Presentation on theme: "Detection and Identification of Near Seismic Events by SeisComP3 limited by a sparse distributed Seismic Network Thomas Burghardt, Friedrich-Schiller-"— Presentation transcript:
Detection and Identification of Near Seismic Events by SeisComP3 limited by a sparse distributed Seismic Network Thomas Burghardt, Friedrich-Schiller- Universität Jena 17. Januar 2013 User Group Meeting Potsdam GFZ
Contents Configuration of the network Which signals are measured and which features the measurement has Examples for detected events The reported events Conclusion
How TSN and SX network is configured for SeisComP3?
The outer stations stabilize the localization of regional, Mediterranean and teleseismic events
The inner Stations are for the detection of the local events
Grid Search Algorithm Parameter
The outer domain for Grid Search is the ^default configuration of SC3
The inner Grid Search has a dense grid point domain of R=0,0625° ca Grid Points are investigated
Which signals the network measures?
Local blasts Local blasts or mining in Poland or northwest Germany Local blasts at Bavaria Teleseismic Events Mediterranean, Balcan Local earthquakes or mining events
The ambiguity of the Grid Search Algorithm and of LocSAT
Conclusion: There are different detection and location results at two computers with the same SC3 configuration. To my mind the cause depends on the not stabilized Grid Search Algorithm for near events and on the difficulties of LocSAT to localize teleseismic events with a regional velocity model.
Is the localization error less for a denser distribution of the stations in the network ?
Is answer seems to be no. Probably the influence of the S onsets and the unsufficient pick order provided by the Grid Search have a great portion to the false localization
Swabian Alp, Albstadt, Germany, Earthquake 02. Jan :55 EMSC: 48,24 ; 9,01 ML=2,3 S2: south. Nürnberg: 49,16 ; 10,91 P Onsets, BFO is absent, but the pick exists S1: S Onsets Near Cannes after relocation after put out of the far station: TRPA : 42,97 ; 6,03
S2: Grid Search takes the P Onsets
S1: Grid Search collects the S Onsets
S2: south Nürnberg, P-OnsetsS1: Near Cannes, S-Onsets
S2: vp=6,18 ; vpk=6,97km/s S1: vp=5,15 ; vpk=8,06 km/s In spite of S Onsets vpk: velocity of LocSAT after determination the hypocenter
Freiburg/Breisgau, Germany, Earthquake 01. Jan :48 EMSC: 48,37 ; 8,99 ML=2,1 S2: 48,30 ; 8,64 P Onsets S1: 48,30 ; 8,63 P Onsets
The Station BFO near of Epicenter stabilized the Location vp=6,89, vpk=7,38km/s, Res. of BFO: -0,1
Only some grid cells take part for location?
Plauen, Germany, Earthquake 28. Dec :55 SHM: 50,454 ; 12,225, ML=1,1,10,5km S2: 50,46 ; 12,34 MLv=1,1 S1: 50,45 ; 12,33 MLv=1,1 The best place for determination of hypocenter, because of the dense network
The nearest station PLN is too far from epicenter
The right location by manually picking and location
Regression line for manual Picks vp=6,64km/s S1: Automatic Regression line vp=4,32, vpk=6,37km/s The automatical onsets are spreading much
TT is bent, therefore the location shows to Thuringia and not to Poland, the regression line gives vp=32,9, vpk=14,9km/s
The determination of S velocity by regression line is problematical because of the wrong epicenter resulting by S Onset location
Detection Results of the reported events to the Office of Environment and Geology of Thuringia
The detectibility of the network in the swarm and in the tectonic region is sufficiently good. Down up to ML=1,5 with a location error up to 15 km the network give hints for manually revising. At the mining areas due to the sparse distribution of stations the Magnitude threshold is higher than 2.
Conclusion To my mind the Grid Search Algorithm has to be tuned to the sparse network to achieve a better location and less ambiguity. It will not become perfectly, because of the heterogeneity and the missing of coherence of signals in comparison to the teleseimic signals. With the absent regonizability of S onsets arises a big problem for localization. At this level of development in the local event detection with a sparse network, SC3 is an excellent tool for detection of the events, but a revision by a seismologist is absolutely necessary. The possibility to determine the spectra of the event with SC3 tool would be helpful.