Abstract：To solve the reorganization problem of seismic events with low signal to noise ratio, the weighted nuclear norm minimization (C-WNNM) method was proposed to suppress the random noise in seismic data. The low rank approximation theory was presented based on WNNM. The low rank approximate matrices were constructed according to the similar characteristics of seismic signals in time and space domain. The IMF1 component obtained from CEEMD decomposition was used to estimate the local noise variance and lead to more accurate weights. The final denoising signal was obtained by iterative approximation. The C-WNNM method was used to process the simulated seismic exploration data generated by ricker wavelets. The results show that the proposed method can remove random noise effectively and preserve the effective signals well in the presence of strong noise in seismic data. The signal to noise ratio filtered by C-WNNM is promoted by about 3 dB than original WNNM.
2017, Vol. 38 
