Global grid of master events for waveform cross correlation: design and testing Kitov, I., D. Bobrov, and M. Rozhkov International Data Centre Preparatory Commission for the Comprehensive Nuclear-Test-Ban Treaty Organization Provisional Technical Secretariat Vienna International Centre P.O. Box 1200 A-1400 Vienna AUSTRIA ivan.kitov@ctbto.org International Data Centre Page 1
Acknowledgements The authors are grateful to the IDC and especially to all analysts reviewing XSEL and REB events. This presentation has been produced with the assistance of the European Union, EU Council Decision 2010/CFSP of 26 July 2010. Disclaimer The content of this presentation is the sole responsibility of the authors and can in no way be taken to reflect the views of the European Union and the CTBTO Preparatory Commission. International Data Centre Page 2
Comprehensive Nuclear-Test-Ban Treaty Background The Comprehensive Nuclear-Test-Ban Treaty (CTBT) obligates each State Party not to carry out any nuclear explosions, independently of their size and purpose. The Technical Secretariat (TS) of the Comprehensive Nuclear-Test-Ban Treaty Organization will carry out the verification of the CTBT. The International Data Centre (IDC) is an integral part of the (currently Provisional) TS. It receives, collects, processes, analyses, reports on and archives data from the International Monitoring System (IMS). The IDC is responsible for automatic and interactive processing of the IMS data and for standard IDC products. The IDC is also required by the Treaty to progressively enhance its technical capabilities. International Data Centre Page 3
Objectives To built a global grid of master events for waveform cross correlation To assess the performance of waveform cross correlation as a technique of seismic monitoring using the global grid of master events International Data Centre Page 4 25 October 2010
Outline 1. Motivation 2. Global seismic monitoring: IMS 3. Global seismicity: IDC view 4. Cross correlation at teleseismic distances 5. Actual and grand master events 6. Machine learning and classification 7. Synthetic master events 8. Underground nuclear explosions as master events 9. Global cross correlation grid. Design 10.Testing. February 12, 2013 International Data Centre Page 5 25 October 2010
Cross correlation as an IDC technique Motivation Regional studies demonstrate significant improvement in • detection, location, and magnitude estimation. At least an order of magnitude! Many IMS primary stations are arrays enhancing the capability • of cross correlation analysis For arrays, correlation distance depends on phase and its • slowness At teleseismic distances, high level of cross correlation is • observed for signals from events spaced by 100 km and even more Remote events may have similar signals • Small events can be considered as point sources • International Data Centre Page 6
IMS, seismic network The primary network includes many arrays Green circles – primary arrays Green triangles – primary 3-C stations Small green circles – auxiliary arrays International Data Centre Page 7
Global seismicity: the IDC view Waveform cross correlation relies on high quality master events REB events with zero depth: yellow – a neighbor closer than 50 km; red – no neighbor within 50 km Monitoring is global. How to populate the aseismic area with quality master event? International Data Centre Page 8
Waveform cross correlation 6 s 6 s Multichannel waveforms Master template Four frequency bands Adjusted template length Waveform quality check CC for individual channels Averaged CC trace Detection CC Detection: STA CC > CC tr LTA SNR_CC > SNR tr SNR=STA/LTA ≥ 3.0 Multichannel CC-detector better sees signals from slave events close to the master International Data Centre Page 9
Actual and grand masters: Sumatera 2012 6 1181 REB events between 4 April 11 and May 24 , 2012 Regular grid REB lat, deg Real masters 2 main shock 0 86 88 90 92 94 96 6 -2 long, deg 4 7 IMS array stations lat, deg • 2 16 master events: actual and grand • masters 2763 XSEL hypotheses 0 • 86 88 90 92 94 96 409 (~15%) randomly chosen XSEL • events were reviewed by analysts -2 long, deg 119 new REB events • International Data Centre Page 10
Machine learning: classification CMAR GERES ASAR MKAR SONM ZALV Tree Naive Nsta XSEL Bagger SVM Bayes 0 0 1066 1406 848 1 0 489 487 613 2 0 382 253 540 3 2080 324 208 452 WRA 4 514 347 256 198 5 129 115 113 80 6 31 31 31 24 7 9 9 9 8 2763 826 617 762 Total International Data Centre Page 11
Grand masters: Atlantic Ocean Cross correlation of signals from remote events 931 REB events; 3 array stations with SNR>3 International Data Centre Page 12
Grand masters: Atlantic Ocean Cross correlation coefficient for 931 events in seismic region 32 Events are ordered by latitude: north to south Matrix of cross correlation coefficients (color coded) Signals correlation does not dependent on the distance between events International Data Centre Page 13
Cross correlation: explosion signals Towards seismic monitoring of underground nuclear explosions • 100 waveforms • 25 underground nuclear explosions • 6.2 > mb > 4.5 • 2015 m > H > 150 m • 60 stations • 16º > ∆ > 100º International Data Centre Page 14
Cross correlation of explosion signals Synthetic seismograms: ∆ =30º, 45º, 60º, 90º H=0.1, 0.3, 0.6, 1.0, 2.0 km fc= 0.8 Hz to 4.8 Hz International Data Centre Page 15
Cross correlation of explosion signals Principal Component Analysis 10 best components for real and synthetic waveforms CCs for 100 real waveforms CCs for 100 real waveforms correlated with real PC correlated with synthetic PC Synthetics demonstrate excellent performance when used for waveforms cross correlation International Data Centre Page 16
Global Cross Correlation Grid Master: Ten primary seismic arrays at P-wave distances (6 to 96 degrees) International Data Centre Page 17
Global Cross Correlation Grid Segment R = 100 km International Data Centre Page 18
Global Cross Correlation Grid Testing, February 12, 2013 REB - 134 events Grid: 25000 nodes Group 1 = WRA, TORD, MKAR, ILAR, GERES, PDAR, CMAR, SONM, AKASG, BRTR, GEYT Group 2 = ASAR, ZALV, YKA, ARCES, TXAR, KSRS Group 3 = USRK, FINES, NVAR, NOA, MJAR Defining parameters: Templates: simplest 1D synthetic waveform for all arrays, theoretical time delays Detections: SNRmin = 0.5; SNR_CCmin=2.5; CCmin = 0.2; FKSTATmin = 2.5; AZRESmax= 20.0º; SLORESmax = 2.0 s/º; Events: dTorigin = 6s; NSTAmin= 3; AZGAPmax= 330º RESULTS: Total arrivals and hypotheses: 22,900,402 arrivals; 107,969 events; After conflict resolution: SNR_CC>2.5 SNR_CC>3.0 SNR_CC>3.5 SNR>2 XSEL 6,141 events 766 122 2351 REB Matched 92 90 77 101 DPRK 2013: time - 02:57:50.799 , d=24.92 km, OTres=0.1s; nsta=9: AKASG, BRTR, CMAR, GERES, GEYT, ILAR, MKAR, SONM, WRA International Data Centre Page 19
Global Cross Correlation Grid V0.1: All master templates are synthetics same at all stations, a version of f-k • analysis V0.2: Master templates are station/master specific synthetics in 1D velocity • model V0.3: Master templates are station/master/source (e.g. explosion) specific • synthetics calculated for 2D velocity structure (e.g. ak135+CRUST 2.0) V1.1: Real master templates are used where possible • V1.2: Grand master events are applied where possible • V2.0: The set of principal components are optimized where possible as • obtained by the PCA applied to the complete set of actual and historical data V3.0: Synthetic + real master templates based on principal components with • classification algorithms trained on actual data International Data Centre Page 20
Discussion IMS array stations make possible automatic processing based on • waveform cross correlation Cross correlation is a powerful technique allowing to reduce the • detection threshold and relative location accuracy by an order of magnitude, i.e. to find by 50% to 100% more (smaller) REB events Grand master and synthetic master events may reduce the • magnitude threshold of seismic monitoring by 0.4 units of magnitude The Global Cross Correaltion Grid is flexible (e.g. master density, • templates, number of stations, thresholds, etc.) to fulfill various tasks including effective monitoring of UNEs International Data Centre Page 21
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