Introducing a new method for predicting PVT properties of Iranian crude oils by applying artificial neural networks

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Introducing a new method for predicting PVT properties of Iranian crude oils by applying artificial neural networks. / Moghadam, J. Naseryan; Salahshoor, K.; Kharrat, R.
In: Petroleum science and technology, Vol. 29, No. 10, 01.2011, p. 1066-1079.

Research output: Contribution to journal › Article › Research › peer-review

Harvard

Moghadam, JN, Salahshoor, K & Kharrat, R 2011, 'Introducing a new method for predicting PVT properties of Iranian crude oils by applying artificial neural networks', Petroleum science and technology, vol. 29, no. 10, pp. 1066-1079. https://doi.org/10.1080/10916460903551040

APA

Moghadam, J. N., Salahshoor, K., & Kharrat, R. (2011). Introducing a new method for predicting PVT properties of Iranian crude oils by applying artificial neural networks. Petroleum science and technology, 29(10), 1066-1079. https://doi.org/10.1080/10916460903551040

Vancouver

Moghadam JN, Salahshoor K, Kharrat R. Introducing a new method for predicting PVT properties of Iranian crude oils by applying artificial neural networks. Petroleum science and technology. 2011 Jan;29(10):1066-1079. doi: 10.1080/10916460903551040

Author

Moghadam, J. Naseryan ; Salahshoor, K. ; Kharrat, R. / Introducing a new method for predicting PVT properties of Iranian crude oils by applying artificial neural networks. In: Petroleum science and technology. 2011 ; Vol. 29, No. 10. pp. 1066-1079.

Bibtex - Download

@article{95a767171ab149f18536e84c90d19012,
title = "Introducing a new method for predicting PVT properties of Iranian crude oils by applying artificial neural networks",
keywords = "artificial neural network, bubble point pressure, cross validation data set, oil formation volume factor, PVT correlations, PVT properties, training data set",
author = "Moghadam, {J. Naseryan} and K. Salahshoor and R. Kharrat",
year = "2011",
month = jan,
doi = "10.1080/10916460903551040",
language = "English",
volume = "29",
pages = "1066--1079",
journal = "Petroleum science and technology",
issn = "1091-6466",
number = "10",

}

RIS (suitable for import to EndNote) - Download

TY - JOUR

T1 - Introducing a new method for predicting PVT properties of Iranian crude oils by applying artificial neural networks

AU - Moghadam, J. Naseryan

AU - Salahshoor, K.

AU - Kharrat, R.

PY - 2011/1

Y1 - 2011/1

KW - artificial neural network

KW - bubble point pressure

KW - cross validation data set

KW - oil formation volume factor

KW - PVT correlations

KW - PVT properties

KW - training data set

UR - http://www.scopus.com/inward/record.url?scp=79953083008&partnerID=8YFLogxK

U2 - 10.1080/10916460903551040

DO - 10.1080/10916460903551040

M3 - Article

AN - SCOPUS:79953083008

VL - 29

SP - 1066

EP - 1079

JO - Petroleum science and technology

JF - Petroleum science and technology

SN - 1091-6466

IS - 10

ER -

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