TY - JOUR
T1 - Seismic random noise attenuation using MVMD and MSSA
AU - Zhang, Haoran
AU - Zhang, Yijie
AU - Yang, Yang
AU - Liu, Naihao
AU - Wang, Zhiguo
AU - Gao, Jinghuai
N1 - Publisher Copyright:
© 2021 Society of Exploration Geophysicists First International Meeting for Applied Geoscience & Energy
PY - 2021
Y1 - 2021
N2 - Seismic random noise attenuation plays an important role in seismic signal processing and geological interpretation. Due to seismic signal is a typical broadband signal, which makes it difficult to attenuate random noises contained in the whole frequency of raw seismic data. Moreover, tunning parameters in denoising methods is a difficult task, especially for filtering field data. To address the above issues, We propose a multichannel denoising scheme, termed as multi-channel variational mode decomposition (MVMD) based multi-channel singular spectrum analysis (MSSA). The proposed method first decomposes seismic data into several intrinsic mode functions (IMFs) with different center frequencies and bandwidths. Then, we adopt MSSA for each IMF by selecting different tunning parameters. To demonstrate the effectiveness of the proposed method, we apply it to field data and compare the filtered results with the traditional methods.
AB - Seismic random noise attenuation plays an important role in seismic signal processing and geological interpretation. Due to seismic signal is a typical broadband signal, which makes it difficult to attenuate random noises contained in the whole frequency of raw seismic data. Moreover, tunning parameters in denoising methods is a difficult task, especially for filtering field data. To address the above issues, We propose a multichannel denoising scheme, termed as multi-channel variational mode decomposition (MVMD) based multi-channel singular spectrum analysis (MSSA). The proposed method first decomposes seismic data into several intrinsic mode functions (IMFs) with different center frequencies and bandwidths. Then, we adopt MSSA for each IMF by selecting different tunning parameters. To demonstrate the effectiveness of the proposed method, we apply it to field data and compare the filtered results with the traditional methods.
UR - https://www.scopus.com/pages/publications/85120972033
U2 - 10.1190/segam2021-3583350.1
DO - 10.1190/segam2021-3583350.1
M3 - 会议文章
AN - SCOPUS:85120972033
SN - 1052-3812
VL - 2021-September
SP - 1111
EP - 1115
JO - SEG Technical Program Expanded Abstracts
JF - SEG Technical Program Expanded Abstracts
T2 - 1st International Meeting for Applied Geoscience and Energy
Y2 - 26 September 2021 through 1 October 2021
ER -