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The Seasonal Variation of Large Volume Airgun Signals in Hutubi, Xinjiang
SU Jinbo1, WANG Qiong1, ZHANG Wenxiu1, WEI Yunyun1, CHEN Hao2, WANG Haitao3
1.Earthquake Agency of Xinjiang Uygur Autonomous Region, Urumqi 830011, China;2.First Monitoring Center of China Earthquake Administration, Tianjin 300180, China;3.China Earthquake Networks Center, Beijing 100045, China
摘要:
In order to study the seasonal variation of large volume airgun signals in Hutubi, Xinjiang, we analyzed 2,936 signals of airgun source excitations during 2015-2016 received by a seismograph on the bank of the excitation pool. Firstly, the RMS value of the signal amplitude and the daily average temperature were compared after linearly superimposing the signal in days, to analyze the influence of the surface ice cover on the excitation energy release of the airgun source. The result shows that the ice cover will reduce the excitation energy, and the thicker the ice cover is, the more obvious the excitation energy reduces. Secondly, the time-frequency analysis method was used to analyze the influence of the surface ice cover on the signal frequency. It is concluded that the existence of the ice cover has little effect on the signal frequency, but it will affect the intensity of the signal around 4Hz between 1-2s after excitation. The cause of these phenomena is that the ice cover affects the bubble oscillation, which in turn affects the energy conversion. The study shows that when using the cross-correlation delay method to calculate the wave velocity, the signals can be divided into two periods according to the daily average temperature:with or without ice cover on the upper surface of the excitation pool. This can help eliminate the influence of the source variation and improve the accuracy of the monitoring results.
关键词:  airgun source  seasonal variation  signal energy  signal frequency
DOI:10.19743/j.cnki.0891-4176.201902010
分类号:
基金项目:This project sponsored by the National Key Research and Development Program (2018YFC1503200), the National Natural Science Foundation (41474051), Xinjiang Project Aided by Institute of Earthquake Forecasting of China Earthquake Administration(2016IES0103)and the Xinjiang Seismological Science Fund (201902).
The Seasonal Variation of Large Volume Airgun Signals in Hutubi, Xinjiang
SU Jinbo1, WANG Qiong1, ZHANG Wenxiu1, WEI Yunyun1, CHEN Hao2, WANG Haitao3
1.Earthquake Agency of Xinjiang Uygur Autonomous Region, Urumqi 830011, China;2.First Monitoring Center of China Earthquake Administration, Tianjin 300180, China;3.China Earthquake Networks Center, Beijing 100045, China
Abstract:
In order to study the seasonal variation of large volume airgun signals in Hutubi, Xinjiang, we analyzed 2,936 signals of airgun source excitations during 2015-2016 received by a seismograph on the bank of the excitation pool. Firstly, the RMS value of the signal amplitude and the daily average temperature were compared after linearly superimposing the signal in days, to analyze the influence of the surface ice cover on the excitation energy release of the airgun source. The result shows that the ice cover will reduce the excitation energy, and the thicker the ice cover is, the more obvious the excitation energy reduces. Secondly, the time-frequency analysis method was used to analyze the influence of the surface ice cover on the signal frequency. It is concluded that the existence of the ice cover has little effect on the signal frequency, but it will affect the intensity of the signal around 4Hz between 1-2s after excitation. The cause of these phenomena is that the ice cover affects the bubble oscillation, which in turn affects the energy conversion. The study shows that when using the cross-correlation delay method to calculate the wave velocity, the signals can be divided into two periods according to the daily average temperature:with or without ice cover on the upper surface of the excitation pool. This can help eliminate the influence of the source variation and improve the accuracy of the monitoring results.
Key words:  airgun source  seasonal variation  signal energy  signal frequency