Downloads provided by UsageCounts
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
, lithofacies , petrophysical, well logs, North SEA, FORCE, 2020, Machine Learnig competition, GR, NEU, DENS,, well, logs, petrophysics
, lithofacies , petrophysical, well logs, North SEA, FORCE, 2020, Machine Learnig competition, GR, NEU, DENS,, well, logs, petrophysics
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 3 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
| views | 2K | |
| downloads | 889 |

Views provided by UsageCounts
Downloads provided by UsageCounts