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Weak Seismic Signal Extraction Based on the Curvelet Transform
TAN Junqing1, YANG Runhai2, WANG Bin2, XIANG Ya3
1.Yunnan University, Kunming 650091, China;2.Yunnan Earthquake Agency, Kunming 650224, China;3.Key Laboratory of Earthquake Geodesy, Institute of Seismology, China Earthquake Administration, Wuhan 430071, China
摘要:
Seismic signal denoising is a key step in seismic data processing. Airgun signals are easy to be interfered with by noise when it travels a long distance due to the weak energy of active source signal of the airgun. Aiming to solve this problem, and considering that the conventional Curvelet transform threshold processing method does not use the seismic spectrum information, we independently process the Curvelet scale layer corresponding to valid data based on the characteristics of the Curvelet transform of multi-scale, multi-direction and capable of expressing the sparse seismic signals in order to fully excavate the information features. Combined with the Curvelet adaptive threshold denoising the algorithm, we apply the Curvelet transform to denoising seismic signals while retaining the weak information in the signal as much as possible. The simulation experiments show that the improved threshold denoising method based on Curvelet transform is superior to the frequency domain filtering, wavelet denoising and traditional Curvelet denoising method in detailed information extraction and signal denoising of low SNR signals. The calculation accuracy of the relative wave velocity variation of underground medium is improved.
关键词:  Seismic signal denoising  Airgun active source signal  Curvelet transform  The velocity of the underground medium
DOI:10.19743/j.cnki.0891-4176.201902011
分类号:
基金项目:This project is sponsored by the National Natural Science Foundation of China (41574059, 41474048) and sponsored by the State Key Laboratory of Earthquake Dynamics,CEA (LED2016B06).
Weak Seismic Signal Extraction Based on the Curvelet Transform
TAN Junqing1, YANG Runhai2, WANG Bin2, XIANG Ya3
1.Yunnan University, Kunming 650091, China;2.Yunnan Earthquake Agency, Kunming 650224, China;3.Key Laboratory of Earthquake Geodesy, Institute of Seismology, China Earthquake Administration, Wuhan 430071, China
Abstract:
Seismic signal denoising is a key step in seismic data processing. Airgun signals are easy to be interfered with by noise when it travels a long distance due to the weak energy of active source signal of the airgun. Aiming to solve this problem, and considering that the conventional Curvelet transform threshold processing method does not use the seismic spectrum information, we independently process the Curvelet scale layer corresponding to valid data based on the characteristics of the Curvelet transform of multi-scale, multi-direction and capable of expressing the sparse seismic signals in order to fully excavate the information features. Combined with the Curvelet adaptive threshold denoising the algorithm, we apply the Curvelet transform to denoising seismic signals while retaining the weak information in the signal as much as possible. The simulation experiments show that the improved threshold denoising method based on Curvelet transform is superior to the frequency domain filtering, wavelet denoising and traditional Curvelet denoising method in detailed information extraction and signal denoising of low SNR signals. The calculation accuracy of the relative wave velocity variation of underground medium is improved.
Key words:  Seismic signal denoising  Airgun active source signal  Curvelet transform  The velocity of the underground medium