An Attention-Based Hypocenter Estimator for Earthquake Localization

Abstract

The accuracy of earthquake localization is of great importance for earthquake monitoring systems. Traditionally, numerical optimization methods are used to estimate the hypocenter location and the origin time of an earthquake in an iterative manner. The traditional methods usually depend on certain theoretical models, but the geological conditions in practice can be quite different from the presumed models. In this study, an attention-based hypocenter estimation (AHE) model was proposed to locate the hypocenter and origin time of the earthquake. Rather than using the raw waveforms, the phase picking times and the positions of the triggered stations are used as the input. The attention mechanism is adapted to reveal the correlations among the input sequence. An experimental model was trained using data collected from earthquakes in Taiwan in 2016 and 2017 and tested on data in 2018. From the results, AHE is capable of locating the hypocenter with a high degree of accuracy in terms of the distance, depth, and origin time of earthquakes.