Irregular Seismic Data Reconstruction Using a Percentile-half-thresholding Algorithm
Y. Chen, P.D. Shi, Y.Y. Wang and S.X. Wang
Event name: 76th EAGE Conference and Exhibition 2014
Session: Seismic Signal Processing
Publication date: 16 June 2014
Info: Extended abstract, PDF ( 3.11Mb )
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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 lies 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.