DWT-based methodology for detection of seismic precursors on electric field signals in Mexico

Abstract

This paper presents an analysis of atmospheric electric field signals which were taken on an important seismic activity period from 2012 to 2015 to study its relationship with seismic events. For this purpose, several measurements were acquired every second by using a triaxial electric field monitoring system. Furthermore, the discrete wavelet transform (DWT) was applied to electric field signals with seismic events of magnitudes greater than Mw > 5.5, which occurred in Mexico with different focal mechanisms. The analysed epochs consist of 24 h of observations for a data-set corresponding to 55 different earthquakes (EQs). The time series were processed 12 h before and 12 h after each seismic event. The proposed methodology proves to be an efficient tool to detect signals with relations between electric field and seismic activity. The methodology presented herein shows important anomalies on different time instants according to the focal mechanism. Finally, a statistical postprocessing algorithm was performed in order to quantify the data dispersion as a measure of seismic activity. It is found that the variance increases before, during, and after the seismic event about the coefficients D1 to D7 obtained using the DWT.