Open AccessSeismic signal denoising method based on CEEMD and improved wavelet threshold
Author(s) -
Qiao Ye,
Qiong Li,
Haodong Qian,
Xin Song
Publication year - 2021
Publication title -
iop conference series. earth and environmental science
Language(s) - English
Resource type - Journals
eISSN - 1755-1307
pISSN - 1755-1315
DOI - 10.1088/1755-1315/671/1/012036
Subject(s) - noise reduction , wavelet , hilbert–huang transform , noise (video) , signal (programming language) , discontinuity (linguistics) , signal to noise ratio (imaging) , pattern recognition (psychology) , computer science , mathematics , algorithm , white noise , artificial intelligence , statistics , programming language , mathematical analysis , image (mathematics)
Seismic data usually contains a lot of noise. In order to effectively remove noise and improve the signal-to-noise ratio of seismic signals, this paper proposes a method of combining complete empirical mode decomposition (CEEMD) with improved wavelet threshold denoising.method. CEEMD has good adaptability to signal decomposition; the new wavelet threshold function can effectively overcome the discontinuity of hard threshold function and the deviation of wavelet coefficients in soft threshold function. The combination of the two methods can obtain better denoising effect. After processing the simulated signal with the method proposed in this paper, the signal-to-noise ratio is significantly better than the traditional single denoising method.