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Noisy Dispersion Curve Picking (NDCP): A Matlab package for group velocity dispersion picking of seismic surface waves

机译:噪声色散曲线拾取(NDCP):用于地震面波群速度色散拾取的Matlab软件包

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We developed a Matlab package, Noisy Dispersion Curve Picking (NDCP), which allows full control over several parameters to properly identify group velocity dispersion curves using two types of datasets: i) Green's Functions recovered from cross-correlations between pairs of stations and ii) earthquake surface waves.In seismic noise analysis, a non-homogeneous distribution of noise sources could lead to a non-symmetric reconstruction of the Green's function. In such a case NDCP allows to the user to pick the dispersion curve in the time domain both in the causal and anticausal part of the signal, allowing retrieval of more complete information. Furthermore, NDCP applies a narrow filtering to the signal allowing for better judgment of which periods can be reliably picked. Then the picked dispersion curve is displayed on the Frequency Time diagram in order to verify that it matches the maximum of the signal energy and avoids confusion with other spikes of energy or overtones. The same procedure is applied to earthquake data where the picking is also carried out in the time domain.To illustrate how NDCP performs, we show three examples: i) local scale correlograms functions obtained from sensors deployed into a geothermal-volcanic caldera, ii) regional scale correlograms functions between two stations installed by the Mexican National Seismological Service, and iii) the surface waves from an earthquake in the Pacific Ocean near the coast of Mexico.
机译:我们开发了Matlab软件包“噪声色散曲线拾取(NDCP)”,该软件包可以使用两种类型的数据集完全控制几个参数以正确识别组速度色散曲线:i)从测站对之间的互相关中恢复的格林函数,以及ii)在地震噪声分析中,噪声源的不均匀分布可能导致格林函数的非对称重建。在这种情况下,NDCP允许用户在信号的因果和反因果部分中选取时域中的色散曲线,从而可以检索到更完整的信息。此外,NDCP对信号进行窄滤波,从而可以更好地判断可以可靠地选择哪些周期。然后,在频率时间图上显示拾取的色散曲线,以验证其与信号能量的最大值匹配,并避免与其他能量尖峰或泛音混淆。对于在时域也进行拾取的地震数据也采用了相同的步骤。为说明NDCP的性能,我们展示了三个示例:i)从部署到地热火山破火山口中的传感器获得的局部比例相关函数,ii)墨西哥国家地震局在两个站点之间建立了区域比例相关图,并且iii)墨西哥海岸附近太平洋发生的地震地表波。

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