Published as Geophysics, 2020, 85, no. 2, V223–V232

Relative time seislet transform

Zhicheng Geng$^1$, Xinming Wu$^1$, Sergey Fomel$^1$, and Yangkang Chen$^2$
$^1$Bureau of Economic Geology, John A. and Katherine G. Jackson School of Geosciences, The University of Texas at Austin, Austin, Texas, USA
$^2$Zhejiang University, School of Earth Sciences, Hangzhou, Zhejiang, China

Abstract:

The seislet transform utilizes the wavelet-lifting scheme and local slopes to analyze the seismic data. In its definition, the designing of prediction operators specifically for seismic images and data is an important issue. We propose a new formulation of the seislet transform based on the relative time (RT) attribute. This method uses RT volume to construct multiscale prediction operators. With the new prediction operators, the seislet transform gets accelerated since distant traces get predicted directly. We apply the proposed method to synthetic and real data to demonstrate that the new approach reduces computational cost and obtains excellent sparse representation on test datasets.