The 2014 Integrated Field Exercise Seismic Event Identification by Spectral Pattern Recognition and Combination of Array and Network Localization / Benjamin Sick, Nicolai Gestermann, Martin Hage, Thomas Blake, Peter Labak and Manfred Joswig.
The 2014 Integrated Field Exercise Seismic Event Identification by Spectral Pattern Recognition and Combination of Array and Network Localization / Benjamin Sick, Nicolai Gestermann, Martin Hage, Thomas Blake, Peter Labak and Manfred Joswig.
Due to the location of the the 2014 Integrated Field Exercise inspection area in Jordan on the Dead Sea Rift, an abundance of natural seismic events and quarry explosions had to be ruled out as possible aftershocks from an underground nuclear explosion for the OSI seismic aftershock monitoring system (SAMS). The extreme topography and restrictions led to a reduced number in deployed mini-arrays. Nevertheless SAMS successfully detected all scenario relevant events. This study shows the current SAMS manual detection and localization techniques and how they can be extended with automatic routines. The detection of local events with low signalto- noise ratios at very few stations (<3) with a duration of few seconds cannot be realized with detectors based solely on coincidences of amplitude variances (e.g. STA/LTA) or changes in the statistic distribution of ground velocities. An abundance of local noise sources triggers false detections continuously. The use of matched filters is limited due to the low-SNR and short epicentral distances. Instead a pattern recognition based on robust noise adapted spectrograms is used. The automatic localization is done through a combination of beam-forming, fk-analysis, phase-picking and a weighted 3D grid-search which takes the certainty of each information and the topography of the area into account.
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Open Access
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Electronic resource - Conference Proceedings
In
3.4: Developments in Seismology for On--Site Inspection: T3.4-O2 (2015)