Prediction of solid-vapor-liquid equilibrium in natural gas using ANNs

Muhannad T. Shuker, Firas Basim Ismail

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

In the last five decades, several studies have been performed on the measurement and predication of hydrate forming conditions. Many correlations were presented in the literature, but most of these correlations considered pure gases and their mixtures which leads to low accuracy. In addition, some of these correlations are presented mainly in graphical form, thus making it difficult to use them within general computer packages for simulation and design. The purpose of this work is to present a comprehensive neural network model for predicting hydrate formation conditions for pure gases and gas mixtures. The neural network model enables the user to accurately predict hydrate formation conditions for a given gas mixture, without having to do costly experimental measurements.

Original languageEnglish
Title of host publicationSociety of Petroleum Engineers - International Petroleum Technology Conference 2012, IPTC 2012
Pages3470-3476
Number of pages7
Publication statusPublished - 28 May 2012
EventInternational Petroleum Technology Conference 2012, IPTC 2012 - Bangkok, Thailand
Duration: 07 Feb 201209 Feb 2012

Publication series

NameSociety of Petroleum Engineers - International Petroleum Technology Conference 2012, IPTC 2012
Volume4

Other

OtherInternational Petroleum Technology Conference 2012, IPTC 2012
CountryThailand
CityBangkok
Period07/02/1209/02/12

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All Science Journal Classification (ASJC) codes

  • Geochemistry and Petrology

Cite this

Shuker, M. T., & Ismail, F. B. (2012). Prediction of solid-vapor-liquid equilibrium in natural gas using ANNs. In Society of Petroleum Engineers - International Petroleum Technology Conference 2012, IPTC 2012 (pp. 3470-3476). (Society of Petroleum Engineers - International Petroleum Technology Conference 2012, IPTC 2012; Vol. 4).