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| Denoising of seismic data via multi-scale ridgelet transform |
| Henglei Zhang1, 2, Tianyou Liu1, 2, Yuncui Zhang3 |
1 Institute of Geophysics and Geomatics, China University of Geosciences, Wuhan 430074, China
2 Key Laboratory of Tectonics and Petroleum Resources (China University of Geosciences), Ministry of Education, Wuhan 430074, China
3 The 5th Geophysical Prospecting Brigade, Zhongnan Petroleum Bureau, Xiangtan 411104, China |
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Abstract Noise has traditionally been suppressed or eliminated in seismic data sets by the use of Fourier filters and, to a lesser degree, nonlinear statistical filters. Although these methods are quite useful under specific conditions, they may produce undesirable effects for the low signal to noise ratio data. In this paper, a new method, multi-scale ridgelet transform, is used in the light of the theory of ridgelet transform. We employ wavelet transform to do sub-band decomposition for the signals and then use non-linear thresholding in ridgelet domain for every block. In other words, it is based on the idea of partition, at sufficiently fine scale, a curving singularity looks straight, and so ridgelet transform can work well in such cases. Applications on both synthetic data and actual seismic data from Sichuan basin, South China, show that the new method eliminates the noise portion of the signal more efficiently and retains a greater amount of geologic data than other methods, the quality and consecutiveness of seismic event are improved obviously as well as the quality of section is improved.
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Received: 18 February 2009
Published: 10 October 2009
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| Fund:China Petrochemical key project during the 11th Five-year Plan as well as the Doctorate Fund of Ministry of Education of China (No.20050491504) |
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Corresponding Authors:
Henglei Zhang
E-mail: sky0610@163.com
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