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Comprehensive geological dataset describing a crystalline rock mass for hydraulic stimulation experiments

High-resolution 3D geological models are crucial for underground development projects and corresponding numerical simulations with applications in e.g., tunneling, hydrocarbon exploration, geothermal exploitation and mining. Most geological models are based on sparse geological data sampled pointwis...

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Autores principales: Krietsch, Hannes, Doetsch, Joseph, Dutler, Nathan, Jalali, Mohammadreza, Gischig, Valentin, Loew, Simon, Amann, Florian
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6259022/
https://www.ncbi.nlm.nih.gov/pubmed/30480661
http://dx.doi.org/10.1038/sdata.2018.269
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author Krietsch, Hannes
Doetsch, Joseph
Dutler, Nathan
Jalali, Mohammadreza
Gischig, Valentin
Loew, Simon
Amann, Florian
author_facet Krietsch, Hannes
Doetsch, Joseph
Dutler, Nathan
Jalali, Mohammadreza
Gischig, Valentin
Loew, Simon
Amann, Florian
author_sort Krietsch, Hannes
collection PubMed
description High-resolution 3D geological models are crucial for underground development projects and corresponding numerical simulations with applications in e.g., tunneling, hydrocarbon exploration, geothermal exploitation and mining. Most geological models are based on sparse geological data sampled pointwise or along lines (e.g., boreholes), leading to oversimplified model geometries. In the framework of a hydraulic stimulation experiment in crystalline rock at the Grimsel Test Site, we collected geological data in 15 boreholes using a variety of methods to characterize a decameter-scale rock volume. The experiment aims to identify and understand relevant thermo-hydro-mechanical-seismic coupled rock mass responses during high-pressure fluid injections. Prior to fluid injections, we characterized the rock mass using geological, hydraulic and geophysical prospecting. The combination of methods allowed for compilation of a deterministic 3D geological analog that includes five shear zones, fracture density information and fracture locations. The model may serve as a decameter-scale analog of crystalline basement rocks, which are often targeted for enhanced geothermal systems. In this contribution, we summarize the geological data and the resulting geological interpretation.
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spelling pubmed-62590222018-11-29 Comprehensive geological dataset describing a crystalline rock mass for hydraulic stimulation experiments Krietsch, Hannes Doetsch, Joseph Dutler, Nathan Jalali, Mohammadreza Gischig, Valentin Loew, Simon Amann, Florian Sci Data Data Descriptor High-resolution 3D geological models are crucial for underground development projects and corresponding numerical simulations with applications in e.g., tunneling, hydrocarbon exploration, geothermal exploitation and mining. Most geological models are based on sparse geological data sampled pointwise or along lines (e.g., boreholes), leading to oversimplified model geometries. In the framework of a hydraulic stimulation experiment in crystalline rock at the Grimsel Test Site, we collected geological data in 15 boreholes using a variety of methods to characterize a decameter-scale rock volume. The experiment aims to identify and understand relevant thermo-hydro-mechanical-seismic coupled rock mass responses during high-pressure fluid injections. Prior to fluid injections, we characterized the rock mass using geological, hydraulic and geophysical prospecting. The combination of methods allowed for compilation of a deterministic 3D geological analog that includes five shear zones, fracture density information and fracture locations. The model may serve as a decameter-scale analog of crystalline basement rocks, which are often targeted for enhanced geothermal systems. In this contribution, we summarize the geological data and the resulting geological interpretation. Nature Publishing Group 2018-11-27 /pmc/articles/PMC6259022/ /pubmed/30480661 http://dx.doi.org/10.1038/sdata.2018.269 Text en Copyright © 2018, The Author(s) http://creativecommons.org/licenses/by/4.0/ Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ The Creative Commons Public Domain Dedication waiver http://creativecommons.org/publicdomain/zero/1.0/ applies to the metadata files made available in this article.
spellingShingle Data Descriptor
Krietsch, Hannes
Doetsch, Joseph
Dutler, Nathan
Jalali, Mohammadreza
Gischig, Valentin
Loew, Simon
Amann, Florian
Comprehensive geological dataset describing a crystalline rock mass for hydraulic stimulation experiments
title Comprehensive geological dataset describing a crystalline rock mass for hydraulic stimulation experiments
title_full Comprehensive geological dataset describing a crystalline rock mass for hydraulic stimulation experiments
title_fullStr Comprehensive geological dataset describing a crystalline rock mass for hydraulic stimulation experiments
title_full_unstemmed Comprehensive geological dataset describing a crystalline rock mass for hydraulic stimulation experiments
title_short Comprehensive geological dataset describing a crystalline rock mass for hydraulic stimulation experiments
title_sort comprehensive geological dataset describing a crystalline rock mass for hydraulic stimulation experiments
topic Data Descriptor
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6259022/
https://www.ncbi.nlm.nih.gov/pubmed/30480661
http://dx.doi.org/10.1038/sdata.2018.269
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