Adaptive neuro-fuzzy algorithm applied to predict and control multi-phase flow rates through wellhead chokes-Reference-Cited by-同舟云学术

Adaptive neuro-fuzzy algorithm applied to predict and control multi-phase flow rates through wellhead chokes

Published:2020-12 Issue: Volume:76 Page:101849
ISSN:0955-5986
Container-title:Flow Measurement and Instrumentation
language:en
Short-container-title:Flow Measurement and Instrumentation

Author:

Ghorbani Hamzeh,Wood David A.^ORCID,Mohamadian Nima,Rashidi Sina,Davoodi Shadfar^ORCID,Soleimanian Alireza,Shahvand Amirafzal Kiani,Mehrad Mohammad^ORCID

Publisher

Elsevier BV

Subject

Electrical and Electronic Engineering,Computer Science Applications,Instrumentation,Modeling and Simulation

Reference77 articles.

1. A new correlation for prediction of sub-critical two-phase flow pressure drop through large-sized wellhead chokes;Seidi;J. Nat. Gas Sci. Eng.,2015

2. Optimization of choke size for two-phase flow using artificial intelligence;Khamis;Journal of Petroleum Exploration and Production Technology,2020

3. Performance comparison of bubble point pressure from oil PVT data: several neurocomputing techniques compared;Ghorbani;Experimental Computational Multiphase Flow,2020

4. Predicting liquid flow-rate performance through wellhead chokes with genetic and solver optimizers: an oil field case study;Ghorbani;Journal of Petroleum Exploration and Production Technology,2019

5. Prediction of Oil Flow Rate through an Orifice Flow Meter: Artificial Intelligence Alternatives Compared;Ghorbani,2018

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