Please use this identifier to cite or link to this item: http://hdl.handle.net/2122/1866
AuthorsKvaerna, T.* 
Ringdal, F.* 
TitleIntelligent post processing of seismic events
Issue DateJun-1994
Series/Report no.37/3
URIhttp://hdl.handle.net/2122/1866
Keywordsseismology
signal processing
onset time
event location
Subject Classification05. General::05.09. Miscellaneous::05.09.99. General or miscellaneous 
AbstractThe Intelligent Monitoring Systern (IMS) currently provides for joint processing of data from six arrays located in Northern and Central Europe. From experience with analyst review of events automatically defined by the IMS, we bave realized that the quality of the automatic event locations can be significantly improved if the event intervals are reprocessed with signal processing pararneters tuned to phases from events in the given region. The tuned processing parameters are obtained from off line analysis of events located in the region of interest. The primary goal of such intelligent post processing is to provide event definitions of a quality that minimizes the need for subsequent manual analysis. The first step in this post processing is to subdivide the arca to be monitored in order to identify sites of interest. Clearly, calibration will be the easiest and potential savings in manpower are the largest for areas of high, recurring seismicity. We bave identified 8 mining sites in Fennoscandia/NW Russia and noted that 65.6% of the events of ML > 2.0 in this region can be associated with one of these sites. This result is based on 1 year and a half of data. The second step is to refine the phase arrival and azimuth estimates using frequency filters and processing parameters that are tuned to the initial event location provided by the IMS. In this study, we have analyzed a set of 52 mining explosions from the Khibiny Massif mining area in the Kola peninsula of Russia. Very accurate locations of these events bave been provided by the seismologists from the Kola Regional Seismology Centre. Using an autoregressive likelihood technique we have been able to estimate onset times to an accuracy (standard deviation) of about 0.05 s for P phases and 0.15 0.20 s for S phases. Using fixed frequency bands, azimuth can be estimated to an accuracy (one standard deviation) of 0.9 degrees for the ARCESS array and 3 4 degrees for the small array recently established near Apatity on the Kola peninsula. The third step in the post processing is a relocation of the event, using refined arrivai times and recomputed azimuths from broad band flk analysis. By introducing region specific travel time corrections, a median error of 1.4 km from the reported location has been obtained. This should be compared to the median error of 10.8 km for the automatie IMS processing for these events. This improvement in location accuracy clearly demonstrates the usefulness of the intelligent post processing approach.
Appears in Collections:Annals of Geophysics

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