Comparing the performance of stacking-based methods for microearthquake location: a case study from the Burträsk fault, northern Sweden

• Published in: Geophysical Journal International
• Main Authors: Beckel, Ruth A, Lund, Björn, Eggertsson, Gunnar A, Juhlin, Christopher
• Format: Article in Journal/Newspaper
• Language: English
• Published: Oxford University Press (OUP) 2021
• Subjects: Northern Sweden
• Online Access: http://dx.doi.org/10.1093/gji/ggab437; http://academic.oup.com/gji/advance-article-pdf/doi/10.1093/gji/ggab437/40830546/ggab437.pdf; https://academic.oup.com/gji/article-pdf/228/3/1918/41395362/ggab437.pdf

SUMMARY Traditional earthquake location relying on first arrival picking is challenging for microseismic events with low signal-to-noise ratio. Over the past years, alternative procedures have been explored based on the idea of migrating the energy of an earthquake back into its source position by stacking along theoretical traveltime curves. To avoid destructive interference of signals with opposite polarity, it is common to transform the input signals into positive time-series. Stacking-based source location has been successfully applied at various scales, but existing studies differ considerably in the choice of characteristic function, the amount of pre-processing and the phases used in the analysis. We use a data set of 62 natural microearthquakes recorded on a 2-D seismic array of 145 vertical geophones across the glacially triggered Burträsk fault to compare the performance of five commonly used characteristic functions: the noise filtered seismograms and the semblance, the envelope, the short-term average/long-term average ratio and the kurtosis gradient of the seismograms. We obtain the best results for a combined P- and S-wave location using a polarity-sensitive characteristic function, that is the filtered seismograms or the semblance. In contrast, the absolute functions often fail to align the signals properly, yielding biased location estimates. Moreover, we observe that the success of the procedure is very sensitive to noise suppression and signal shaping prior to stacking. Our study demonstrates the usefulness of including lower quality S-wave data to improve the location estimates. Furthermore, our results illustrate the benefits of retaining the phase information for location accuracy and noise suppression. To ensure optimal location results, we recommend carefully pre-processing the data and test different characteristic functions for each new data set. Despite the suboptimal array geometry, we obtain good locations for most events within ∼30–40 km of the survey and the locations are consistent ...