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

Muhannad T. Shuker, Firas B. Ismail

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

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 publicationInternational Petroleum Technology Conference 2011, IPTC 2011
PublisherInternational Petroleum Technology Conference (IPTC)
ISBN (Print)9781613991480
Publication statusPublished - 01 Jan 2011
EventInternational Petroleum Technology Conference 2011, IPTC 2011 - Bangkok, Thailand
Duration: 15 Nov 201117 Nov 2011

Publication series

NameInternational Petroleum Technology Conference 2011, IPTC 2011

Other

OtherInternational Petroleum Technology Conference 2011, IPTC 2011
CountryThailand
CityBangkok
Period15/11/1117/11/11

All Science Journal Classification (ASJC) codes

  • Fuel Technology
  • Geochemistry and Petrology
  • Geophysics
  • Geotechnical Engineering and Engineering Geology

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    Shuker, M. T., & Ismail, F. B. (2011). Prediction of solid-vapor-liquid equilibrium in natural gas using ANNs. In International Petroleum Technology Conference 2011, IPTC 2011 (International Petroleum Technology Conference 2011, IPTC 2011). International Petroleum Technology Conference (IPTC).