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A Water Saturation Prediction Using Artificial Neural Networks and an Investigation on Cementation Factors and Saturation Exponent Variations in an Iranian Oil Well

Author
MARDI, M1 ; NUROZI, H1 ; EDALATKHAH, S1
[1] Petroleum University of Technology, Tehran, Iran, Islamic Republic of
Source

Petroleum science and technology. 2012, Vol 30, Num 1-4, pp 425-434, 10 p ; ref : 1/4 p

ISSN
1091-6466
Scientific domain
Energy
Publisher
Taylor & Francis, Colchester
Publication country
United Kingdom
Document type
Article
Language
English
Author keyword
artificial neural network cementation factor saturation exponent water saturation wireline logs
Keyword (fr)
Densité Porosité Réseau neuronal
Keyword (en)
Density Porosity Neural network
Keyword (es)
Densidad Porosidad Red neuronal
Classification
Pascal
001 Exact sciences and technology / 001D Applied sciences / 001D06 Energy / 001D06B Fuels / 001D06B02 Crude oil, natural gas and petroleum products / 001D06B02D Processing of crude oil and oils from shales and tar sands. Processes. Equipment. Refinery and treatment units

Pascal
001 Exact sciences and technology / 001D Applied sciences / 001D06 Energy / 001D06B Fuels / 001D06B02 Crude oil, natural gas and petroleum products / 001D06B02E Petroleum products, gas and fuels. Motor fuels, lubricants and asphalts

Discipline
Energy
Origin
Inist-CNRS
Database
PASCAL
INIST identifier
25527877

Sauf mention contraire ci-dessus, le contenu de cette notice bibliographique peut être utilisé dans le cadre d’une licence CC BY 4.0 Inist-CNRS / Unless otherwise stated above, the content of this bibliographic record may be used under a CC BY 4.0 licence by Inist-CNRS / A menos que se haya señalado antes, el contenido de este registro bibliográfico puede ser utilizado al amparo de una licencia CC BY 4.0 Inist-CNRS

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