论文部分内容阅读
提出了一种称为震源扫描算法(SSA)的新方法,用来绘制震源的时空分布。利用试验地点和发震时间,这种方法通过对所有台站在它们理论到时处观测到的绝对振幅求和来计算“亮度”函数。然后,对整个模型的空间和时间进行系统的搜索,寻找“亮度”函数最大值来确定震源的时空分布。这种方法的最大优点是:(1)不需要计算高频率理论地震图就可以获得波形信息(包括到时和相对振幅);(2)既不需要对震源的几何特征做任何先验的假设也不需要拾取预先组合的相位数据。使用合成数据进行的一系列测试表明,这种方法是健全的并且能够在一个网格间隔中如实地还原震源结构。最后,我们通过对最近的卡斯凯迪亚北部消减带偶发的颤动及滑动产生的波形数据定位了一个典型的颤动事件,以此来证明震源扫描算法的有效性。
A new method called source scanning algorithm (SSA) is proposed to map the spatiotemporal distribution of hypocenters. Using the test site and the onset time, this method computes the “brightness” function by summing the absolute amplitudes observed by all stations at the time of their arrival. Then, we search the space and time of the whole model systematically to find the maximum value of the “brightness” function to determine the spatiotemporal distribution of the hypocenter. The major advantages of this approach are: (1) waveform information (including arrival and relative amplitudes) can be obtained without the need to calculate high-frequency theoretical seismograms; (2) neither a priori assumption on the geometry of the source is required It is also not necessary to pick up the pre-combined phase data. A series of tests using synthetic data show that this approach is robust and enables faithful restoration of hypocenters within a grid interval. Finally, we demonstrate the effectiveness of the source-scanning algorithm by locating a typical chatter event on the waveform data generated by the recent chatter and slip with incidental attenuation in northern Cascadia.