In this paper, we propose a novel picking algorithm for the automatic P- and S- waves onset time determination. Our algorithm is based on the variance piecewise constant models of the earthquake waveforms. The effectiveness and robustness of our picking algorithm are tested both on synthetic seismograms and real data. We simulate seismic events with different magnitudes (between 2 and 5) recorded at different epicentral distances (between 10 and 250 km). For the application to real data, we analyse waveforms from the seismic sequence of L'Aquila (Italy), in 2009. The obtained results are compared with those obtained by the application of the classic STA/LTA picking algorithm. Although the two algorithms lead to similar results in the simulated scenarios, the proposed algorithm results in greater flexibility and automation capacity, as shown in the real data analysis. Indeed, our proposed algorithm does not require testing and optimization phases, resulting potentially very useful in earthquakes routine analysis for novel seismic networks or in regions whose earthquakes characteristics are unknown.

Nicoletta D'Angelo, Andrea Di Benedetto, Giada Adelfio, Antonino D'Alessandro, Marcello Chiodi (2022). A new picking algorithm based on the variance piecewise constant models. STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT [10.1007/s00477-022-02218-x].

A new picking algorithm based on the variance piecewise constant models

Nicoletta D'Angelo
;
Andrea Di Benedetto;Giada Adelfio;Antonino D'Alessandro;Marcello Chiodi
2022-01-01

Abstract

In this paper, we propose a novel picking algorithm for the automatic P- and S- waves onset time determination. Our algorithm is based on the variance piecewise constant models of the earthquake waveforms. The effectiveness and robustness of our picking algorithm are tested both on synthetic seismograms and real data. We simulate seismic events with different magnitudes (between 2 and 5) recorded at different epicentral distances (between 10 and 250 km). For the application to real data, we analyse waveforms from the seismic sequence of L'Aquila (Italy), in 2009. The obtained results are compared with those obtained by the application of the classic STA/LTA picking algorithm. Although the two algorithms lead to similar results in the simulated scenarios, the proposed algorithm results in greater flexibility and automation capacity, as shown in the real data analysis. Indeed, our proposed algorithm does not require testing and optimization phases, resulting potentially very useful in earthquakes routine analysis for novel seismic networks or in regions whose earthquakes characteristics are unknown.
2022
Settore SECS-S/01 - Statistica
Nicoletta D'Angelo, Andrea Di Benedetto, Giada Adelfio, Antonino D'Alessandro, Marcello Chiodi (2022). A new picking algorithm based on the variance piecewise constant models. STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT [10.1007/s00477-022-02218-x].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10447/535834
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