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SH‑waveform modeling of small local seismic events in Ladoga lake

机译:Ladoga Lake小地方地震事件的SH波形建模

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摘要

A lot of seismic phenomena with small magnitude has been taking place in the Ladoga lake region (northwestern Russia).One of them is the earthquake which was recorded on the 31st of July, 2010 followed by the swarm of microearthquakesnear Nikonovsky cape. There is only one station in the region that is why it is difficult to process the data. In this work, wepropose a new approach to construct synthetic seismograms of the main event with minimum data. Also this approachapplies us to calculate parameters of the source. The approximate magnitude of the main event is M_L = −0.8 . For swarmevents, we have magnitude values from −1.0 to −2.6 . The data of swarm events (microearthquakes) is used to test thetechnique of constructing synthetic seismograms. The approach we propose is based on Green’s function method withusing two temporal -sequences (the Lorentzian function and the continuous Dirichlet kernel). A comparison of syntheticand real seismograms shows that the Lorentzian function is better to describe small local events, and the continuousDirichlet kernel is more appropriate for earthquakes. This approach can be generalized to various problems of differentnature.
机译:Ladoga Lake Region(俄罗斯西北部)正在进行大量少量幅度的地震现象。其中一个是在2010年7月31日录制的地震,然后是微微地震的群体靠近Nikonovsky Cape。该地区只有一个站点是为什么难以处理数据。在这项工作中,我们提出一种以最小数据构建主事件的合成地震图的新方法。也是这种方法适用于我们计算源的参数。主事件的近似幅度为m_l = -0.8。适合群体事件,我们的幅度值从-1.0到-2.6。群体事件(微焦点)的数据用于测试构建合成地震图的技术。我们提出的方法是基于绿色的功能方法使用两个时间序列(Lorentzian函数和连续Dirichlet内核)。合成的比较和真实的地震图表明,Lorentzian功能更好地描述小型本地事件,以及连续的Dirichlet Kernel更适合地震。这种方法可以推广到不同的各种问题自然。

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