Event detection in prestack migration using matched filters
Jeffrey Karl Beckett, John C. Bancroft
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.