High resolution Radon transform based on the reweighted-iterative soft threshold algorithm
XUE Yaru1, GUO Mengjun1, FENG Luyu1, MA Jitao2, CHEN Xiaohong2
1. College of Information Science and Engineering, China University of Petroleum(Beijing), Beijing 102249, China; 2. College of Geophysics, China University of Petroleum(Beijing), Beijing 102249, China
Abstract：The resolution of Radon transform is the key to seismic data processing. The iterative weighting method based on Bayes inversion improves the re-solution of Radon transform, but its convergence rate is low. In light of the strong correlation between Radon transform spaces, the convergence rate of the iterative soft threshold algorithm applied to Radon transform inversion is also low, and the resolution is poor. In this paper, the iterative reweighted least squares algorithm is embedded into the iterative soft threshold algorithm to form a reweighted-iterative soft threshold algorithm. The idea of weighted matrix in high-resolution Radon transform is introduced, and the prior information of Radon parameters is employed to constrain the inversion error function, overcoming the disadvantages of slow convergence and low resolution of the iterative soft threshold algorithm. Synthetic records and real seismic data processing show that this method improves the resolution of Radon transform and achieves good performance in multiple separation and noise suppression.
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