F-X域复数经验模态分解去噪方法

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Bibliographic Details
Published in应用地球物理：英文版 Vol. 12; no. 1; pp. 47 - 54
Main Author 马彦彦 李国发 王钧 周辉 张保江
Format Journal Article
LanguageEnglish
Published 2015
Subjects
F-X域预测滤波
复固有模态函数
复数经验模态分解
随机噪声衰减
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ISSN1672-7975
1993-0658

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Bibliography:Complex empirical mode decomposition; complex intrinsic mode functions; f–x predictive filtering; random noise attenuation
Ma Yan-Yan;Li Guo-Fa;Wang Yao-Jun;Zhou Hui;Zhang Bao-Jiang （1. State Key Laboratory of Petroleum Resources and Prospecting, China University of Petroleum, Beijing 102249, China. 2. CNPC Key Laboratory of Geophysical Prospecting, China University of Petroleum, Beijing 102249, China. 3. Petroleum Exploration and Production Research Institute, SINOPEC, Beijing 100083, China）
11-5212/O
The frequency–space（f–x） empirical mode decomposition（EMD） denoising method has two limitations when applied to nonstationary seismic data. First, subtracting the first intrinsic mode function（IMF） results in signal damage and limited denoising. Second, decomposing the real and imaginary parts of complex data may lead to inconsistent decomposition numbers. Thus, we propose a new method named f–x spatial projection-based complex empirical mode decomposition（CEMD） prediction filtering. The proposed approach directly decomposes complex seismic data into a series of complex IMFs（CIMFs） using the spatial projection-based CEMD algorithm and then applies f–x predictive filtering to the stationary CIMFs to improve the signal-to-noise ratio. Synthetic and real data examples were used to demonstrate the performance of the new method in random noise attenuation and seismic signal preservation.
ISSN:1672-7975
1993-0658