Abstract:We propose a seismic signal denoising method combining adaptive noise complete ensemble empirical mode decomposition(CEEMDAN) and wavelet transform(WT). First, using CEEMDAN, we adaptively decompose the seismic signal into several intrinsic mode functions(IMFs) and margins, and calculate the Pearson correlation coefficient between each component and the original signal. We process the components in the threshold interval by wavelet filtering, maintaining the original state, and directly eliminating, and then we carry out linear reconstruction. Finally, to quantitatively evaluate the denoising effect, we construct the index system of sample entropy change, mutual information, and signal-to-noise ratio. The simulated experiment and measured data (Maduo earthquake in Qinghai) results show that, compared with EMD, EEMD and other methods, the CEEMDAN-WT method can effectively suppress the influence of random noise and improve the signal-to-noise ratio. The refined reconstruction effect of the seismic signal is better, and the effective components of the signal are largely preserved.
GUO Xiaofei,OU Tonggeng,MA Wugang et al. A New Random Noise Attenuation Method of Seismic Signal Based on CEEMDAN and Wavelet Transform[J]. jgg, 2022, 42(11): 1202-1206.