Application of neural network technology to calculate well logging porosity on the example of UK2-7 formations in the Yelizarovsky deflection (Western Siberia)

dc.contributor.author	Lisovskaya E.A.
dc.contributor.author	Platov B.V.
dc.date.accessioned	2022-02-09T20:49:05Z
dc.date.available	2022-02-09T20:49:05Z
dc.date.issued	2021
dc.identifier.issn	2555-0403
dc.identifier.uri	https://dspace.kpfu.ru/xmlui/handle/net/170496
dc.description.abstract	The article describes the use of an artificial neural network to calculate porosity in the West Siberian oil and gas province for the UK2-7 strata. The estimated porosity was compared with core porosity data. Correlation coefficient between core samples porosity and well logging porosity (using the neural network) showed higher values in comparison with traditional methods of porosity estimation.
dc.relation.ispartofseries	E3S Web of Conferences
dc.title	Application of neural network technology to calculate well logging porosity on the example of UK2-7 formations in the Yelizarovsky deflection (Western Siberia)
dc.type	Conference Proceeding
dc.relation.ispartofseries-volume	266
dc.collection	Публикации сотрудников КФУ
dc.source.id	SCOPUS25550403-2021-266-SID85108216620

Файлы в этом документе

Имя: SCOPUS25550403-20 ...

Размер: 45.33Kb

Формат: PDF

Публикации сотрудников КФУ Scopus [24551]
Коллекция содержит публикации сотрудников Казанского федерального (до 2010 года Казанского государственного) университета, проиндексированные в БД Scopus, начиная с 1970г.