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Moment tensor inversion at Pyhasalmi ore mine: accuracy test using explosions

Moment tensor inversion at Pyhasalmi ore mine: accuracy test using explosions. Daniela Kühn (NORSAR) V. Vavrycuk (Academy of Sciences of the CR) AIM 2 nd annual meeting, 29-30 Sept 2011, Prague, Czech Republic. Introduction. Waveform modelling. Moment tensor inversion. Summary.

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Moment tensor inversion at Pyhasalmi ore mine: accuracy test using explosions

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  1. Moment tensor inversion at Pyhasalmi ore mine:accuracy test using explosions Daniela Kühn (NORSAR) V. Vavrycuk (Academy of Sciences of the CR) AIM 2nd annual meeting, 29-30 Sept 2011, Prague, Czech Republic

  2. Introduction Waveform modelling Moment tensor inversion Summary Pyhäsalmi ore mine, Finland • microseismic monitoring: • since January 2003 • safety of the underground personnel • optimisation of mining process • network: • 12 1-C geophones • + 6 3-C geophones (ISS) • 3-D geometry • sampling rate: < 3000 Hz • events: • 1500 events /months (including blasting) • -2 < Mw < 1.5 owned by Inmet Mining Co.

  3. Introduction Waveform modelling Moment tensor inversion Summary InconsistentpolaritiesofP-wave first onset • Moment tensor inversion: • homogeneous velocity model (as for locations) • amplitude inversion

  4. Introduction Waveform modelling Moment tensor inversion Summary Waveform modelling

  5. Introduction Waveform modelling Moment tensor inversion Summary Complexityofvelocitymodel

  6. Introduction Waveform modelling Moment tensor inversion Summary Waveform modelling: 2D section • E3D: viscoelastic 3-D FD code (Larsen and Schultz, 1995) • strong interaction with mining cavities: reflection, scattering, conversion • healing of wavefronts 620 m

  7. Introduction Waveform modelling Moment tensor inversion Summary Waveformmodelling synthetic seismograms • - complex waveforms • strong coda • complex secondary arrivals • scattering effects stronger on amplitudes than travel times, since size of heterogeneities (cavities, access tunnels) same order or smaller than wavelengths • arrival times computed by Eikonal solver still fit (wavefronts heal quickly after passing a cavitiy) observed seismograms

  8. Introduction Waveform modelling Moment tensor inversion Summary Comparison1-D/3-D Imaginary network!

  9. Introduction Waveform modelling Moment tensor inversion Summary Comparison1-D/3-D

  10. Introduction Waveform modelling Moment tensor inversion Summary Influence of proximity to cavity Real mine network!

  11. Introduction Waveform modelling Moment tensor inversion Summary Sourcedepth → raypath

  12. Introduction Waveform modelling Moment tensor inversion Summary Ray path → onsetpolarity

  13. Introduction Waveform modelling Moment tensor inversion Summary Moment tensor inversion

  14. Amplitude picking Introduction Waveform modelling Moment tensor inversion Summary direct wave scattered wave direct wave scattered wave first maximum amplitude = amplitude of the direct wave ? energy diffracted around cavity first maximum amplitude is not always the amplitude of the direct wave

  15. Introduction Waveform modelling Moment tensor inversion Summary Amplitude vs. waveforminversion • Amplitude inversion: • homogeneous model of the medium • Green’s functions calculated using ray theory • inversion of P-wave amplitudes (20-30 amplitudes) • frequencies: 250-500 Hz • cannot take into account distortion of rays on focal sphere • misinterpretation of amplitudes: which one is the direct wave? • Waveform inversion: • 3-D heterogeneous model of the medium • Green’s functions calculated using FD code • inversion of full waveforms (15-20 waveforms) • frequencies (at the moment): 25-100 Hz • inversion is performed in frequency domain • in principle same inversion algorithm as for amplitude inversion, but run repeatedly for every frequency band (0.5 Hz steps)

  16. Introduction Waveform modelling Moment tensor inversion Summary Selected explosions: relocation expl 1 expl 1 expl 3 expl 5 expl 3 expl 5 expl 1 expl 3 Explosions (coords in m): 1) x=8306E y=2312N z=-1238 → 26 m shift 3) x=8218E y=2192N z=-1352 → 68 m shift 5) x=8214E y=2168N z=-1356 → 59 m shift expl 5

  17. Examples: good fit

  18. Examples: amplitude misfit

  19. Examples: phase misfit

  20. Introduction Waveform modelling Moment tensor inversion Summary Inversion results explosion 1 explosion 3 explosion 5

  21. Length of time windows ISO percentage ISO percentage ISO percentage GF duration [10 ms] GF duration [10 ms] GF duration [10 ms] explosion 1 explosion 3 explosion 5 Data duration [10 ms] Data duration [10 ms] Data duration [10 ms] nearly all solutions have high isotropic percentage best solutions near diagonal (length of GF time window = length of data time window) best solutions P –wave + S-wave onset

  22. Introduction Waveform modelling Moment tensor inversion Summary Explosion 1 Amplitude inversion Waveform inversion DC = 7% CLVD = -14% ISO = 79%

  23. Introduction Waveform modelling Moment tensor inversion Summary Summary: seismicity in mines structural model in mines is very complex large and abrupt changes in velocity at cavities model varies in time earthquake source is complex (single forces, non-DC components) small changes in source position lead to large changes in ray propagation, rays can be strongly curved radiated wave field is complex (reflected, converted, scattered waves, head waves)

  24. Introduction Waveform modelling Moment tensor inversion Summary Summary: waveform inversion • In general: • complex Green’s functions can be calculated by 3-D FD codes (accurate model needed!); • sensitive to time shifts due to mislocation or due to inaccurate velocity model • frequency band of inverted waves can be easily controlled => stability analysis • In particular: • good network configuration => focal sphere nicely covered • inversion algorithm: • optimal with same window length for Green’s functions and data • optimal with simultaneous inversion of P- and S-wave, but excluding S-wave coda • yields high isotropic percentage, higher than amplitude inversion, almost • independently of window length • promising, but computationally demanding (especially the computation of Green’s • functions with sufficiently small grid point distances) • will be performed for selected events, not whole database

  25. Thank you for your attention! http://commons.wikimedia.org/wiki/File:Preikestolen_Norge.jpg

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