Title

1. Three-dimensional velocity models and probabilistic earthquake location Title Stephan Husen Institute of Geophysics, ETH Zurich, Switzerland, husen@sed.ethz.ch with contributions from Anthony Lomax Scientific Software, Mouans-Sartoux, France, anthony@alomax.net Edi Kissling Institute of Geophysics, ETH Zurich, Switzerland

2. Introduction Linearized earthquake location linearized earthquake location Traditional earthquake location • linearized methods (HYPO71, HYPOELLIPSE, HYPOINVERSE,..) 3D Velocity Model • 1-D velocity models (plus station delays) Probabilistic Earthquake Location • error bars or error ellipses (linear) Location Examples • efficient …. but linearized methods and 1-D velocity models are only approximations! Conclusions

3. Introduction what do we need improvement How can we improve the situation? 3D Velocity Model • 3-D velocity models (Local earthquake tomography, controlled-source experiment) Probabilistic Earthquake Location • Non-linear earthquake location (NonLinLoc) Location Examples Conclusions

4. Introduction Example mine blast relocation mine blast Mine Blast - True location is known 3D Velocity Model Probabilistic Earthquake Location True location True location Location Examples Non-linear solution (3D) Linear solution (1D) Linear solution (1D) Conclusions

5. Introduction Data quality 3D Velocity Model earthquake data in Switzerland Probabilistic Earthquake Location Location Examples 729 earthquakes with 10,044 P-observations Conclusions only highest quality data (impulsive onsets)

6. Introduction Moho topography 3D Velocity Model Moho topography Probabilistic Earthquake Location Location Examples Waldhauser et al., 1998 3-D Moho topography beneath Switzerland as determined by controlled-source seismology data Conclusions

7. Introduction Min. 1D model 3D Velocity Model Subset of 200 earthquakes min. 1D model Simultaneous inversion for 1D velocity models, hypocenter locations, and station delays Probabilistic Earthquake Location Location Examples Software VELEST Initial models Final models Conclusions

8. Introduction CSS model 3D Velocity Model controlled-source data Probabilistic Earthquake Location Location Examples Conclusions 3-D P-wave velocity model determined by controlled-source seismology (CSS) data

9. Introduction Final model 3D Velocity Model final (combined) model Probabilistic Earthquake Location Location Examples Lower crust / Moho is controlled by CSS data crust is controlled by earthquake data Conclusions Final 3D P-wave velocity model determined by earthquake data and controlled-source data

10. Introduction NonLinLoc Tarantola and Valette (1982) 3D Velocity Model Posteriori Probability Density Function (x)(PDF): (x) = K(x)*exp[-1/2misfitL2(x)] Probabilistic Earthquake Location relies on known a priori information (x) on model parameters and on observations. software NonLinLoc PDF is computed using global sampling techniques - grid search or Oct-Tree importance sampling. Location Examples PDF gives complete location uncertainties. Conclusions Software NonLinLoc: www.alomax.net/nlloc

11. Introduction Global sampling methods Grid-Search 3D Velocity Model Probabilistic Earthquake Location Grid-Search Location Examples complete mapping Conclusions inefficient and slow

12. Introduction Global sampling methods Grid-Search Oct-Tree sampling 3D Velocity Model Probabilistic Earthquake Location Grid-Search vs. Oct-Tree sampling Location Examples complete mapping importance sampling Conclusions inefficient and slow efficient and fast

13. Introduction Location uncertainties Grid-search Oct-Tree importance sampling 3D Velocity Model Probabilistic Earthquake Location solution and location uncertainties Location Examples confidence contours scatter clouds Conclusions maximum likelihood hypocenter location 68% confidence ellipsoid

14. Introduction Example 1 1987 05 08 09:59 46.146 N 8.614 E 4.1km 3D Velocity Model Nobs: 8 RMS: 0.04 s GAP: 193 Dmin: 1.9 km Probabilistic Earthquake Location Difference: dx: 1.0 km dy: 5.2 km dz: 0.1 km Location Examples non-linear uncertainties SED error: ERRH: 1.9 km ERRZ: 2.6 km Non-linear(3D) Conclusions Linear(1D)

15. Introduction Example 2 1993 04 15 13:57 46.921 N 9.607 E -0.9 km 3D Velocity Model Nobs: 8 RMS: 0.14 s GAP: 164 Dmin: 16.9 km Probabilistic Earthquake Location Difference: dx: 2.5 km dy: 3.0 km dz: 15.7 km Location Examples no control on focal depth Non-linear(3D) SED error: ERRH: 2.2 km ERRZ: 2.6 km Linear(1D) Conclusions

16. Introduction Conclusions Conclusions 3D Velocity Model • combination of local earthquake data and controlled-source data provides reliable 3-D velocity models Probabilistic Earthquake Location • probabilistic earthquake location combined with global sampling algorithms is efficient and reliable • location uncertainties obtained by probabilistic earthquake location prove to be much more reliable, important for planetary data sets with few instruments Location Examples Conclusions

17. Introduction Conclusions Outlook • application and tuning of existing geophysical methods to planetary data sets (real and synthetic) considering their peculiarities, i.e. small number of receivers 3D Velocity Model Probabilistic Earthquake Location Location Examples Conclusions