Seismic Image Analysis Using Local Spectra

Abstract

This report considers a problem in seismic imaging, as presented by researchers from Calgary Scientific Inc. The essence of the problem was to understand how the S-transform could be used to create better seismic images, that would be useful in identifying possible hydrocarbon reservoirs in the earth.

The important first step was to understand what aspect of the imaging problem we were being asked to study. However, since we would not be working directly with raw seismic data, traditional seismic techniques would not be required. Rather, we would be working with a two dimensional image, either a migrated image, a common mid-point (CMP) stack, or a common depth point (CDP) stack. In all cases, the images display the subsurface of the earth with geological structures evident in various layers.

For a given image the local spectrum is computed at each point. The various peaks in the spectrum are used to classify each pixel in the original seismic image resulting in an enhanced and hopefully more useful seismic pseudosection. Thus, the objective of this project was to improve the identification of layers and other geological structures apparent in the two dimensional image (a seismic section, or CDP gather) by classifying and coloring image pixels into groups based on their local spectral attributes.