Focal mechanisms of micro-earthquakes in the Little Carpathians -

1. AIMsecond annual meeting September 29-30, 2011 Prague Progseis, Ltd. Focal mechanisms of micro-earthquakes in the Little Carpathians - time-frequency identification of problematic input data for Isola MT inversions MiriamKristekováLuciaFojtíková Geophysical Institute SAS, Bratislava, Slovakia in cooperation with industrial partner: JurajSekereš DagmarSekerešová Progseis, Ltd., Trnava, Slovakia

2. Outline Motivation of our work: Why we pay attention to ISOLA method? Need to investigate sensitivity of ISOLA method to the choice of parameters of computation Possibilities how to verifywhether proper parameters are usedor whether obtained results are reliable Use of TFA for identification of problematic input data (indication of necessity to improve velocity model usedor at least to omit problematic data) Conlusions

3. Motivation For estimation of focal mechanisms: different methods – different advantages/limitations e.g. FOCMEC(focal mechanisms, inversion from polarities of P-waves)[Snoke 2003] needs data from many stations with precise location and optimal coverage of focal sphere AMT (moment tensor, inversion from amplitudes of P-waves)[Vavryčuk 2009] needs data from several (at least 7-8) stations with suitable configuration

4. Another possibility ISOLA (moment tensor, waveform inversion) [Sokos & Zahradnik 2009]allows to obtain solution for a small number of stations (theoretically for the only one station)* + it could be really helpful when dense local network is not available- method could be more sensitive to the data and parameters of computation

5. In general,in computations of focal mechanismsthere are uncertaintiesof resultscaused by input data(quality, configuration) or by parameters of computations(e.g. velocity model – for real complex geological structures) Byprocessing of large statistical datasets of events and by using different methods it is possible to eliminate (at least partly) influence of these uncertatiesand to compensate lack of our knowledge and to obtain more reliable solutions(e.g. [Fojtikova et al 2010])

6. However, what to do in cases when large statistical dataset is not available,and/orit is not possible to use several independent methods? Limited number of stations available and their unsuitable configuration quite common situation when analyzing weak local events in regions with moderate seismicity Then using ISOLA method could be helpful

7. By using data from only few stations, ISOLA method could be more sensitive to the quality of data and to the choice of parameters of computationmoreover, In some cases this could be the only one applicable methodwithout possibility to verify obtained result with other method it is important andnecessary (especially for such a cases) to investigate sensitivity of ISOLA to the choice of parameters(e.g. freq.range for inversion, velocity model used, etc.) and to be careful when verifyingwhether the obtained result is reliable

8. In order to make inversion less sensitive to unknown tiny details of the velocity model used ISOLA uses S- and surface waves mainly (lower frequency part of seismograms) ISOLA has usually been used for regional events, not for microearthquakes (exception was [Fojtikova et al 2010]) => different frequency range is analyzed Therefore, the first natural question was: what freq. range is suitable for waveform inversion of weak local events?

9. We investigated and selected suitable frequency ranges (containing useful signal) for ISOLA inversions of weak local events using time-frequency analysis and this work was already presented at previous AIM meeting

10. As it was shown in previous presentations of our teamat this meeting ISOLA method is sensitive to the changes in the velocity model used => sufficient knowledge of velocity model is neccessary Therefore important issue when considering possibilities of the use of the ISOLA method is the following one: How to identify cases when our knowledge of the model is insufficient and when computation could lead to the biased results?

11. V04 Q05 Q12 U01 S03 V19 Q16 W05 S02 V07 V09 Y01 V05 V06 X02 X01 V08 V03 Q15 R03 W01 T01 V17 Q13 X03 V15 X04 V14 Event V14 MKNET Micro-events in Little Carpathians Mts. area (2001-2009, Ml>1)

12. Event V14 was a special case in previous analyses It seemed that the two different solutions of focal mechanisms are equally probable FOCMEC AMT Solutions from ISOLA varied between these two typesand for the fixed velocity model they strongly depended on the selection of stationsused for computation level of agreement between real and synthetic seismogram was similar for these different solutions, so this criterion did not help to select more reliable solution...

13. This strong dependence on the selection of stations was probably consequence of not sufficient knowledge of the velocity model in the area of interest(Dobra Voda source zone has complicated local geological structure)or by some artifacts in data Therefore we started with more detailed analysis of input data (seismograms) from individual stations looking for some anomaly We performed time-frequency analysisusing continuous wavelet transform (CWT).

14. Z N E SMO, D = 2.67 km 19.0e-10 30.0e-10 60.0e-10 BUK, D = 5.26 km 1.9e-10 5.6e-10 9.5.0e-10 4.0e-10 4.6e-10 45.0e-10 KAT, D = 7.22 km DVO, D = 11.23 km 1.1e-10 1.8e-10 1.4e-10

15. FOCMEC AMT SMO, BUK, KAT SMO, BUK, KAT Aditionaly, we have noticed that the cases when ISOLA results resembled FOCMEC resultswere cases with low number of stations including KAT SMO, BUK, KAT Ecomp.

16. Thank you for your attention