Digital drill core models: Structure-from-motion as a tool for the characterisation, orientation, and digital archiving of drill core samples

Structure-from-motion (SfM) photogrammetry enables the cost-effective digital characterisation of seismic- to sub-decimetre-scale geoscientific samples. The technique is commonly used for the characterisation of outcrops, fracture mapping, and increasingly so for the quantification of deformation du...

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Published in:Remote Sensing
Main Authors: Betlem P., Birchall T., Ogata K., Park J., Skurtveit E., Senger K.
Other Authors: Betlem, P., Birchall, T., Ogata, K., Park, J., Skurtveit, E., Senger, K.
Format: Article in Journal/Newspaper
Language:English
Published: 2020
Subjects:
Online Access:http://hdl.handle.net/11588/820155
https://doi.org/10.3390/rs12020330
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spelling ftunivnapoliiris:oai:www.iris.unina.it:11588/820155 2024-09-09T19:51:24+00:00 Digital drill core models: Structure-from-motion as a tool for the characterisation, orientation, and digital archiving of drill core samples Betlem P. Birchall T. Ogata K. Park J. Skurtveit E. Senger K. Betlem, P. Birchall, T. Ogata, K. Park, J. Skurtveit, E. Senger, K. 2020 http://hdl.handle.net/11588/820155 https://doi.org/10.3390/rs12020330 eng eng info:eu-repo/semantics/altIdentifier/wos/WOS:000515569800128 volume:12 issue:2 firstpage:330 journal:REMOTE SENSING http://hdl.handle.net/11588/820155 doi:10.3390/rs12020330 info:eu-repo/semantics/altIdentifier/scopus/2-s2.0-85081085275 Density Digital sample Drill core re-orientation Orthoprojection Sample reconstruction Volume info:eu-repo/semantics/article 2020 ftunivnapoliiris https://doi.org/10.3390/rs12020330 2024-06-17T15:19:34Z Structure-from-motion (SfM) photogrammetry enables the cost-effective digital characterisation of seismic- to sub-decimetre-scale geoscientific samples. The technique is commonly used for the characterisation of outcrops, fracture mapping, and increasingly so for the quantification of deformation during geotechnical stress tests. We here apply SfM photogrammetry using off-the-shelf components and software, to generate 25 digital drill core models of drill cores. The selected samples originate from the Longyearbyen CO2 Lab project's borehole DH4, covering the lowermost cap rock and uppermost reservoir sequences proposed for CO2 sequestration onshore Svalbard. We have come up with a procedure that enables the determination of bulk volumes and densities with precisions and accuracies similar to those of such conventional methods as the immersion in fluid method. We use 3D printed replicas to qualitatively assure the volumes, and show that, with a mean deviation (based on eight samples) of 0.059% compared to proven geotechnical methods, the photogrammetric output is found to be equivalent. We furthermore splice together broken and fragmented core pieces to reconstruct larger core intervals. We unwrap these to generate and characterise 2D orthographic projections of the core edge using analytical workflows developed for the structure-sedimentological characterisation of virtual outcrop models. Drill core orthoprojections can be treated as directly correlatable to optical borehole-wall imagery data, enabling a direct and cost-effective elucidation of in situ drill core orientation and depth, as long as any form of borehole imagery is available. Digital drill core models are thus complementary to existing physical and photographic sample archives, and we foresee that the presented workflow can be adopted for the digitisation and digital storage of other types of geological samples, including degradable and dangerous ice and sediment cores and samples. Article in Journal/Newspaper Longyearbyen Svalbard IRIS Università degli Studi di Napoli Federico II Longyearbyen Svalbard Remote Sensing 12 2 330
institution Open Polar
collection IRIS Università degli Studi di Napoli Federico II
op_collection_id ftunivnapoliiris
language English
topic Density
Digital sample
Drill core re-orientation
Orthoprojection
Sample reconstruction
Volume
spellingShingle Density
Digital sample
Drill core re-orientation
Orthoprojection
Sample reconstruction
Volume
Betlem P.
Birchall T.
Ogata K.
Park J.
Skurtveit E.
Senger K.
Digital drill core models: Structure-from-motion as a tool for the characterisation, orientation, and digital archiving of drill core samples
topic_facet Density
Digital sample
Drill core re-orientation
Orthoprojection
Sample reconstruction
Volume
description Structure-from-motion (SfM) photogrammetry enables the cost-effective digital characterisation of seismic- to sub-decimetre-scale geoscientific samples. The technique is commonly used for the characterisation of outcrops, fracture mapping, and increasingly so for the quantification of deformation during geotechnical stress tests. We here apply SfM photogrammetry using off-the-shelf components and software, to generate 25 digital drill core models of drill cores. The selected samples originate from the Longyearbyen CO2 Lab project's borehole DH4, covering the lowermost cap rock and uppermost reservoir sequences proposed for CO2 sequestration onshore Svalbard. We have come up with a procedure that enables the determination of bulk volumes and densities with precisions and accuracies similar to those of such conventional methods as the immersion in fluid method. We use 3D printed replicas to qualitatively assure the volumes, and show that, with a mean deviation (based on eight samples) of 0.059% compared to proven geotechnical methods, the photogrammetric output is found to be equivalent. We furthermore splice together broken and fragmented core pieces to reconstruct larger core intervals. We unwrap these to generate and characterise 2D orthographic projections of the core edge using analytical workflows developed for the structure-sedimentological characterisation of virtual outcrop models. Drill core orthoprojections can be treated as directly correlatable to optical borehole-wall imagery data, enabling a direct and cost-effective elucidation of in situ drill core orientation and depth, as long as any form of borehole imagery is available. Digital drill core models are thus complementary to existing physical and photographic sample archives, and we foresee that the presented workflow can be adopted for the digitisation and digital storage of other types of geological samples, including degradable and dangerous ice and sediment cores and samples.
author2 Betlem, P.
Birchall, T.
Ogata, K.
Park, J.
Skurtveit, E.
Senger, K.
format Article in Journal/Newspaper
author Betlem P.
Birchall T.
Ogata K.
Park J.
Skurtveit E.
Senger K.
author_facet Betlem P.
Birchall T.
Ogata K.
Park J.
Skurtveit E.
Senger K.
author_sort Betlem P.
title Digital drill core models: Structure-from-motion as a tool for the characterisation, orientation, and digital archiving of drill core samples
title_short Digital drill core models: Structure-from-motion as a tool for the characterisation, orientation, and digital archiving of drill core samples
title_full Digital drill core models: Structure-from-motion as a tool for the characterisation, orientation, and digital archiving of drill core samples
title_fullStr Digital drill core models: Structure-from-motion as a tool for the characterisation, orientation, and digital archiving of drill core samples
title_full_unstemmed Digital drill core models: Structure-from-motion as a tool for the characterisation, orientation, and digital archiving of drill core samples
title_sort digital drill core models: structure-from-motion as a tool for the characterisation, orientation, and digital archiving of drill core samples
publishDate 2020
url http://hdl.handle.net/11588/820155
https://doi.org/10.3390/rs12020330
geographic Longyearbyen
Svalbard
geographic_facet Longyearbyen
Svalbard
genre Longyearbyen
Svalbard
genre_facet Longyearbyen
Svalbard
op_relation info:eu-repo/semantics/altIdentifier/wos/WOS:000515569800128
volume:12
issue:2
firstpage:330
journal:REMOTE SENSING
http://hdl.handle.net/11588/820155
doi:10.3390/rs12020330
info:eu-repo/semantics/altIdentifier/scopus/2-s2.0-85081085275
op_doi https://doi.org/10.3390/rs12020330
container_title Remote Sensing
container_volume 12
container_issue 2
container_start_page 330
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