Datapages, Inc.Print this page

Post-Stack Signal Enhancement

Steve Spratt

Various post-stack signal enhancement techniques improve the appearance of seismic data. Most popular data-adaptive enhancement algorithms involve three steps: a linear transform, some method of discriminating between signal and noise in the transform domain, and an inverse transform. Three algorithms operate in the f-k, f-x, and r-p domains. For flat-lying data plus random noise, all of the algorithms become in effect spatially weighted running averages. For data with more than one dip, the enhancement is obtained by averaging along the various dip directions. Details of how the averaging weights are determined and how rapidly each method can adapt in space and time comprise their major differences. The f-k and f-x algorithms perform best in enhancing regional trends, wh reas the r-p domain process is better at bringing out stronger structure. The improvement in signal-to-noise is invariably at the expense of spatial resolution, regardless of how clever or complex the procedure.

AAPG Search and Discovery Article #91035©1988 AAPG-SEPM-SEG Pacific Sections and SPWLA Annual Convention, Santa Barbara, California, 17-19 April 1988.