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Laboratory-scale hydraulic fracturing dataset for benchmarking of enhanced geothermal system simulation tools
Successful design of enhanced geothermal systems (EGSs) requires accurate numerical simulation of hydraulic stimulation processes in the subsurface. To ensure correct prediction, the underlying model assumptions and constitutive relationships of simulators need to be verified against experimental da...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7343873/ https://www.ncbi.nlm.nih.gov/pubmed/32641714 http://dx.doi.org/10.1038/s41597-020-0564-x |
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author | Deb, Paromita Düber, Stephan Guarnieri Calo’ Carducci, Carlo Clauser, Christoph |
author_facet | Deb, Paromita Düber, Stephan Guarnieri Calo’ Carducci, Carlo Clauser, Christoph |
author_sort | Deb, Paromita |
collection | PubMed |
description | Successful design of enhanced geothermal systems (EGSs) requires accurate numerical simulation of hydraulic stimulation processes in the subsurface. To ensure correct prediction, the underlying model assumptions and constitutive relationships of simulators need to be verified against experimental datasets. With the aim of generating laboratory-scale benchmark datasets, a state-of-the-art testing facility was developed, allowing for experiments under controlled conditions. Samples of size 30 cm × 30 cm × 45 cm were subjected to confining stresses while high-pressure fluid was injected into the sample through a pre-drilled borehole, where a saw-cut notch was used to initiate a penny-shaped fracture. Fracture growth and propagation was monitored by measuring pressure data and acoustic emissions detected using 32 seismic sensors. Subsequently, samples were split along the fracture plane to outline the created fracture marked by a red-dyed injection fluid. Finally, a 2D fracture contour was generated using photogrammetry. Presented datasets, accessible via a public repository, include experiments on granite and marble samples. They can be used for verifying and improving numerical codes for field stimulation designs. |
format | Online Article Text |
id | pubmed-7343873 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-73438732020-07-13 Laboratory-scale hydraulic fracturing dataset for benchmarking of enhanced geothermal system simulation tools Deb, Paromita Düber, Stephan Guarnieri Calo’ Carducci, Carlo Clauser, Christoph Sci Data Data Descriptor Successful design of enhanced geothermal systems (EGSs) requires accurate numerical simulation of hydraulic stimulation processes in the subsurface. To ensure correct prediction, the underlying model assumptions and constitutive relationships of simulators need to be verified against experimental datasets. With the aim of generating laboratory-scale benchmark datasets, a state-of-the-art testing facility was developed, allowing for experiments under controlled conditions. Samples of size 30 cm × 30 cm × 45 cm were subjected to confining stresses while high-pressure fluid was injected into the sample through a pre-drilled borehole, where a saw-cut notch was used to initiate a penny-shaped fracture. Fracture growth and propagation was monitored by measuring pressure data and acoustic emissions detected using 32 seismic sensors. Subsequently, samples were split along the fracture plane to outline the created fracture marked by a red-dyed injection fluid. Finally, a 2D fracture contour was generated using photogrammetry. Presented datasets, accessible via a public repository, include experiments on granite and marble samples. They can be used for verifying and improving numerical codes for field stimulation designs. Nature Publishing Group UK 2020-07-08 /pmc/articles/PMC7343873/ /pubmed/32641714 http://dx.doi.org/10.1038/s41597-020-0564-x Text en © The Author(s) 2020 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 associated with this article. |
spellingShingle | Data Descriptor Deb, Paromita Düber, Stephan Guarnieri Calo’ Carducci, Carlo Clauser, Christoph Laboratory-scale hydraulic fracturing dataset for benchmarking of enhanced geothermal system simulation tools |
title | Laboratory-scale hydraulic fracturing dataset for benchmarking of enhanced geothermal system simulation tools |
title_full | Laboratory-scale hydraulic fracturing dataset for benchmarking of enhanced geothermal system simulation tools |
title_fullStr | Laboratory-scale hydraulic fracturing dataset for benchmarking of enhanced geothermal system simulation tools |
title_full_unstemmed | Laboratory-scale hydraulic fracturing dataset for benchmarking of enhanced geothermal system simulation tools |
title_short | Laboratory-scale hydraulic fracturing dataset for benchmarking of enhanced geothermal system simulation tools |
title_sort | laboratory-scale hydraulic fracturing dataset for benchmarking of enhanced geothermal system simulation tools |
topic | Data Descriptor |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7343873/ https://www.ncbi.nlm.nih.gov/pubmed/32641714 http://dx.doi.org/10.1038/s41597-020-0564-x |
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