THE WAVEFORM SIMILARITY APPROACH TO IDENTIFY DEPENDENT EVENTS IN INSTRUMENTAL SEISMIC CATALOGUES

Abstract

In this paper, waveform similarity analysis is adapted and implemented in a declustering procedure to identify foreshocks and aftershocks, to obtain instrumental catalogues that are cleaned of dependent events and to perform an independent check of the results of traditional declustering techniques.Unlike other traditional declustering methods (i.e. windowing techniques), the application of cross-correlation analysis allows definition of groups of dependent events (multiplets) characterized by similar location, fault mechanism and propagation pattern. In this way the chain of intervening related events is led by the seismogenetic features of earthquakes. Furthermore, a time-selection criterion is used to define time-independent seismic episodes eventually joined (on the basis of waveform similarity) into a single multiplet. The results, obtained applying our procedure to a test data set, show that the declustered catalogue is drawn by the Poisson distribution with a degree of confidence higher than using the Gardner and Knopoff method. The declustered catalogues, applying these two approaches, are similar with respect to the frequency–magnitude distribution and the number of earthquakes.Nevertheless, the application of our approach leads to declustered catalogues properly related to the seismotectonic background and the reology of the investigated area and the success of the procedure is ensured by the independence of the results on estimated location errors of the events collected in the raw catalogue.