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Permeability prediction using hybrid neural network modelling

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dc.contributor.author Maslennikova Y.
dc.date.accessioned 2018-09-18T20:35:44Z
dc.date.available 2018-09-18T20:35:44Z
dc.date.issued 2013
dc.identifier.uri https://dspace.kpfu.ru/xmlui/handle/net/141504
dc.description.abstract This paper presents a method for predicting permeability as one of the most important parameters in well logging. The method is based on the use of a hybrid neural network model consisting of several computational and one clustering neural networks. This approach to permeability prediction for wells that are not involved in neural network training has been shown to ensure a high correlation with permeabilities determined by core analysis.
dc.title Permeability prediction using hybrid neural network modelling
dc.type Conference Paper
dc.relation.ispartofseries-volume 7
dc.collection Публикации сотрудников КФУ
dc.relation.startpage 5622
dc.source.id SCOPUS-2013-7-SID84894216950


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

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