Irregular seismic data reconstruction using a percentile-half-thresholding algorithm

Chen, Yangkang, Chen, Keling, Shi, Peidong ORCID: https://orcid.org/0000-0001-5782-245X and Wang, Yanyan 2014. Irregular seismic data reconstruction using a percentile-half-thresholding algorithm. Journal of Geophysics and Engineering 11 (6) , 065001. 10.1088/1742-2132/11/6/065001

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Abstract

In this paper, a percentile-half-thresholding approach is proposed in the transformed domain thresholding process for iterative shrinkage thresholding (IST). The percentile-thresholding strategy is more convenient for implementing than the constant-value, linear-decreasing, or exponential-decreasing thresholding because it’s data-driven. The novel half-thresholding strategy is inspired from the recent advancement in the researches on optimization using non-convex regularization. We summarize a general thresholding framework for IST and show that the only difference between half thresholding and the conventional soft or hard thresholding lays in the thresholding operator. Thus it’s straightforward to insert the existing percentile-thresholding strategy to the half-thresholding iterative framework. We use both synthetic and field data examples to compare the performances using soft thresholding or half thresholding with constant threshold or percentile threshold. Synthetic and field data show consistent results that apart from the threshold-setting convenience, the percentile thresholding also has the possibility for improving the recovery performance. Compared with soft thresholding, half thresholding tends to have a more precise reconstructed result.

Item Type:	Article
Date Type:	Publication
Status:	Published
Schools:	Earth and Environmental Sciences
Publisher:	Oxford University Press
ISSN:	1742-2132
Date of Acceptance:	1 September 2014
Last Modified:	11 Feb 2025 13:15
URI:	https://orca.cardiff.ac.uk/id/eprint/175378

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