Identification of Local Seismic Events Using the Mikhnevo Seismic Array

Abstract

A large number of events with sources in the immediate vicinity of an array are usually detected during seismological observations with seismic arrays. These events should be detected and correctly interpreted during processing of seismic array records in order to avoid clogging up the event catalog. This problem can be solved by classifying records of local events by genetic features and creating a databank with the most representative samples. The present paper considers local events recorded using a unique scientific setup, the Mikhnevo small aperture seismic array. Epicenters of local seismic events are located less than 5 km from the center of the array. Seismic responses of acoustic shock waves are also examined. Seismic events caused by anthropogenic sources are identified and classified using cluster, cross-correlation, and wavelet analysis. Events accompanied only by the arrival of surface waves, as well as events represented by body, surface, and acoustic waves, are identified. Shock wave events are classified as a separate category. A small group of supposedly natural weak events is also found. As a result, a databank of waveforms of local seismic events for the Mikhnevo seismic array is established. In the future, this will make it possible to automate their identification when investigating the seismicity of the East European Platform.