In this paper, the support vector machine model (SVM) was used to classify the earthquakes and blasting from the files recorded by an open pit copper mine seismic network. The database cleaning of false positive records (vibrations records not from blasting) must be supervised. This implies spending several hours of highly skilled engineers doing this routine task. Changing to an unsupervised classification method, based on AI, has shown an extremely high overall accuracy (as high as 0.97 over the validation dataset), allowing to perform the database filtering on real time while the vibration events are recorded by the seismographs.