Automatic Detection and Location of Regional Earthquakes: Toward Improving the Earthquake Catalogue in the Northern Canadian Cordillera

Stephane Gaston Faubert, University of Ottawa, Ottawa, ON, Canada and Pascal Audet, University of Ottawa, Earth Sciences, Ottawa, ON, Canada

Contact First Author: Stephane Gaston Faubert; sfaub020@uottawa.ca

Abstract ID#: 33946

 

English Abstract:
The northern Canadian Cordillera is one of the most seismically active regions in Canada. Unfortunately, the earthquake catalogue is only complete down to magnitudes M>3 due to the sparse distribution of seismograph stations in the Yukon and Northwest Territories, thus hampering our ability to fully characterize the structures and sources of stress responsible for the deformation. Following the installation of the Yukon-Northwest Seismograph Network, we are now in a position to significantly improve the earthquake catalogue, with the ultimate goal of understanding the tectonic processes that are actively deforming the northern Canadian Cordillera. In this work we attempt to implement an automated detection and picking technique to facilitate the detection and localization of earthquakes in the region. The automated detection technique first employs a short-time over long-time average (STA/LTA) trigger to initially detect seismic events across the network. From these triggers, we locate earthquakes based on a four-step process. First, for each event, we determine initial P-wave arrival times through the simultaneous use of an STA/LTA picker, a kurtosis-based picker, and a signal to noise ratio (SNR) based picker. Second, we use these picks to calculate an initial earthquake location and obtain predicted body-wave arrival times. We then use a short window around the predicted body-wave arrival times to refine our initial P-wave picks and to obtain S-wave picks using the same picking algorithms. Finally, we re-calculate the earthquake location and determine its magnitude. The final earthquake parameters are then catalogued in a database for future analysis.