Channel edge detection using 2D complex shearlet transform: a case study from the South Caspian Sea

Abstract

Channels are important sedimentary features in hydrocarbon plays either as targets for drilling or geohazards that should be avoided, depending on burial depth and fluid-fill. Either way, for well design purposes it is important to image channels before drilling. Shearlet transform, as a multi-scale and multi-directional transformation, is capable of detecting anisotropic singularities in two and higher dimensional data. In this study, the complex-valued shearlet-based edge measure was implemented for the aim of channel boundary detection. The method was applied to synthetic seismic time-slices containing channels with different signal-to-noise ratios as well as a real time-slice from the South Caspian Sea. The performance of the shearlet-based algorithm was compared both qualitatively and quantitatively with well known gradient-based edge detectors such as Sobel and Canny, resulting in successfully localising edges and detecting less false positives.