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Task 3: Irpinia Fault System WP3.1 Seismic noise analysis and Green Functions

Task 3: Irpinia Fault System WP3.1 Seismic noise analysis and Green Functions. Project – DPC S5 High-resolution multi-disciplinary monitoring of active fault test-site areas in Italy. Vassallo Maurizio, Gaetano Festa, Antonella Bobbio, Piero Brondi. 24 March 2010 –INGV Rome.

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Task 3: Irpinia Fault System WP3.1 Seismic noise analysis and Green Functions

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  1. Task 3: Irpinia Fault SystemWP3.1 Seismic noise analysis and Green Functions Project – DPC S5High-resolution multi-disciplinary monitoring of active faulttest-site areas in Italy Vassallo Maurizio, Gaetano Festa, Antonella Bobbio, Piero Brondi 24 March 2010 –INGV Rome

  2. Broad-band ISNetstations and AmbientseismicNoise Broad-band stations: RSF3 Rocca S. Felice (AV) TEO3 Teora (AV) RDM3 Ruvo del Monte(PZ) COL3 Colliano (SA) PGN3 Pignola (PZ) • ISNet dense seismic network: • A field laboratory to study the seismic source at small scales • An advanced infrastructure to test early warning procedures RSF3 RDM3 TEO3 COL3 PGN3 Ambient seismic noise acquired for 18 months at 5 stations of ISNet equipped with broad-band velocimeters (Trillium 40)

  3. Green functions from ambient seismic noise When the propagation medium satisfies the equipartition principle for a complete diffuse wavefield we can compute the Green function GAB(t) between two recording points A and B by the cross-correlation functions of the respectively seismic fields: Lobkis and Weaver (2001) Where and ФA and ФB are the seismic fields received by two sensors in A and B GAB(t) can be reitrieved by the causal part (t > 0) and anticausal part (t<0) of the cross correlation function CAB(t)

  4. Data collecting and processing Removemean; remove trend; band pass filterand cut tolength6 hours Continuous seismic data acquired for 18 months at 5 broad band stations of ISNet SpectralNormalization (spectralwhitening) time domain normalization (1-bit normalization) Phase 1: single station data preparation Computecross-correlation Compute the stackofcorrelations Phase 2: cross-correlation and stack

  5. Cross-correlations and stacks Distance between stations 27 km |One year of data (2009) | Distance between stations 40 km Higher stability of signal during the spring and summer Common low frequency signal • symmetric stack • energetic signal between -30 e 30 s • asymmetric stack • energetic signal between -70 e 70 s

  6. Processing toincreasesignalquality • Spectralwhitening • RecoursiveButterworthfilterbetween 0.1 Hz and 1 Hz • Stackoftraceswith high S/N Whitening Recoursivefilter small variations in the processed stacks processing not effective

  7. Dispersion analysis [0.1Hz-1Hz] PGN-TEO • Velocity models • Comparison between picked dispersion curves and dispersion curves computed using the 1D velocity models of the area • Surface wave analysis of stacks • Velocity analysis for identification of phases • Picking for dispersion curves reconstruction PGN-RSF Group velocity (km/s) Group velocity (m/s) Group velocity (km/s) Period (s) frequency (Hz) Period (s)

  8. Dispersion analysis [0.1Hz-1Hz] Dispersion computed only for far stations pairs , for near stations pairs low S/N in stack traces  problems for velocity analysis

  9. Dispersion analysis [10s-50s] Velocity analysis Time-dispersion analysis PGN-RSF Preliminary results RDM-RSF RDM-PGN 0.01 Hz 0.02 Hz 0.03 Hz 0.04 Hz 0.05 Hz 0.06 Hz 0.07 Hz 0.08 Hz 0.09 Hz Group velocity (km/s) 0.10 Hz Frequency All stacks filtered in 0.05Hz-0.08 Hz Surface wave propagation Group velocity (km/s) Period (s) Period (s) Distance

  10. Dispersion analysis [10s-50s] Preliminary results Clear surface waves identified on stack traces for all broad band stations

  11. Time Schedule Conclusions WP 3.1 activities 6 months 12 months 18 months 24 months Data collection and processing • Data collections and processing 100% completed • Computedcross-Correlations and Green functionsforallpairsofbroad band stations 100% completed • Velocity and dispersionanalysis 80-90% completed • Inversiondispersioncurvesforreconstructionofvelocitymodels 30-40% completed Green functions Dispersion analysis Velocity models

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