地震研究

挑选了2013年以来信噪比较高、数据较为完整的6个宾川主动源接收台站的气枪记录数据,采用互相关时延检测、近场校正等技术进行了高精度波速变化测量,得到以下初步结果:(1)接收台站下方介质存在δv/v≈10^-5～10^-2的相对波速变化;(2)2014年9月初至10月底,初至波走时变化较平稳,集中在-0.01～0.01 s之间变化,且6个台的变化趋势一致。

Firstly,we chose the complete data with high signal-to-noise ratio recorded by six receiving stations of active source in Binchuan County since 2013. Secondly,we measured the velocity change with high precision by using cross-correlation delay detection,near-field correction technique etc.. Finally,the conclusions are obtained as follow:(1)The relative velocity variation was δv/v≈10^-5～10^-2 in the medium beneath the stations.(2)From early Sep.,2014 to the end of Oct.,2014,the travel time variations of initial wave was relatively stable which was between -0.01 s and 0.01 s,and the change trend of waveform recorded by six selected stations was same.

引言
1 互相关时延检测技术原理
2 资料及数据处理过程介绍
3 处理结果
4 结论与讨论

图1 2013-01-07～2014-10-24宾川主动源发射基地气枪激发次数<br/>Fig.1 Transmitting frequency of airguns at Binchuan transmitting seismic station(TSS)from Jan.7,2013 to Oct.24,2014

图1 2013-01-07～2014-10-24宾川主动源发射基地气枪激发次数
Fig.1 Transmitting frequency of airguns at Binchuan transmitting seismic station(TSS)from Jan.7,2013 to Oct.24,2014

图2 台站分布示意图(a)及6个台的原始波形(b)<br/>Fig.2 Sketch diagram of station distribution(a)and the original waveforms recorded by six stations(b)

图2 台站分布示意图(a)及6个台的原始波形(b)
Fig.2 Sketch diagram of station distribution(a)and the original waveforms recorded by six stations(b)

图3 数据处理流程图<br/>Fig.3 Flow chart of data processing

图3 数据处理流程图
Fig.3 Flow chart of data processing

图4 波形预处理过程(a)原始波形;(b)去均值、去趋势后的波形;(c)滤波后的波形<br/>Fig.4 Preprocessing process for waveform (a)the original waveform;(b)the waveform after averaged and removed trend;(c)the waveform after filtering

图4 波形预处理过程(a)原始波形;(b)去均值、去趋势后的波形;(c)滤波后的波形
Fig.4 Preprocessing process for waveform (a)the original waveform;(b)the waveform after averaged and removed trend;(c)the waveform after filtering

图5 反卷积过程(a)参考台记录;(b)远台记录;(c)格林函数<br/>Fig.5 The process of deconvolution (a)recording of reference station;(b)recording of distant station;(c)green's function

图5 反卷积过程(a)参考台记录;(b)远台记录;(c)格林函数
Fig.5 The process of deconvolution (a)recording of reference station;(b)recording of distant station;(c)green's function

图6 互相关时延检测示意图(a)参考模板;(b)格林函数(2013-01-07);(c)相关系数;(d)走时t1;(e)走时t2<br/>Fig.6 Schematic diagram of detecting time delay by using cross correlation technique (a)reference template;(b)green's function(2013-01-07);(c)correlation coefficient;(d)travel time t1;(e)travel time t2

图6 互相关时延检测示意图(a)参考模板;(b)格林函数(2013-01-07);(c)相关系数;(d)走时t1;(e)走时t2
Fig.6 Schematic diagram of detecting time delay by using cross correlation technique (a)reference template;(b)green's function(2013-01-07);(c)correlation coefficient;(d)travel time t1;(e)travel time t2

图7 6个台站不同时段的初至波走时变化曲线(a)2013-01-01～2014-10-31;(b)2013-01-01～2013-06-01;(c)2013-09-01～2014-06-01;(d)2014-09-01～2014-10-31<br/>Fig.7 Travel time variation curves of primary waves recorded by 6 stations in different period

图7 6个台站不同时段的初至波走时变化曲线(a)2013-01-01～2014-10-31;(b)2013-01-01～2013-06-01;(c)2013-09-01～2014-06-01;(d)2014-09-01～2014-10-31
Fig.7 Travel time variation curves of primary waves recorded by 6 stations in different period

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备注

引言

1 互相关时延检测技术原理

2 资料及数据处理过程介绍

3 处理结果

4 结论与讨论

期刊信息