A novel algorithm for seismic events multiplets search

Abstract

A common practice of seismology is to analyze earthquake occurrence in terms of events catalogues, with the aim to either find useful correlations between internal mechanisms under study and their outcome in the spatial/temporal series of the events or, more directly, to assess some statistical rules from observations. With this approach, catalogues are often searched for some recognizable patterns or behaviors: in this work we present a software tool created to reveal a particular kind of events sequences.

The idea follows from the concept of multiplets, a well known events pattern often found in seismic series. A multiplet is defined as a sequence of events, all near in space and time and exhibiting similar magnitudes. The amount of multiplets in seismic series is related, as it is for other clustering mechanisms, to underlying correlations in the physics of the events.

The software, built from scratch, scans seismic catalogues in search of events clustered as “multiplets”: this is done through the thorough application of comparison tests whose parameters thresholds are both user defined and semi-automated. The tool is however more “general” in the sense that by varying values of the filtering parameters it can reveal other kind of patterns too.

While we think that this tool can be thought as a general purpose space–time series analyzer, we have found it particularly useful when applied to the results of a seismic simulator with the purpose of assessing their adherence with the observed seismicity. It can be used as a sort of metric to quantify the simulation predictions effectiveness in terms of presence of similar multiplets distributions in simulated vs. real catalogues.

The software has been entirely developed in the Wolfram Language (Mathematica), a commercial powerful environment for scientific calculus and results report, but the main computational routine has been also ported to python for open-source, copyleft usage.