3rd Annual AIM Workshop I October 10 – 12, 2012 | Smolenice Castle, Slovakia

1. Evidence for a low-permeability fluid trap in the Nový Kostel Seismic Zone from double-difference tomography 3rd Annual AIM Workshop I October 10 – 12, 2012 | Smolenice Castle, Slovakia Catrina Alexandrakis1,3, Marco Calò2, Fateh Bouchaala1 and Vaclav Vavryčuk1 1 Institute of Geophysics, CAS 2 EOST, University of Strasbourg 3 Institute of Geophysics and Geoinformatics, TU BAF

2. Acknowledgements • Data: • J. Horálek, A. Boušková and other members of the WEBNET group • Funding: • European Union Research Project AIM ‘Advanced Industrial microseismic Monitoring‘ - Marie Curie Actions

3. Outline • Introduction • Methodology • Double-Difference Tomography • Weighted Average Mean Analysis • Results and Interpretation • Conclusions

4. West Bohemia Seismic Zone

5. Swarm Triggers Smrčiny Pluton Geissler et al., 2005 Babuška and Plomerová, 2008

6. Outline • Introduction • Methodology • Double-Difference Tomography • Weighted Average Mean Analysis • Results and Interpretation • Conclusion and Future Work

7. Double-Difference TomographyTomoDD (Zhang and Thurber, 2003)

8. Double-Difference TomographyTomoDD (Zhang and Thurber, 2003)

9. Double-Difference Tomography • Advantages: • Relocates hypocenter locations • 3D Vp and Vs model of focal zone • Gives the Derivative Weight Sum (DWS) at each node • Disadvantages: • No error estimate for the velocity models • Starting model parameterization introduces bias and artifacts

10. Weighted Average Mean (WAM) Analysis (Calò et al., 2011) • Solution to parameterization artifacts • Calculates the Weighted Standard Deviation (WSTD) for the final model Steps • Define basic model parameters (e.g. Velocity model, node locations, hypocenters) • Perturb the basic parameters • Average models together using tomoDD’s DWS • Calculate the standard deviation using DWS as a weighting factor

11. Single Inversions Weighted Average Mean Model Weighted Standard Deviation

12. Input Data • Absolute P and S arrival times -- WEBNET • Differential Times (two events, single station) • Catalog differential arrival times • Cross-correlated arrival times • EventLocations -- WEBNET • 474 events • Magnitude 0 - 3.8 • Initial hypocenter locations range from 7 to 12 km depth • HypoDD - relocated events • 3D Velocity Model • Initial Vp model and Vp/Vs(1.70) -- Malek et al., 2000

13. A‘ A‘ A A HRED All Stations A‘ VAC HRC A A‘ A‘ A A

14. Outline • Introduction • Methodology • Double-Difference Tomography • Weighted Average Mean Analysis • Results and Interpretation • Conclusions

15. Checkerboard Test

16. WAM Model

17. WAM Model

18. Average Velocities Average Model Average Model Average Model Base Model Base Model Base Model

19. Wave speeds and fluids • P-Velocity • Expect a decrease in fluid-filled and fractured materials • Overpressured conditions may produce a velocity increase (Ito et al., 1979; Popp and Kern, 1993) • Vp/Vs ratio: • Sensitive to the presence of fluids • Increases in fractured and fluid-filled materials

20. Average Velocities Average Model Average Model Average Model Base Model Base Model Base Model

21. Weise et al., 2001

22. Weise et al., 2001

23. Outline • Introduction • Methodology • Double-Difference Tomography • Weighted Average Mean Analysis • Results and Interpretation • Conclusions

24. 3D velocity analysis reveals: • Layer of low Vp/Vs ratio values corresponds with the Smrčiny Pluton • May act as a low-permeability fluid trap • High Vp/Vs and P-velocities occur along the fault plane • Correspond with previously identified principal faults • High Vp/Vs values extend to the surface and may reflect fluid pathways

25. Future Work… North – South Principal Fault Across-Strike

27. Anomaly Restoration

28. Starting Model Tests Slow Model Base Model Fast Model