsets.

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