Abstract
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.
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This work is supported financially by the National Natural Science Foundation (No. 41174117) and the Major National Science and Technology Projects (No. 2011ZX05031-001).
Ma Yan-Yan received a BS (2007) in Information and Computing Science and a MS (2011) in Earth Exploration and Information Technology from China University of Petroleum (Beijing). She is presently a Ph.D. candidate in China University of Petroleum (Beijing), majoring in Geological Resources and Geological Engineering. Her research interests are seismic data processing and reservoir prediction.
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Ma, YY., Li, GF., Wang, YJ. et al. Random noise attenuation by f-x spatial projection-based complex empirical mode decomposition predictive filtering. Appl. Geophys. 12, 47–54 (2015). https://doi.org/10.1007/s11770-015-0467-3
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DOI: https://doi.org/10.1007/s11770-015-0467-3