Seismic random noise suppression using an adaptive nonlocal means algorithm
Shang Shuai1, Han Li-Guo1, Lv Qing-Tian2, and Tan Chen-Qing1
1. College of Geo-Exploration Science and Technology, Jilin University, Changchun 130026, China.
2. Chinese Academy of Geological Sciences, Beijing 100000, China.
Abstract Nonlocal means filtering is a noise attenuation method based on redundancies in image information. It is also a nonlocal denoising method that uses the self-similarity of an image, assuming that the valid structures of the image have a certain degree of repeatability that the random noise lacks. In this paper, we use nonlocal means filtering in seismic random noise suppression. To overcome the problems caused by expensive computational costs and improper filter parameters, this paper proposes a block-wise implementation of the nonlocal means method with adaptive filter parameter estimation. Tests with synthetic data and real 2D post-stack seismic data demonstrate that the proposed algorithm better preserves valid seismic information and has a higher accuracy when compared with traditional seismic denoising methods (e.g., f-x deconvolution), which is important for subsequent seismic processing and interpretation.
This work is supported by the National Natural Science Foundation of China (No.41074075), National Science and Technology Project (SinoProbe-03), National public industry special subject (No. 201011047-02), and Graduate Innovation Fund of Jilin University (No. 20121070).
Cite this article:
SHANG Shuai,HAN Li-Guo,吕Qing-Tian et al. Seismic random noise suppression using an adaptive nonlocal means algorithm[J]. APPLIED GEOPHYSICS, 2013, 10(1): 33-40.
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