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DGGV-E-Publikationen

Title: Seismic Monitoring of DeepStor: Using low-cost sensors for ambient noise correlation methods and Citizen Science

Authors:
Johannes Käufl, Eva Schill, Thomas Kohl

Institutions:
Karlsruhe Institute of Technology, Germany

Event: GeoKarlsruhe 2021

Date: 2021

DOI: 10.48380/dggv-gt5z-t820

Summary:
DeepStor is an experimental facility with the goal to investigate High Temperature Aquifer Thermal Energy Storage (HT-ATES) systems at KIT Campus North. The operational seismic monitoring of DeepStor includes a network of five broadband and one borehole seismometer. In addition, we plan to install a scientific monitoring network with low-cost seismometers (such as the Raspberry Shake and the Quakesaver Hidra) to test innovative monitoring methods and for a Citizen Science project.

Ambient noise tomography and coda wave interferometry are being used increasingly to image and monitor geothermal reservoirs. Especially in locations with a high anthropogenic noise level, such as the Oberrheingraben, these methods could potentially provide valuable insights in the evolution of the storage acquifer during injection/production cycles. Our monitoring approach focuses on the use of a larger number of these low-cost sensors instead of fewer and more expensive broadband instruments (Large-N approach). With the broadband network and established monitoring methods as a benchmark, DeepStor provides the ideal testing ground to explore the benefits of a dense network of low-cost sensors.

The Citizen Science project will build on the successful Gecko project, which involved the public in the conceptualization of geothermal energy usage. A major conclusion from the Gecko workshops was the importance of transparent monitoring processes for the acceptance of geothermal energy usage. Consequently, we plan to involve the communities around KIT Campus North in the monitoring of DeepStor by distributing sensors for radon and seismicity. To ensure trust in the monitoring process, we will follow open data practice and investigate options to make the data easily accessible and understandable.



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