EGU2020-16199, updated on 10 Jan 2024
https://doi.org/10.5194/egusphere-egu2020-16199
EGU General Assembly 2020
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.

Contribution of continuous waveform processing to induced seismicity realtime monitoring during geothermal stimulation at Geldinganes, Iceland.

Francesco Grigoli1, Sebastian Heimann2, Claus Milkereit2, Stefan Mikulla2, Nima Nooshiri3, Malte Metz2, Gesa Petersen2, Simone Cesca2, Vala Hjörleifsdóttir4, Rögnvaldur Magnússon5, Ragnheidur St. Ásgeirsdóttir5, Hannes Hofmann2, Marco Broccardo1, Dimitrios Karvounis1, Arnaud Mignan1, Kristjan Augustsson5, Stefan Audunn Stefansson5, Gunter Zimmermann2, Torsten Dahm2, and Stefan Wiemer1
Francesco Grigoli et al.
  • 1ETH-Zurich, Institute of Geophysics, Swiss Seismological Service, Zurich, Switzerland (francesco.grigoli@sed.ethz.ch)
  • 2Helmholtz Centre Potsdam GFZ German Research Centre for Geosciences, Potsdam, Germany
  • 3Dublin Institute of Advanced Studies, Dublin, Ireland
  • 4Reykjavik Energy, Reykjavik, Iceland
  • 5ISOR, Reykjavik, Iceland

At Geldinganes Island, Reykjavik, Iceland a hydraulic stimulation was recently conducted to enhance the productivity of an existing hydrothermal well. An experimental cyclic soft stimulation concept was applied. Seismic risk was assessed with an appropriate monitoring network which was set up and operated before, during, and for some time after the stimulation activities. An advanced traffic light system was developed and operated for the first time in this setup.

A crucial element in such traffic light systems is the real-time monitoring of background and induced seismicity. During the experiment, real-time seismograms from the monitoring network were streamed over the internet to three different institutions (ISOR, ETHZ and GFZ), where they were analysed independently, with different combinations and setups of automatic, semi-automatic and manual methods. Both, classic pick based approaches and modern full-waveform methods were applied. Locations, magnitudes, and centroid moment tensor solutions were determined.

Many things can go wrong in real-time or near-real-time processing of seismic data. Sensor failures, transmission failures, timing issues, processing hardware failures, computational limitations, software bugs and human error, just to name a few. In a temporary network the challenges are additionally salted by the need to validate sensor responses, orientations, gain factors and site conditions in a short time frame between station setup and beginning of the experiment. Furthermore, tuning of advanced analysis methods can be difficult without example events at hand.

In this contribution, we would like to share our lessons learned in near-real-time processing of data from a heterogeneous temporary seismic network. 

How to cite: Grigoli, F., Heimann, S., Milkereit, C., Mikulla, S., Nooshiri, N., Metz, M., Petersen, G., Cesca, S., Hjörleifsdóttir, V., Magnússon, R., Ásgeirsdóttir, R. St., Hofmann, H., Broccardo, M., Karvounis, D., Mignan, A., Augustsson, K., Stefansson, S. A., Zimmermann, G., Dahm, T., and Wiemer, S.: Contribution of continuous waveform processing to induced seismicity realtime monitoring during geothermal stimulation at Geldinganes, Iceland. , EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-16199, https://doi.org/10.5194/egusphere-egu2020-16199, 2020.