The Binchuan region of Yunnan is a structurally complex region with mountains,basins,and active faults.In this situation,seismic wave propagation exhibits complex characteristics due to strong heterogeneity of undergr...The Binchuan region of Yunnan is a structurally complex region with mountains,basins,and active faults.In this situation,seismic wave propagation exhibits complex characteristics due to strong heterogeneity of underground media instead of following the great-circle path.In order to obtain a high-resolution shallow crustal structure,a dense seismic array was deployed during March 21 to May 30,2017 in this area.To better understand the complexities of seismic wave propagation in this region,we perform array-based frequency-domain beamforming analysis and single-station based polarization analysis to investigate the characteristics of seismic wave propagation,using airgun-generated P-wave signals recorded by dense array stations in this experiment.The results from these two methods both reveal similar but complex characteristics of seismic wave propagation in the Binchuan basin.The azimuth anomalies off the great-circle path are quite large with values up to 30°,which is caused by strong structural heterogeneity in the very shallow crust.Our research provide a better understanding of the complex geologic structures in this area and provide guidance for detecting concealed faults and distribution of velocity anomalies.展开更多
Repeating airgun sources are eco-friendly sources for monitoring the changes in the physical properties of subsurface mediums,but their signals decay quickly and are buried in the noises soon after traveling short dis...Repeating airgun sources are eco-friendly sources for monitoring the changes in the physical properties of subsurface mediums,but their signals decay quickly and are buried in the noises soon after traveling short distances.Stacking waveforms from different airgun shots recorded by a single seismic station(shot stacking)is the most popular technique to detect weak signals from noisy backgrounds,and has been widely used to process the data of Fixed Airgun Signal Transmission Stations(FASTS)in China.However,shot stacking sacrifices the time resolution in monitoring to recover a qualified airgun signal by stacking many shots at distance stations,and also suffers from persistent local noises.In this paper,we carried out several small-aperture seismic array experiments around the Binchuan FAST Station(BCFASTS)in Yunnan Province,China,and applied the array technique to improve airgun signal detection.The results show that seismic array processing combining with shot stacking can suppress seismic noises more efficiently,and provide better signal-to-noise ratio(SNR)and coherent airgun signals with less airgun shots.This work suggests that the array technique is a feasible and promising tool in FAST to increase the time resolution and reduce noise interference on routine monitoring.展开更多
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.Aim...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.展开更多
The Qilian Mountain active source network data was processed using the methods of stacking, cross-correlation and interpolation, and the airgun travel time variation characteristics of P and S waves around the January...The Qilian Mountain active source network data was processed using the methods of stacking, cross-correlation and interpolation, and the airgun travel time variation characteristics of P and S waves around the January 21,2016 MS6. 4 Menyua,Qinghai earthquake. The results show that about 6 months before the earthquake,the relative travel time of three stations near the epicenter showed a declined change( travel time decrease),and such a change of low value anomaly was recovered about 3 months before the earthquake. The travel time decrease then appeared again, and the earthquake occurred during the recovery process. The maximum decrease of the S-wave travel time was 18 ms,and the change in travel time returned to normal after the earthquake. The variation trend of the 3 stations is consistent,including the S-wave travel time change of station ZDY38,which is nearest to the epicenter and changed obviously,and the variation range of the travel time is smaller at the stations afar. This variation pattern is related to the position of the seismic source. The shorter travel time means the velocity increase,which may be related to the regional stress accumulation.展开更多
基金sponsored by the National Natural Science Foundation of China(GG2080000476)the China Earthquake Science Experiment Project,China Earthquake Administration(2017CESE0101,2018CSES0101)
文摘The Binchuan region of Yunnan is a structurally complex region with mountains,basins,and active faults.In this situation,seismic wave propagation exhibits complex characteristics due to strong heterogeneity of underground media instead of following the great-circle path.In order to obtain a high-resolution shallow crustal structure,a dense seismic array was deployed during March 21 to May 30,2017 in this area.To better understand the complexities of seismic wave propagation in this region,we perform array-based frequency-domain beamforming analysis and single-station based polarization analysis to investigate the characteristics of seismic wave propagation,using airgun-generated P-wave signals recorded by dense array stations in this experiment.The results from these two methods both reveal similar but complex characteristics of seismic wave propagation in the Binchuan basin.The azimuth anomalies off the great-circle path are quite large with values up to 30°,which is caused by strong structural heterogeneity in the very shallow crust.Our research provide a better understanding of the complex geologic structures in this area and provide guidance for detecting concealed faults and distribution of velocity anomalies.
基金jointly sponsored by National Natural Science Foundation of China(41574050,41674058)
文摘Repeating airgun sources are eco-friendly sources for monitoring the changes in the physical properties of subsurface mediums,but their signals decay quickly and are buried in the noises soon after traveling short distances.Stacking waveforms from different airgun shots recorded by a single seismic station(shot stacking)is the most popular technique to detect weak signals from noisy backgrounds,and has been widely used to process the data of Fixed Airgun Signal Transmission Stations(FASTS)in China.However,shot stacking sacrifices the time resolution in monitoring to recover a qualified airgun signal by stacking many shots at distance stations,and also suffers from persistent local noises.In this paper,we carried out several small-aperture seismic array experiments around the Binchuan FAST Station(BCFASTS)in Yunnan Province,China,and applied the array technique to improve airgun signal detection.The results show that seismic array processing combining with shot stacking can suppress seismic noises more efficiently,and provide better signal-to-noise ratio(SNR)and coherent airgun signals with less airgun shots.This work suggests that the array technique is a feasible and promising tool in FAST to increase the time resolution and reduce noise interference on routine monitoring.
基金sponsored by the National Natural Science Foundation of China(41574059,41474048)sponsored by the State Key Laboratory of Earthquake Dynamics,CEA(LED2016B06)
文摘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.
基金jointly funded by the Sparkle Program of China Earthquake Administration(XH17039)the Project on the Surface of the National Natural Science Foundation of China(41574044)
文摘The Qilian Mountain active source network data was processed using the methods of stacking, cross-correlation and interpolation, and the airgun travel time variation characteristics of P and S waves around the January 21,2016 MS6. 4 Menyua,Qinghai earthquake. The results show that about 6 months before the earthquake,the relative travel time of three stations near the epicenter showed a declined change( travel time decrease),and such a change of low value anomaly was recovered about 3 months before the earthquake. The travel time decrease then appeared again, and the earthquake occurred during the recovery process. The maximum decrease of the S-wave travel time was 18 ms,and the change in travel time returned to normal after the earthquake. The variation trend of the 3 stations is consistent,including the S-wave travel time change of station ZDY38,which is nearest to the epicenter and changed obviously,and the variation range of the travel time is smaller at the stations afar. This variation pattern is related to the position of the seismic source. The shorter travel time means the velocity increase,which may be related to the regional stress accumulation.
