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| 1 | Study on the Source Characteristics of Downhole Airgun with Different Excitation Environments显示文摘The measurement of underground medium variation using a repeated artificial source has gradually become an important goal to pursue. In recent years,we have developed and improved a technology system with large capacity airguns excited in land reservoirs by transplanting marine seismic exploration technology. The excitation effect has a close relationship to airgun capacity,water environment,and excitation conditions. In view that large capacity airgun must be excited without a water environment,we expand the system to use in downhole. Based on the BHS-2200 LL downhole airgun with a capacity of250in3,this paper carries out a comparative analysis on the characteristics of an airgun source excited in 0. 2m- and 5. 0m-diameter wells,and the results show that:( 1) The dominant frequency of the airgun signal excited in a 5. 0m well is mainly from 10 Hz to40Hz,lower than that in a 0. 2m well,and the larger body of water is good for bubble oscillation.( 2) In terms of exciting energy,the signal excited in a 5. 0m well has stronger energy than in a 0. 2m well,with a difference of 1 order in magnitude,and the signal can be detected up to 9km excited in a 5. 0m well with a single shot.( 3) The airgun signal has good repeatability in both excitation wells. The downhole airgun excitation technology system has potential application in dynamic monitoring near a fault zone with a small scale range, exploration of oil and mineral resources, and modern urban geophysical environment. | Yang Wei Wang Baoshan Liu Zhengyi Yang Jun Li Xiaobin Chen Yong | 2016 | Earthquake Research in China2016，30，3： | 2 |
| 2 | Weak Seismic Signal Extraction Based on the Curvelet Transform显示文摘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. | TAN Junqing YANG Runhai WANG Bin XIANG Ya | 2019 | Earthquake Research in China2019，33，2： | 1 |
| 3 | Amplitude variation characteristics of active source airgun signals at Qilian Mountain显示文摘In this study,Qilian Mountain active source airgun signals recorded at 79 stations were obtained after stacking waveforms from July 2015 to December 2016.Based on analysis of the amplitude variation characteristics of the airgun signals,the following conclusions were drawn:along the NW-SE fault distribution direction of the Qilian Mountain area,the decrease in amplitude of airgun signals was relatively slow in relation to the epicentral distance,while the decrease in amplitude in the direction perpendicular to the fault was relatively fast.This difference may be related to the energy loss of seismic waves reflecting and scattering by the regional faults mainly distributed along the NW-SE direction,which are caused by tectonic compression of the QinghaiTibet and Alxa blocks. | Xuzhou Liu Yuansheng Zhang Zhiguo Liu Manzhong Qin Rui Zou Xiao Guo | 2021 | Earthquake Science2021，34，2： | 0 |
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