The Use of Artificial Neural Networks and Genetic Algorithms for Effectively Optimizing Production from Multiphase Flow Wells

Bottom-hole pressure (BHP) and separator pressure (SEPP) are playing an important role in defining the general fashion of production from upstream and downstream systems. The need for accurate prediction of these parameters is a key factor in clearly understanding multiphase flow in tubing. Predicti...

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Main Author: Ayoub, Mohammed Abdalla
Format: Conference or Workshop Item
Institution: Universiti Teknologi Petronas
Record Id / ISBN-0: utp-eprints.10573 /
Published: 2010
Online Access: http://eprints.utp.edu.my/10573/1/ICIPEG2010ORIGINAL.pdf
http://www.utp.edu.my/icipeg2010/images/stories/docs/conference-programme2010.pdf
http://eprints.utp.edu.my/10573/
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spelling utp-eprints.105732017-03-20T01:59:51Z The Use of Artificial Neural Networks and Genetic Algorithms for Effectively Optimizing Production from Multiphase Flow Wells Ayoub, Mohammed Abdalla Bottom-hole pressure (BHP) and separator pressure (SEPP) are playing an important role in defining the general fashion of production from upstream and downstream systems. The need for accurate prediction of these parameters is a key factor in clearly understanding multiphase flow in tubing. Prediction of pressure drop in multiphase flow is quite difficult and complicated due to the complex relationships between the various parameters involved. As they considered very hard obtaining parameters, bottom-hole pressure and separator pressure are selected for prediction using Artificial Neural Networks. The latter will be utilized in attempt at this study to generate a generic model for predicting bottom-hole and separator pressures in multiphase flow tubing that accounts for all angles of inclination. Artificial Neural Networks provide an easy and trustable means for predicting these parameters with high degree of confidence. Moreover, the output from the ANNs will be utilized plus selected other input parameters as controlling variables for optimizing the production from a multiphase producing field using Genetic Algorithms (GA). 2010-06-17 Conference or Workshop Item PeerReviewed application/pdf http://eprints.utp.edu.my/10573/1/ICIPEG2010ORIGINAL.pdf http://www.utp.edu.my/icipeg2010/images/stories/docs/conference-programme2010.pdf Ayoub, Mohammed Abdalla (2010) The Use of Artificial Neural Networks and Genetic Algorithms for Effectively Optimizing Production from Multiphase Flow Wells. In: ICIPEG 2010, part of ESTCON 2010, 15-17 June 2010, Kuala Lumpur. (Submitted) http://eprints.utp.edu.my/10573/
institution Universiti Teknologi Petronas
collection UTP Institutional Repository
description Bottom-hole pressure (BHP) and separator pressure (SEPP) are playing an important role in defining the general fashion of production from upstream and downstream systems. The need for accurate prediction of these parameters is a key factor in clearly understanding multiphase flow in tubing. Prediction of pressure drop in multiphase flow is quite difficult and complicated due to the complex relationships between the various parameters involved. As they considered very hard obtaining parameters, bottom-hole pressure and separator pressure are selected for prediction using Artificial Neural Networks. The latter will be utilized in attempt at this study to generate a generic model for predicting bottom-hole and separator pressures in multiphase flow tubing that accounts for all angles of inclination. Artificial Neural Networks provide an easy and trustable means for predicting these parameters with high degree of confidence. Moreover, the output from the ANNs will be utilized plus selected other input parameters as controlling variables for optimizing the production from a multiphase producing field using Genetic Algorithms (GA).
format Conference or Workshop Item
author Ayoub, Mohammed Abdalla
spellingShingle Ayoub, Mohammed Abdalla
The Use of Artificial Neural Networks and Genetic Algorithms for Effectively Optimizing Production from Multiphase Flow Wells
author_sort Ayoub, Mohammed Abdalla
title The Use of Artificial Neural Networks and Genetic Algorithms for Effectively Optimizing Production from Multiphase Flow Wells
title_short The Use of Artificial Neural Networks and Genetic Algorithms for Effectively Optimizing Production from Multiphase Flow Wells
title_full The Use of Artificial Neural Networks and Genetic Algorithms for Effectively Optimizing Production from Multiphase Flow Wells
title_fullStr The Use of Artificial Neural Networks and Genetic Algorithms for Effectively Optimizing Production from Multiphase Flow Wells
title_full_unstemmed The Use of Artificial Neural Networks and Genetic Algorithms for Effectively Optimizing Production from Multiphase Flow Wells
title_sort use of artificial neural networks and genetic algorithms for effectively optimizing production from multiphase flow wells
publishDate 2010
url http://eprints.utp.edu.my/10573/1/ICIPEG2010ORIGINAL.pdf
http://www.utp.edu.my/icipeg2010/images/stories/docs/conference-programme2010.pdf
http://eprints.utp.edu.my/10573/
_version_ 1741196124824272896
score 11.62408

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