Focal mechanisms of micro-earthquakes in the Little Carpathians

-

time-frequency identification of problematic input data

for Isola MT inversions

AIM second annual meeting

September 29-30, 2011 Prague

Miriam Kristeková Lucia Fojtíková

Geophysical Institute SAS, Bratislava, Slovakia

in cooperation with

industrial partner:

Juraj Sekereš Dagmar Sekerešová

Progseis, Ltd., Trnava, Slovakia

Progseis, Ltd.

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 verify

whether proper parameters are used

orwhether obtained results are reliable

Use of TFA for identification of problematic input data (indication of necessity to improve velocity model used

or at least to omit problematic data)

Conlusions

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

Motivation

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

In general, in computations of focal mechanisms

there are uncertainties of results

caused

by input data (quality, configuration) or

by parameters of computations

(e.g. velocity model – for real complex geological structures)

By processing of large statistical datasets of events

and

by using different methods

it is possible to eliminate (at least partly) influence of these uncertaties

and to compensate lack of our knowledge

and

to obtain more reliable solutions

(e.g. [Fojtikova et al 2010])

However, what to do in cases

when large statistical dataset is not available,

and/or

it 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

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 computation

moreover,

In some cases this could be the only one applicable method

without possibility to verify obtained result with other method

it is important and necessary

(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 verifying

whether the obtained result is reliable

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?

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

As it was shown in previous presentations of our team

at 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?

MKNET

Micro-events in

Little Carpathians Mts. area(2001-2009, Ml>1)

S03

V08

V14

V05

V04

W05

W01

X04

Y01

X01

V06

Q05

Q13

Q15

Q16

R03

S02

T01

U01

V15

V17

X02

X03

Q12

V19

V03

V07

V09

Event V14

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 types

and for the fixed velocity model

they strongly depended on the selection of stations

used 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...

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 analysis

using continuous wavelet transform (CWT).

DVO, D = 11.23 km

Z N E SMO, D = 2.67 km

KAT, D = 7.22 km

BUK, D = 5.26 km

60.0e-10

45.0e-10

1.4e-10

9.5.0e-10

19.0e-10 30.0e-10

4.6e-10

1.9e-10 5.6e-10

1.8e-10

4.0e-10

1.1e-10

SMO, BUK,

KAT Ecomp.

SMO, BUK, KAT

FOCMEC AMT

SMO, BUK, KAT

Aditionaly, we have noticed that

the cases when ISOLA results

resembled FOCMEC results

were cases with low number of

stations including KAT

Thank you for your attention