气枪震源波形走时变化分析的反褶积处理
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摘要
利用云南省宾川主动源基地周边10 km范围内7个流动台站2017年2月气枪震源集中激发时段记录的气枪信号,使用干涉法计算了直接使用波形和将波形与参考台反褶积后的格林函数两种处理方法下气枪信号的走时变化。使用了气枪震源附近不同方位角的两个参考台的数据,以分析不同参考台对走时变化结果的影响。结果表明:反褶积能较为有效的压制气枪震源的时间、空间和频谱轻微不重复性导致的走时变化;反褶积能降低一些来源不明的伪走时变化;使用CKT2的数据反褶积的结果略优于CKT0,其可能原因是气枪阵列沿方位角的非均匀辐射。
Using the airgun signals recorded by seven mobile stations within 10 km range around the active source base of Binchuan, Yunnan Province, during the concentrated excitation period of the air gun source in February 2017, the travel time variation of the airgun signals under two processing methods, i.e. the direct waveform and the deconvolution of the waveform with the Green's function of the reference station, is calculated by the interference method. The data of two reference stations with different azimuths near the air gun source are used to analyze the influence of different reference stations on the results of travel time variation. The results show that deconvolution can effectively suppress the travel time variation caused by slight non-repetition of time,space and frequency spectrum of air gun source; deconvolution can reduce some pseudo-travel time variation caused by unknown sources; data deconvolution using CKT2 is slightly better than CKT0, which may be due to the non-uniform radiation of air gun array along azimuth.
Using the airgun signals recorded by seven mobile stations within 10 km range around the active source base of Binchuan, Yunnan Province, during the concentrated excitation period of the air gun source in February 2017, the travel time variation of the airgun signals under two processing methods, i.e. the direct waveform and the deconvolution of the waveform with the Green's function of the reference station, is calculated by the interference method. The data of two reference stations with different azimuths near the air gun source are used to analyze the influence of different reference stations on the results of travel time variation. The results show that deconvolution can effectively suppress the travel time variation caused by slight non-repetition of time,space and frequency spectrum of air gun source; deconvolution can reduce some pseudo-travel time variation caused by unknown sources; data deconvolution using CKT2 is slightly better than CKT0, which may be due to the non-uniform radiation of air gun array along azimuth.
引文
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[2]陈颙,朱日祥.设立“地下明灯研究计划”的建议[J].地球科学进展,2005, 20(5):485-489.
[3]陈蒙.利用水库大容量非调制气枪阵列进行区域尺度地下结构探测和监测[D].北京:中国地震局地球物理研究所, 2014.
[4]姚道平,张艺峰,闫培,等.台湾海峡大容量气枪震源海陆联测初探[J].地震学报,2016, 38(2):167-178.
[5]林彬华,金星,李军,等.台网噪声评估及其对气枪震源激发效果影响的研究[J].地震学报,2017, 39(3):330-342.
[6]谢凡,任雅琼,王宝善.利用超声尾波观测1.5 m长岩石断层黏滑实验的波速变化[J].地球物理学报,2017, 60(4):1470-1478.
[7] Sheriff R E,Geldart L P. Exploration Seismology(Second Edition)[M]. Cambredge University Press,1995.
[8]周青云.宾川地震信号发射台气枪震源能量激发方向性初步研究[J].大地测量与地球动力学,2018, 38(7):754-759.
[9]杨微,葛洪魁,王宝善,等.由精密控制人工震源观测到的绵竹5.6级地震前后波速变化[J].地球物理学报,2010, 53(5):1149-1157.
[10]刘自凤,苏有锦,王宝善,等.宾川主动源地震波走时变化分析方法研究[J],地震研究,2015, 38(4):591-597.
[11]魏芸芸,王海涛,苏金波,等.新疆2次中强地震前气枪震源反射波震相走时异常变化初步研究[J].中国地震,2016, 32(2):270-281.
[12]陈佳,叶泵,高琼,王军,等.利用气枪震源信号研究2016年云龙MS5.0地震前后波速变化特征[J].地震研究,2017, 40(4):550-556.
[13]黄亦磊,运乃丹,周仕勇.台差法提高低信噪比下走时变化探测精度的研究[J].地震研究,2017, 40(4):595-604.
[14] Niu F,Silver P G,Daley T M, et al. Preseismic Velocity Changes Observed from Active Source Monit oring at the Parkfield SAFOD Drill Site[J]. Nature, 2008, 454(7201):204-208.
[15] Wang B S,Zhu P,Chen Y,et al. Continuous Subsurface Velocity Measurement with Coda Wave Interferometry[J].Journal of Geophysical Research, 2008(113):B12313.
[16]张元生,王宝善,陈颙,等.两次强震发生前后主动源观测走时数据的变化[J].地球物理学报,2017, 60(10):3815-3822.
[17]王彬,吴国华,苏有锦,等.宾川地震信号发射台的选址、建设及初步观测结果[J].地震研究,2015, 38(1):1-6.
[18]王彬,李孝宾,刘自凤,等.宾川地震信号发射台的震源系统、观测系统和观测结果[J].中国地震,2016, 32(2):193-201.
[19] Snieder R, Grêt A, Douma H, et al. Coda wave interferometry for estimating nonlinear behavior in seismic velocity[J]. Science,2002, 295(5563):253-255.
[20]陈佳,李孝宾,杨军,等.云南宾川大容量气枪震源波形频谱特征分析[J].中国地震,2016, 32(2):216-221.
[21]栾奕,杨宏峰,王宝善.大容量气枪主动源波形资料处理(一):云南宾川[J].中国地震,2016, 32(2):305-318.
[22]周青云,刘自凤,贺素歌.气枪震源地震波走时变化影响因素分析及地震相关的走时变化[J].地震,2018, 38(3):144-157.