Distributed Acoustic Sensing (DAS) data associated with a 6-month seismic monitoring of the Schäftlarnstraße geothermal site (Munich, Germany)

DOI

Data associated with Azzola J, Thiemann K, Gaucher E. Integration of Distributed Acoustic Sensing for real-time seismic monitoring of a geothermal field. Geothermal Energy – Science, Society and Technology. 2023.

  • mini-seed files include data subsets for both events studied in the article: DAS strain-rate data are sampled at 500Hz and provided unfiltered, with station names defined as the depth of the measuring point in well TH3 (datum is ground level).

  • python codes associated with the processing of the DAS strain-rate datasets on the Azure cloud work stations. The codes aim in particular at reading HDF5 files generated by the interrogator and transferred to the Azure data lake.

Corresponding author: Jerome Azzola, jerome.azzola@kit.edu

Identifier
DOI https://doi.org/10.35097/1430
Related Identifier IsIdenticalTo https://publikationen.bibliothek.kit.edu/1000157458
Metadata Access https://www.radar-service.eu/oai/OAIHandler?verb=GetRecord&metadataPrefix=datacite&identifier=10.35097/1430
Provenance
Creator Azzola, Jérôme ORCID logo; Thiemann, Katja; Gaucher, Emmanuel ORCID logo
Publisher Karlsruhe Institute of Technology
Contributor RADAR
Publication Year 2023
Rights Open Access; Creative Commons Attribution Non Commercial Share Alike 4.0 International; info:eu-repo/semantics/openAccess; https://creativecommons.org/licenses/by-nc-sa/4.0/legalcode
OpenAccess true
Representation
Resource Type Dataset
Format application/x-tar
Discipline Other