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.
%0 Journal Article
%1 plenkers_etal:2012
%A Plenkers, Katrin
%A Ritter, Joachim R. R.
%A Schindler, Marion
%D 2012
%I Springer Netherlands
%J Journal of Seismology
%K geophysics seismology
%P 1--23
%R 10.1007/s10950-012-9284-9
%T Low signal-to-noise event detection based on waveform stacking and
cross-correlation: application to a stimulation experiment
%U http://dx.doi.org/10.1007/s10950-012-9284-9
%X 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.
@article{plenkers_etal:2012,
abstract = {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.},
added-at = {2012-09-01T13:08:21.000+0200},
author = {Plenkers, Katrin and Ritter, Joachim R. R. and Schindler, Marion},
biburl = {https://www.bibsonomy.org/bibtex/255c825b6c8bb5fe8e96f601bd778f309/nilsma},
day = 28,
doi = {10.1007/s10950-012-9284-9},
interhash = {07ab1068f3939c3a31a722e1feede76a},
intrahash = {55c825b6c8bb5fe8e96f601bd778f309},
issn = {1383-4649},
journal = {Journal of Seismology},
keywords = {geophysics seismology},
month = feb,
pages = {1--23},
publisher = {Springer Netherlands},
timestamp = {2021-02-09T13:24:56.000+0100},
title = {Low signal-to-noise event detection based on waveform stacking and
cross-correlation: application to a stimulation experiment},
url = {http://dx.doi.org/10.1007/s10950-012-9284-9},
year = 2012
}