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METHOD OF AUTOMATED DETECTION OF SEISMICALLY ACTIVE ZONES WITHIN THE MINE FIELD BY THE DATA OF INDUCED SEISMICITY
Abstract
The authors propose a method for automated processing of seismic data obtained in high-stress rock masses structured as hierarchy of blocks with a view to detecting seismically active zones and seismic event clusters within a mine field. The processing algorithm is developed based on the statistical theory of classification and cluster analysis. Suitable for zoning of seismic data, FOREL family algorithms include algorithms based on the idea of incorporating objects in the zones of their highest concentration into a cluster. The algorithm displaces a sphere with a radius R in 3D space until having a stable metric center of gravity of seismic events embraced in the sphere. The algorithm is implemented in Java. On the whole, this method produces the wanted results of automated setting a domain of scanning of seismic data from catalogs of seismic events though it has some insignificant shortcomings. One of the shortcomings is, first of all, the inability to pre-set the number of clusters. Furthermore, the boundaries of the cluster may lack the pronounced features of an пїЅinterface.пїЅ Nevertheless, the implemented clustering provides understanding of zones of seismic activity and represents them in a convenient, visual and space-effective form. The stage of clustering governs the further calculations of stresses and strains in the rock mass areas under control in order to develop a rockburst hazard criterion based on dynamic-and-kinematic characteristics of induced seismic events
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References9
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