FORCE 2020 Well well log and lithofacies dataset for machine learning competition ...
This well log dataset from 118 wells in the Norwegian Sea that has been used in the FORCE 2020 machine learning competition with seismic and wells to predict the lithofacies using machine learning models. The well logs have been slightly cleaned up and partially despiked. The lithofacies and litholo...
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Online Access: | https://dx.doi.org/10.5281/zenodo.4351156 https://zenodo.org/record/4351156 |
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ftdatacite:10.5281/zenodo.4351156 2024-01-28T10:08:13+01:00 FORCE 2020 Well well log and lithofacies dataset for machine learning competition ... Bormann, Peter Aursand, Peder Dilib, Fahad Manral, Surrender Dischington, Peter 2020 https://dx.doi.org/10.5281/zenodo.4351156 https://zenodo.org/record/4351156 en eng Zenodo https://dx.doi.org/10.5281/zenodo.4351155 Open Access Creative Commons Attribution 4.0 International https://creativecommons.org/licenses/by/4.0/legalcode cc-by-4.0 info:eu-repo/semantics/openAccess , lithofacies , petrophysical, well logs, North SEA, FORCE, 2020, Machine Learnig competition, GR, NEU, DENS,, well, logs, petrophysics Dataset dataset 2020 ftdatacite https://doi.org/10.5281/zenodo.435115610.5281/zenodo.4351155 2024-01-04T22:40:10Z This well log dataset from 118 wells in the Norwegian Sea that has been used in the FORCE 2020 machine learning competition with seismic and wells to predict the lithofacies using machine learning models. The well logs have been slightly cleaned up and partially despiked. The lithofacies and lithology interpretation has been hand crafted using skilled geoscientists (Thanks to Explocrowd for excellent work). For citation in addition to the DOI please also refer to the github repository where the documentation and trained models reside https://github.com/bolgebrygg/Force-2020-Machine-Learning-competition The original well log data comes form the Norwegian government and is provided by a NOLD 2.0 license ... Dataset Norwegian Sea DataCite Metadata Store (German National Library of Science and Technology) Norwegian Sea |
institution |
Open Polar |
collection |
DataCite Metadata Store (German National Library of Science and Technology) |
op_collection_id |
ftdatacite |
language |
English |
topic |
, lithofacies , petrophysical, well logs, North SEA, FORCE, 2020, Machine Learnig competition, GR, NEU, DENS,, well, logs, petrophysics |
spellingShingle |
, lithofacies , petrophysical, well logs, North SEA, FORCE, 2020, Machine Learnig competition, GR, NEU, DENS,, well, logs, petrophysics Bormann, Peter Aursand, Peder Dilib, Fahad Manral, Surrender Dischington, Peter FORCE 2020 Well well log and lithofacies dataset for machine learning competition ... |
topic_facet |
, lithofacies , petrophysical, well logs, North SEA, FORCE, 2020, Machine Learnig competition, GR, NEU, DENS,, well, logs, petrophysics |
description |
This well log dataset from 118 wells in the Norwegian Sea that has been used in the FORCE 2020 machine learning competition with seismic and wells to predict the lithofacies using machine learning models. The well logs have been slightly cleaned up and partially despiked. The lithofacies and lithology interpretation has been hand crafted using skilled geoscientists (Thanks to Explocrowd for excellent work). For citation in addition to the DOI please also refer to the github repository where the documentation and trained models reside https://github.com/bolgebrygg/Force-2020-Machine-Learning-competition The original well log data comes form the Norwegian government and is provided by a NOLD 2.0 license ... |
format |
Dataset |
author |
Bormann, Peter Aursand, Peder Dilib, Fahad Manral, Surrender Dischington, Peter |
author_facet |
Bormann, Peter Aursand, Peder Dilib, Fahad Manral, Surrender Dischington, Peter |
author_sort |
Bormann, Peter |
title |
FORCE 2020 Well well log and lithofacies dataset for machine learning competition ... |
title_short |
FORCE 2020 Well well log and lithofacies dataset for machine learning competition ... |
title_full |
FORCE 2020 Well well log and lithofacies dataset for machine learning competition ... |
title_fullStr |
FORCE 2020 Well well log and lithofacies dataset for machine learning competition ... |
title_full_unstemmed |
FORCE 2020 Well well log and lithofacies dataset for machine learning competition ... |
title_sort |
force 2020 well well log and lithofacies dataset for machine learning competition ... |
publisher |
Zenodo |
publishDate |
2020 |
url |
https://dx.doi.org/10.5281/zenodo.4351156 https://zenodo.org/record/4351156 |
geographic |
Norwegian Sea |
geographic_facet |
Norwegian Sea |
genre |
Norwegian Sea |
genre_facet |
Norwegian Sea |
op_relation |
https://dx.doi.org/10.5281/zenodo.4351155 |
op_rights |
Open Access Creative Commons Attribution 4.0 International https://creativecommons.org/licenses/by/4.0/legalcode cc-by-4.0 info:eu-repo/semantics/openAccess |
op_doi |
https://doi.org/10.5281/zenodo.435115610.5281/zenodo.4351155 |
_version_ |
1789336725381709824 |