Please use this identifier to cite or link to this item: http://repositorio.unicamp.br/jspui/handle/REPOSIP/346839
Type: Artigo
Title: Multiphase gas-flow model of an electrical submersible pump
Author: Ricardo, Diana Marcela Martinez
Jiménez, German Efrain Castañeda
Ferreira, Janito Vaqueiro
Meirelles, Pablo Siqueira
Abstract: Various artificial lifting systems are used in the oil and gas industry. An example is the Electrical Submersible Pump (ESP). When the gas flow is high, ESPs usually fail prematurely because of a lack of information about the two-phase flow during pumping operations. Here, we develop models to estimate the gas flow in a two-phase mixture being pumped through an ESP. Using these models and experimental system response data, the pump operating point can be controlled. The models are based on nonparametric identification using a support vector machine learning algorithm. The learning machine’s hidden parameters are determined with a genetic algorithm. The results obtained with each model are validated and compared in terms of estimation error. The models are able to successfully identify the gas flow in the liquid-gas mixture transported by an ESP
Subject: Gás
Escoamento multifásico
Country: França
Editor: EDP Sciences
Rights: Aberto
Identifier DOI: 10.2516/ogst/2018031
Address: https://ogst.ifpenergiesnouvelles.fr/articles/ogst/full_html/2018/01/ogst160174/ogst160174.html
Date Issue: 2018
Appears in Collections:FEM - Artigos e Outros Documentos

Files in This Item:
File Description SizeFormat 
000443327800001.pdf837.48 kBAdobe PDFView/Open


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.