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Low signal-to-noise event detection based on waveform stacking and cross-correlation: application to a stimulation experiment

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Journal of Seismology, (28.02.2012)
DOI: 10.1007/s10950-012-9284-9

Аннотация

We study the microseismicity (ML < 2) in the region of Landau, SW Germany. Here, due to thick sediments (\~3 km) and high cultural seismic noise, the signal-to-noise ratio is in general very low for microearthquakes. To gain new insights into the occurrence of very small seismic events, we apply a three-step detection approach and are able to identify 207 microseismic events (-1 < ML < \~1) with signal-to-noise ratios smaller than 3. Recordings from a temporary broadband network are used with station distances of approximately 10 km. First, we apply a short-term to long-term average detection algorithm for data reduction. The detection algorithm is affected severely by transient noise signals. Therefore, the most promising detections, selected by coinciding triggers and high-amplitude measures, are reviewed manually. Thirteen seismic events are identified in this way. Finally, we conduct a cross-correlation analysis. As master template, we use the stacked waveforms of five manually detected seismic events with a repeating waveform. This search reveals additional 194 events with a cross-correlation coefficient exceeding 0.65 which ensures a stable identification. Our analysis shows that the repeating events occurred during the stimulation of a geothermal reservoir within a source region of only about 0.5 km3. Natural background seismicity exceeding our detection level of ML \~ 0.7 is not found in the region of Landau by our analysis.

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