Channel edge detection using 2D complex shearlet transform: a case study from the South Caspian Sea. Issue 5 (1st October 2018) - Karbalaali, Haleh; Javaherian, Abdolrahim; Dahlke, Stephan; Torabi, Siyavash
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. Abstract : Channel detection plays a significant role in seismic interpretation. Shearlet transform as a multi-scale and multi-directional transformation is capable of detecting anisotropic singularities. We applied complex-valued shearlet edge measure to synthetic and real seismic time-slices from the South Caspian Sea. The proposed algorithm outperformed both Sobel and Canny edge detectors.