Introducing a New Method for Predicting PVT Properties of Iranian Crude Oils by Applying Artificial Neural Networks

Author： Moghadam J. Naseryan Salahshoor K. Kharrat R.

ISSN： 1091-6466

Source： Petroleum Science and Technology, Vol.29, Iss.10, 2011-01, pp. : 1066-1079

Disclaimer: Any content in publications that violate the sovereignty, the constitution or regulations of the PRC is not accepted or approved by CNPIEC.

Previous Menu Next

Abstract

Related content

The Application of Artificial Neural Networks in Determination of Bubble Point Pressure for Iranian Crude Oils

By Moghadasi J. Kazemi K. Moradi S.

Petroleum Science and Technology, Vol. 31, Iss. 23, 2013-12 ,pp. : 2475-2482

Taylor & Francis Ltd

Access to resources Recommend Favorite

New Empirical Correlations for Predicting Crude Oil Properties

By Nikpoor M. H. Khanamiri H. H.

Petroleum Science and Technology, Vol. 29, Iss. 16, 2011-07 ,pp. : 1649-1658

Taylor & Francis Ltd

Access to resources Recommend Favorite

Predicting temperature profiles in producing oil wells using artificial neural networks

By Farshad Fred F Garber James D Lorde Juliet N

Engineering Computations: Int J for Computer-Aided Engineering, Vol. 17, Iss. 6, 2000-06 ,pp. : 735-754

Emerald Group Publishing Ltd

Access to resources Recommend Favorite

Artificial neural networks for predicting creep with an example application to structural masonry

By Taha M.M R. Noureldin A El-Sheimy N Shrive N G

Canadian Journal of Civil Engineering, Vol. 30, Iss. 3, 2003-06 ,pp. : 523-532

NRC Research Press

Access to resources Recommend Favorite

A Correlations Approach for Prediction of PVT Properties of Reservoir Oils

By Naseri A. Khishvand M. Sheikhloo A. A.

Petroleum Science and Technology, Vol. 32, Iss. 17, 2014-09 ,pp. : 2123-2136

Taylor & Francis Ltd

Access to resources Recommend Favorite