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Local Seismic Events in the Area of Poland Based on Data from the PASSEQ 2006-2008 Experiment

Polkowski M., Plesiewicz B., Wiszniowski J., Wilde-Piórko M.

Acta Geophysica

2016

Vol. 64, no. 6

2092--2113

PASSEQ 2006-2008 (Passive Seismic Experiment in TESZ; WildePiórko et al. 2008) was the biggest passive seismic experiment carried out so far in the area of Central Europe (Poland, Germany, the Czech Republic and Lithuania). 196 seismic stations (including 49 broadband seismometers) worked simultaneously for over two years. During the experiment, multiple types of data recorders and seismometers were used, making the analysis more complex and time consuming. The dataset was unified and repaired to start the detection of local seismic events. Two different approaches for detection were applied for stations located in Poland. The first one used standard STA/LTA triggers (Carl Johnson’s STA/LTA algorithm) and grid search to classify and locate the events. The result was manually verified. The second approach used Real Time Recurrent Network (RTRN) detection (Wiszniowski et al. 2014). Both methods gave similar results, showing four previously unknown seismic events located in the Gulf of Gdańsk area, situated in the southern Baltic Sea. In this paper we discuss both detection methods with their pros and cons (accuracy, efficiency, manual work required, scalability). We also show details of all detected and previously unknown events in the discussed area.

Application of real time recurrent neural network for detection of small natural earthquakes in Poland

Wiszniowski J., Plesiewicz B.M., Trojanowski J.

Acta Geophysica

2014

Vol. 62, no. 3

469--485

This study is an application of a Real Time Recurrent Neural Network (RTRN) in the detection of small natural seismic events in Poland. Most of the events studied are from the Podhale region with a magnitude of 0.4 to 2.5. The population distribution of the region required that seismic signals be recorded using temporary stations deployed in populated areas. As a consequence, the high level of seismic noise that cannot be removed by filtration made it impossible to detect small events by STA/LTA based algorithms. The presence of high noise requires an alternate method of seismic detection capable of recognizing small seismic events. We applied the RTRN, which potentially can detect seismic signals in the frequency domain as well as in the phase arrival times. Data results of small local seismic events showed that the RTRN has the ability to correctly detect most of the events with fewer false detections than STA/LTA methods.