Publication:
Analysis of Open Well Datasets

creativeworkseries.issn2079-3537
dc.contributor.authorMakienko, D. O.
dc.contributor.authorSafonov, I. V.
dc.contributor.authorСафонов, Илья Владимирович
dc.date.accessioned2024-12-28T15:28:12Z
dc.date.available2024-12-28T15:28:12Z
dc.date.issued2024
dc.description.abstractRecently, the number of studies devoted to the use of machine learning methods in geophysics has been increasing significantly. Examples of such investigations include the prediction of rock properties and separation of rock types according to quantitative characteristics. Annotated datasets are required to build and evaluate the quality of machine learning based models. This paper analyzes open labeled well datasets and related research. We consider data containing well logs, rock images, laboratory results, labeled zonation by lithotypes. Methods for visualizing well data are presented. We provide recommendations for oil and gas companies on the preferable format for making well data publicly available
dc.identifier.citationD.O. Makienko, I.V. Safonov. Analysis of Open Well Datasets (2024). Scientific Visualization 16.5: 164 - 178, DOI: 10.26583/sv.16.5.11
dc.identifier.doi10.26583/sv.16.5.11
dc.identifier.urihttps://openrepository.mephi.ru/handle/123456789/30292
dc.identifier.urihttp://sv-journal.org/2024-5/11/
dc.publisherНИЯУ МИФИ
dc.subjectMachine learning
dc.subjectOpen datasets
dc.subjectRock images
dc.subjectWell logs
dc.titleAnalysis of Open Well Datasets
dc.typeArticle
dspace.entity.typePublication
journal.titleНаучная визуализация
journalvolume.identifier.nameНаучная визуализация
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