Automatic P‐ and S‐Wave Local Earthquake Tomography: Testing Performance of the Automatic Phase‐Picker Engine “RSNI‐Picker”
Automatic P‐ and S‐Wave Local Earthquake Tomography: Testing Performance of the Automatic Phase‐Picker Engine “RSNI‐Picker”
复制标题
自动纵波和横波局地地震层析成像：测试自动选相器引擎“RSNI-Picker”的性能
DOI：
--
复制
发表时间：
2016
期刊：
影响因子：
--
通讯作者：
A. Viganò
中科院分区：
文献类型：
--
作者：
D. Scafidi;D. Spallarossa;Chiara Turino;G. Ferretti;A. Viganò
在这项工作中，我们测试了一个全自动的程序，以获得当地的地震层析成像（LET），从地震波形开始，并应用自动相位选择器和定位器引擎“RSNI-Picker”的能力（Spallarossa等。，2014），其基于对P和S到达时间起作用的多步迭代过程。该代码目前作为热那亚大学地震监测系统的一部分运行（RSNI指定意大利西北部的区域地震网络）。特别是，我们将使用这种全自动拾取和定位程序获得的P波和S波层析成像结果与基于精确手动拾取和修改位置的数据获得的结果进行了比较。
我们使用的数据集的409个地震发生在特伦蒂诺地区（意大利东北部）在1994-2007年期间。高度可变的波形质量（例如，由于记录台站配备了不同类型的传感器和数字化仪（包括单分量窄带地震台站和三分量宽带地震台站），因此对自动程序的测试要求很高（信噪比），这确保了对自动程序的严格测试。
特伦蒂诺地区两种三维速度传播模型的比较（即，LET图像），显示P波和S波的最大差异分别为0.54和0.34 km/s（如果我们考虑所有计算的绝对速度的90%，作为参考百分比）。自动LET显示速度异常分布和可靠性模式（例如，分辨率对角元素[RDE]值）与使用手动程序获得的结果相似; 90%的RDE差异低于0.15。
通过测试RSNI-Picker引擎获得的结果表明，它可用于自动处理大量地震记录，以识别P和S波拾取，从而进行可靠的LET分析。
In this work, we test a fully automatic procedure to obtain local earthquake tomography (LET), starting from seismic waveforms and applying the capability of the automatic phase picker and locator engine “RSNI‐Picker” (Spallarossa et al. , 2014), which is based on a multistep iterative procedure working on P and S arrival times. This code is currently operating as part of the Earthquake Monitoring System at the University of Genoa (RSNI designates the regional seismic network of northwestern Italy). In particular, we compare P ‐ and S ‐wave tomographic results obtained using this fully automatic procedure for picking and locations with those based on data from accurate manual picking and revised locations.
We use a dataset of 409 earthquakes that occurred in the Trentino region (Northeastern Italy) in the 1994–2007 period. The highly variable waveform qualities (e.g., signal‐to‐noise ratio), mainly due to recording stations equipped with different types of sensors and digitizers (including both one‐component narrowband stations and three‐component broadband seismic stations), ensure a severe test for the automatic procedure.
The comparison of the two 3D velocity propagation models for the Trentino region (i.e., LET images) from the automatic and manual procedures, shows maximum differences of 0.54 and 0.34 km/s for P and S waves, respectively (if we consider 90% of all the computed absolute velocities, as a reference percentage). The automatic LET shows velocity anomaly distributions and reliability patterns (e.g., resolution diagonal element [RDE] values) similar to those obtained using the manual procedure; 90% of RDE differences are lower than 0.15.
The results obtained by testing the RSNI‐Picker engine suggest it can be used to automatically process large amounts of seismic recordings in order to identify P and S wavepicks for reliable LET analysis.