Dataset.
[Dataset] Global physics-based database of injection-induced seismicity
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/284662
Digital.CSIC. Repositorio Institucional del CSIC
- Kivi, Iman Rahimzadeh
- Boyet, Auregan
- Wu, Haiqing
- Walter, Linus
- Hanson-Hedgecock, Sara
- Parisio, Francesco
- Vilarrasa, Víctor
The database and its accompanying files are as follows:
GEoREST_database_Readme (.txt): provides an overview of the database goals and content, sharing/accessing information and methodologies used to develop the database.
GEoREST_induced_seismicity_database_v20.11.2022 (.xlsx): database in a single Microsoft Excel spreadsheet.
GEoREST_induced_seismicity_database_v20.11.2022 (.csv): database in .csv format, considered as a standard machine-readable format for direct implementation of data in model developments.
GEoREST_database_bibliography_v20.11.2022 (.docx): provides the full list of references used to collect data included in the database.
GEoREST_database_dictionary_v20.11.2022 (.docx): presents unified, self-explanatory acronyms together with concise definitions for all variables included in the database., We present a comprehensive, publicly accessible database of injection-induced seismicity. The database is sourced from a comprehensive review of more than 500 published documents and contains information for 158 cases of induced earthquakes from around the world. The collected earthquakes are associated with a variety of geoenergy applications, which can be broadly categorized into geologic gas storage, geothermal energy development, shale gas fracturing, research projects and wastewater disposal. The compilation comprises more than 70 variables, including general project information, host rock properties, in situ site characteristics, fault attributes, operational parameters, and recorded seismicity data (both overall seismic activities and the largest event sequence). The developed database opens up opportunities for improved understanding of the causative mechanisms of injection-induced seismicity and advancing on seismic hazard forecasting and mitigation., This research is funded by
(1) the European Research Council (ERC) under ‎the ‎‎European Union’s Horizon ‎‎2020
Research and Innovation Program through the ‎Starting Grant ‎‎GEoREST (www.georest.eu) under Grant ‎agreement No. 801809,
(2) MCIN/AEI/‎‎10.13039/501100011033 and the ‎European ‎Union ‎NextGenerationEU/PRTR
through the international collaboration project EASYGEOCARBON ‎‎‎‎(www.easygeocarbon.com)
under Grant ‎agreement No. PCI2021-122077-2B,
(3) the European Union’s Horizon 2020 Research and Innovation ‎Programme
through the Marie Sklodowska-Curie Action ARMISTICE (www.armistice-energy.eu) under grant â
€Žagreement No. 882733.
(4) the Secretariat for Universities and ‎Research of the Ministry of Business and Knowledge of the
Government of Catalonia (AGAUR) and the European ‎Social Fund (FI-2019),
(5) MCIN/AEI/ ‎‎10.13039/501100011033‎ through the Excellence Servero Ochoa (IDAEA-CSIC) under Grant agreement No. ‎CEX2018-000794-S, Peer reviewed
Proyecto:
EC/H2020/801809
DOI: http://hdl.handle.net/10261/284662, https://doi.org/10.20350/digitalCSIC/14813
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/284662
HANDLE: http://hdl.handle.net/10261/284662, https://doi.org/10.20350/digitalCSIC/14813
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/284662
Ver en: http://hdl.handle.net/10261/284662, https://doi.org/10.20350/digitalCSIC/14813
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/284662
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1 Versiones
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Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/284662
Dataset. 2022
[DATASET] GLOBAL PHYSICS-BASED DATABASE OF INJECTION-INDUCED SEISMICITY
Digital.CSIC. Repositorio Institucional del CSIC
- Kivi, Iman Rahimzadeh
- Boyet, Auregan
- Wu, Haiqing
- Walter, Linus
- Hanson-Hedgecock, Sara
- Parisio, Francesco
- Vilarrasa, Víctor
The database and its accompanying files are as follows:
GEoREST_database_Readme (.txt): provides an overview of the database goals and content, sharing/accessing information and methodologies used to develop the database.
GEoREST_induced_seismicity_database_v20.11.2022 (.xlsx): database in a single Microsoft Excel spreadsheet.
GEoREST_induced_seismicity_database_v20.11.2022 (.csv): database in .csv format, considered as a standard machine-readable format for direct implementation of data in model developments.
GEoREST_database_bibliography_v20.11.2022 (.docx): provides the full list of references used to collect data included in the database.
GEoREST_database_dictionary_v20.11.2022 (.docx): presents unified, self-explanatory acronyms together with concise definitions for all variables included in the database., We present a comprehensive, publicly accessible database of injection-induced seismicity. The database is sourced from a comprehensive review of more than 500 published documents and contains information for 158 cases of induced earthquakes from around the world. The collected earthquakes are associated with a variety of geoenergy applications, which can be broadly categorized into geologic gas storage, geothermal energy development, shale gas fracturing, research projects and wastewater disposal. The compilation comprises more than 70 variables, including general project information, host rock properties, in situ site characteristics, fault attributes, operational parameters, and recorded seismicity data (both overall seismic activities and the largest event sequence). The developed database opens up opportunities for improved understanding of the causative mechanisms of injection-induced seismicity and advancing on seismic hazard forecasting and mitigation., This research is funded by
(1) the European Research Council (ERC) under ‎the ‎‎European Union’s Horizon ‎‎2020
Research and Innovation Program through the ‎Starting Grant ‎‎GEoREST (www.georest.eu) under Grant ‎agreement No. 801809,
(2) MCIN/AEI/‎‎10.13039/501100011033 and the ‎European ‎Union ‎NextGenerationEU/PRTR
through the international collaboration project EASYGEOCARBON ‎‎‎‎(www.easygeocarbon.com)
under Grant ‎agreement No. PCI2021-122077-2B,
(3) the European Union’s Horizon 2020 Research and Innovation ‎Programme
through the Marie Sklodowska-Curie Action ARMISTICE (www.armistice-energy.eu) under grant â
€Žagreement No. 882733.
(4) the Secretariat for Universities and ‎Research of the Ministry of Business and Knowledge of the
Government of Catalonia (AGAUR) and the European ‎Social Fund (FI-2019),
(5) MCIN/AEI/ ‎‎10.13039/501100011033‎ through the Excellence Servero Ochoa (IDAEA-CSIC) under Grant agreement No. ‎CEX2018-000794-S, Peer reviewed
Proyecto: EC/H2020/801809
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