Input file specification

The application requires a MiniSEED Waveform (or any subtype) containing seismograms on which the wave arrival time should be detected. The waveform has to contain E, N and Z channels for each station.

Figure 1. Application input files specification

Filling form values

The application form consists of four five parameters - see Figure 2. The first parameter allows you to choose the model used for the the detection - GPD or PhaseNet (see [1] and [2], respectively). Each model was originally trained on a set of data described in the respective publication, the weights obtained by training the Machine Learning model, where the Original option are the based on that training are set as default, however, different weights may be chosen depending on the characteristic of the input data by modifying the Pretrained model weights field. The Original option should be set to use the default, original weights published by the authors of the models ([1] for the GPD model and [2] , while to use one of the weights obtained for public data described in [3] use one of the ETHZ, GEOFON, INSTANCE, Iquique, LenDB, NEIC, SCEDC and STEAD options. Additionally, for the PhaseNet model), and all the others there are also weights obtained by training on BOGDANKA and LGCD¹ episodes available. See Figure 3 for detailed view of the available weights.

To configure the sensitivity of the phase detection, use for public data described in [3]. The Stride parameter sets the stride in samples for point prediction models, and the P phase threshold and the S phase threshold set (see Figure 2), which determine the threshold of the probability for which the phase is detected.we assume a detection. 

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Figure 2. Application form with values filled

[1] Ross, Meier, Hauksson and Heaton (2018). Generalized Seismic Phase Detection with Deep Learning. doi: 10.1785/0120180080.

[2] Zhu, W., & Beroza, G. C. (2019). PhaseNet: a deep-neural-network-based seismic arrival-time picking method. doi: 10.1093/gji/ggy423

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Figure 3. Available values of the Pretrained model weights

Produced output

The main output of the application is a QuakeML file containing picks marking the phase detections. The file is named after the input MiniSEED file with -picks.xml suffix added. The picks are displayed on the original input file within the application output view (Figure 34).

Figure 34. Application output - MiniSEED waveform with resulting picks displayed

As an additional information, the application provides also the detection probability values, saved to the file named after the input MiniSEED with -annotations.mseed suffix added. The probability can be examined (see Figure 45 and Figure 56) after expanding the Wave detection probability option (bottom of Figure 34).

Figure 45. Application output - wave detection probability

Figure 56. Details of detection pobability probability plots, for phase P, phase S and noise

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