Automated microseismic event location using Master-Event Waveform Stacking.

Francesco Grigoli,Torsten Dahm,Simone Cesca,Enrico Priolo,Marius Kriegerowski,Lars Krieger,Josef Horalek,Sergio Gammaldi

doi:10.1038/srep25744

Abstract

Accurate and automated locations of microseismic events are desirable for many seismological and industrial applications. The analysis of microseismicity is particularly challenging because of weak seismic signals with low signal-to-noise ratio. Traditional location approaches rely on automated picking, based on individual seismograms, and make no use of the coherency information between signals at different stations. This strong limitation has been overcome by full-waveform location methods, which exploit the coherency of waveforms at different stations and improve the location robustness even in presence of noise. However, the performance of these methods strongly depend on the accuracy of the adopted velocity model, which is often quite rough; inaccurate models result in large location errors. We present an improved waveform stacking location method based on source-specific station corrections. Our method inherits the advantages of full-waveform location methods while strongly mitigating the dependency on the accuracy of the velocity model. With this approach the influence of an inaccurate velocity model on the results is restricted to the estimation of travel times solely within the seismogenic volume, but not for the entire source-receiver path. We finally successfully applied our new method to a realistic synthetic dataset as well as real data.

Highlights

The increasing number of microseismic monitoring networks for both seismological and industrial applications has led to an exponential growth of available microseismicity data in the last decade
The main systematic limitation of traditional event location techniques is that the automated event identification is most commonly performed individually on single seismograms, thereby making little or no use of the coherency information between waveforms recorded at different stations[3]
The most important condition which a master event must satisfy is that they need to be recorded with a reasonable signal-to-noise ratio at many stations, so that reliable station corrections can be obtained for most of the receivers

Summary

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To test the effectiveness of the new approach we applied the location process using a simplified velocity model, different from the one used to generate synthetic data. The effect of such approximation can be clearly seen, where the computed arrival times do not corresponds with those observed on waveforms. We apply both the standard and master-event WS location methods to the whole synthetic dataset. In this test we first calculated traveltimes using the simplified velocity model, we added the master-event time corrections, computed by using the equation 5.

Computationally expensive

Discussion and Conclusion

Author Contributions

Findings

Additional Information