High-resolution imaging of diffractions — A window-steered MUSIC approach

Abstract

Enhancement of diffractions and their use to resolve fine-scale details in a seismic image is increasingly important. Diffractions carry useful information about small-scale characteristics of the subsurface associated with features such as faults, pinch-outs, stratigraphic variations, and other geologic features linked to hydrocarbon reservoirs. Extracting the information content of diffractions and forming an image of the features they illuminate are not trivial tasks. The conventional approach relies on seismic migration, or modifications of seismic migration, and is thus limited by the Rayleigh criterion. The limited aperture and finite bandwidth make it difficult to extract all the potential information content. An alternative approach that overcomes such limitations is to turn to signal processing approaches, which extract information from the structure of the data with the aim of detecting and characterizing a finite number of desired events. Our interest is in diffractions, so we used a windowed or steered version of the MUltiple SIgnal Classification method. Use of this method allowed diffractions to be imaged at resolutions finer than the Rayleigh limit.