Prediction of Oil Well Flowing Bottom-hole Pressure in Petroleum Fields

Medhat Awadalla*, Hassan Yousef, Ahmed Al-Hinai, Ali Al-Shidani

*Corresponding author for this work

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

4 Citations (Scopus)

Abstract

Installation of down-hole gauges in oil wells to determine Flowing Bottom-Hole Pressure is a dominant process especially in wells lifted with electrical submersible pumps. However intervening a well is occasionally an exhaustive task, associated with production risk, and interruption. The empirical correlations and mechanistic models failed to provide a satisfactory and reliable tool for estimating pressure drop in multiphase flowing wells. This paper proposes Feed- Forward Neural Network with back-propagation algorithm to predict the flowing bottom-hole pressure in vertical oil wells using real measured data from different oil fields. Intensive experiments have been conducted and the standard statistical analysis has been accomplished on the achieved results to validate the models' prediction accuracy. The obtained results show that the proposed artificial neural network is capable of estimating the Flowing Bottom-Hole Pressure with high accuracy.

Original languageEnglish
Title of host publication6th International Conference on Industrial Engineering and Operations Management in Kuala Lumpur, IEOM 2016
PublisherIEOM Society
Pages3007-3017
Number of pages11
ISBN (Print)9780985549749
Publication statusPublished - 2016
Event6th International Conference on Industrial Engineering and Operations Management in Kuala Lumpur, IEOM 2016 - Kuala Lumpur, Malaysia
Duration: Mar 8 2016Mar 10 2016

Publication series

NameProceedings of the International Conference on Industrial Engineering and Operations Management
Volume8-10 March 2016
ISSN (Electronic)2169-8767

Other

Other6th International Conference on Industrial Engineering and Operations Management in Kuala Lumpur, IEOM 2016
Country/TerritoryMalaysia
CityKuala Lumpur
Period3/8/163/10/16

Keywords

  • Back-propagation algorithm
  • Flowing bottom-hole pressure
  • Forward neural network

ASJC Scopus subject areas

  • Strategy and Management
  • Management Science and Operations Research
  • Control and Systems Engineering
  • Industrial and Manufacturing Engineering

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