Modelling of petroleum multiphase fluids in ESPs an intelligent approach

M. Mohammadzaheri, Reza Tafreshi, Z. Khan, M. Franchek, K. Grigoriadis

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

2 Citations (Scopus)

Abstract

This paper proposes an artificial neural network (ANN) to estimate head of two-phase petroleum fluids in electrical submersible pumps (ESPs) as an alternative to existing widely used empirical models. Analytical models have been also developed for this purpose which are still unattractive due to their complexity, reliance on over-simplified assumptions, need to excessive extent of information or lack of accuracy. The proposed ANN is trained with the same data used in developing a number of empirical models; however, the ANN presents evidently higher accuracy in the entire operating area with a low computation time in the order of milliseconds to be run on an office personal computer.

Original languageEnglish
Title of host publicationOffshore Mediterranean Conference and Exhibition, OMC 2015
PublisherOffshore Mediterranean Conference
ISBN (Print)9788894043648
Publication statusPublished - 1 Jan 2015
EventOffshore Mediterranean Conference and Exhibition, OMC 2015 - Ravenna, Italy
Duration: 25 Mar 201527 Mar 2015

Other

OtherOffshore Mediterranean Conference and Exhibition, OMC 2015
CountryItaly
CityRavenna
Period25/3/1527/3/15

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ASJC Scopus subject areas

  • Geotechnical Engineering and Engineering Geology
  • Geochemistry and Petrology

Cite this

Mohammadzaheri, M., Tafreshi, R., Khan, Z., Franchek, M., & Grigoriadis, K. (2015). Modelling of petroleum multiphase fluids in ESPs an intelligent approach. In Offshore Mediterranean Conference and Exhibition, OMC 2015 Offshore Mediterranean Conference.