A neo-fuzzy approach for bottom parameters estimation in oil wells

Edgar Camargo; Jose Aguilar; Addison Ríos; Francklin Rivas; Joseph Aguilar-Martin

A neo-fuzzy approach for bottom parameters estimation in oil wells

Edgar Camargo^*, Jose Aguilar, Addison Ríos, Francklin Rivas, Joseph Aguilar-Martin

^*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

7 Scopus citations

Abstract

In this work, an approach for the bottom parameters estimation in oil wells is presented. It is based on neural networks and fuzzy logic, specifically on the neo-fuzzy-neuron model. We propose a neo-fuzzy system compose by two neo-fuzzy neurons. For validating the results, the estimation is applied in oil wells based on the artificial gas lift method, using variables of the head of the wells, particularly the gas and production pressures.

Original language	English
Pages (from-to)	445-454
Number of pages	10
Journal	WSEAS Transactions on Systems and Control
Volume	4
Issue number	9
State	Published - Sep 2009
Externally published	Yes

Keywords

Artificial gas lift wells
Neofuzzy neurons
Neuro-fuzzy models
Oil system production
Oil wells
Parameters estimation

Cite this

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title = "A neo-fuzzy approach for bottom parameters estimation in oil wells",

abstract = "In this work, an approach for the bottom parameters estimation in oil wells is presented. It is based on neural networks and fuzzy logic, specifically on the neo-fuzzy-neuron model. We propose a neo-fuzzy system compose by two neo-fuzzy neurons. For validating the results, the estimation is applied in oil wells based on the artificial gas lift method, using variables of the head of the wells, particularly the gas and production pressures.",

keywords = "Artificial gas lift wells, Neofuzzy neurons, Neuro-fuzzy models, Oil system production, Oil wells, Parameters estimation",

author = "Edgar Camargo and Jose Aguilar and Addison R{\'i}os and Francklin Rivas and Joseph Aguilar-Martin",

year = "2009",

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T1 - A neo-fuzzy approach for bottom parameters estimation in oil wells

AU - Camargo, Edgar

AU - Aguilar, Jose

AU - Ríos, Addison

AU - Rivas, Francklin

AU - Aguilar-Martin, Joseph

PY - 2009/9

Y1 - 2009/9

N2 - In this work, an approach for the bottom parameters estimation in oil wells is presented. It is based on neural networks and fuzzy logic, specifically on the neo-fuzzy-neuron model. We propose a neo-fuzzy system compose by two neo-fuzzy neurons. For validating the results, the estimation is applied in oil wells based on the artificial gas lift method, using variables of the head of the wells, particularly the gas and production pressures.

AB - In this work, an approach for the bottom parameters estimation in oil wells is presented. It is based on neural networks and fuzzy logic, specifically on the neo-fuzzy-neuron model. We propose a neo-fuzzy system compose by two neo-fuzzy neurons. For validating the results, the estimation is applied in oil wells based on the artificial gas lift method, using variables of the head of the wells, particularly the gas and production pressures.

KW - Artificial gas lift wells

KW - Neofuzzy neurons

KW - Neuro-fuzzy models

KW - Oil system production

KW - Oil wells

KW - Parameters estimation

UR - https://www.scopus.com/pages/publications/70349572491

M3 - Article

AN - SCOPUS:70349572491

SN - 1991-8763

VL - 4

SP - 445

EP - 454

JO - WSEAS Transactions on Systems and Control

JF - WSEAS Transactions on Systems and Control

IS - 9

ER -

A neo-fuzzy approach for bottom parameters estimation in oil wells

Abstract

Keywords

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