CLUSTERING METHODS TO DIFFERENTIATE SEISMOLOGICAL DATA INTO EARTHQUAKE AND QUARRY BLAST

Data Mining

Earthquake mainly produces P- and S- wave at the point of occurrence. Mining site that mines the geological ma-terial from earth often makes the quarry blasts on the surface of earth to accelerate the mining process instead of drilling. This mining blast also causes the same wave as the earthquake. It is very difficult to differentiate between two of them as the characteristics of waves produced by these two events are similar. Sometimes mining sites are located near to residential area and discrimination of earthquake and quarry blast data is important to analyze the geological activities to create awareness. Data clustering is one of the effective techniques that differentiate the data into a number of clusters where a cluster contains similar data. In this paper , I calculated several parameters from wave form of an event. Clustering is good idea to differentiate them. Experimental result show that simple partitioning methods are not useful to differentiate seismic data into mining blast and earthquake. While FCM method gives 90-95% accurate result to identify cluster over noisy data.

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