Deep Neural Networks for Earthquake Detection and Source Region Estimation in North Central Venezuela
Ruben Tous 1 , Leonardo Alvarado 2,4 , Beatriz Otero 1 , Leonel Cruz 1 and Otilio Rojas 2,3 1 Universitat Politècnica de Catalunya (UPC). Barcelona, Spain. 2 Universidad Central de Venezuela, Facultad de Ciencias, Caracas, Venezuela. 3 Barcelona Supercomputing Center (BSC). Barcelona, Spain. 4 Venezuelan Foundation for Seismological Research, FUNVISIS, Caracas, Venezuela. Publicado en: Bulletin of the Seismological Society of America, 110(5), 2519-2529. Abstract Reliable earthquake detection algorithms are necessary to properly analyze and catalog the continuously growing seismic records. We report the results of applying a deep convolutional neural network, called UPC-UCV, over single-station three-channel signal windows for P-wave earthquake detection and source region estimation in north central Venezuela. The analysis is performed on a new dataset of hand-picked arrivals of P-waves from local events, named CARABOBO, built and made public for reproducibility...