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

机译:使用二维复数小波变换的通道边缘检测:以南里海为例

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摘要

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.
机译:通道是碳氢化合物中重要的沉积特征,应作为钻探目标或应避免的地质灾害,这取决于埋藏深度和流体充填。无论哪种方式,出于良好的设计目的,在钻孔之前对通道进行成像都很重要。 Shearlet变换是一种多尺度和多方向的变换,能够检测二维和更高维数据中的各向异性奇异性。在这项研究中,基于通道的边界值检测的目标是基于复值基于小波的边缘度量。该方法应用于合成地震时间切片,其中包含具有不同信噪比的通道以及来自南里海的实时时间切片。与基于梯度的边缘检测器(如Sobel和Canny)定性和定量地比较了基于剪切波的算法的性能,从而成功地确定了边缘并减少了假阳性。

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