Optimization model based on genetic algorithms for oil wells

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

Optimization model based on genetic algorithms for oil wells

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

^*Autor correspondiente de este trabajo

Producción científica: Capítulo del libro/informe/acta de congreso › Contribución de conferencia › revisión exhaustiva

1 Cita (Scopus)

Resumen

The Processes of optimization of oil wells involve an objective function that maximizes the commercial price and minimizes the production cost. For the solution of this type of problem, in the last decade the evolutionary technologies have demonstrated to be an effective and efficient tool. In this work is presented an Evolutionary System to improve the performance of the Industrial Production in petroleum wells that require gas lift (LAG). The system must optimize an objective composed by two criteria: to maximize the production of oil and to minimize the flow of gas injection, based on the restrictions of the process and the operational cost of production.

Idioma original	Inglés
Título de la publicación alojada	Advances in Computational Intelligence, Man-Machine Systems and Cybernetics - 9th WSEAS International Conference on Computational Intelligence, Man-Machine Systems and Cybernetics, CIMMACS'10
Páginas	131-139
Número de páginas	9
Estado	Publicada - 2010
Publicado de forma externa	Sí
Evento	9th WSEAS International Conference on Computational Intelligence, Man-Machine Systems and Cybernetics, CIMMACS'10 - Merida, República Bolivariana de Venezuela Duración: 14 dic. 2010 → 16 dic. 2010

Serie de la publicación

Nombre	International Conference on Computational Intelligence, Man-Machine Systems and Cybernetics - Proceedings

Conferencia

Conferencia	9th WSEAS International Conference on Computational Intelligence, Man-Machine Systems and Cybernetics, CIMMACS'10
País/Territorio	República Bolivariana de Venezuela
Ciudad	Merida
Período	14/12/10 → 16/12/10

Otros archivos y enlaces

Enlace a la publicación en Scopus

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Camargo, E., Aguilar, J., Ríos, A., Rivas, F., & Aguilar-Martin, J. (2010). Optimization model based on genetic algorithms for oil wells. En Advances in Computational Intelligence, Man-Machine Systems and Cybernetics - 9th WSEAS International Conference on Computational Intelligence, Man-Machine Systems and Cybernetics, CIMMACS'10 (pp. 131-139). (International Conference on Computational Intelligence, Man-Machine Systems and Cybernetics - Proceedings).

Camargo, Edgar ; Aguilar, José ; Ríos, Addison et al. / Optimization model based on genetic algorithms for oil wells. Advances in Computational Intelligence, Man-Machine Systems and Cybernetics - 9th WSEAS International Conference on Computational Intelligence, Man-Machine Systems and Cybernetics, CIMMACS'10. 2010. pp. 131-139 (International Conference on Computational Intelligence, Man-Machine Systems and Cybernetics - Proceedings).

@inproceedings{1355290a1fd448698730a8185305add4,

title = "Optimization model based on genetic algorithms for oil wells",

abstract = "The Processes of optimization of oil wells involve an objective function that maximizes the commercial price and minimizes the production cost. For the solution of this type of problem, in the last decade the evolutionary technologies have demonstrated to be an effective and efficient tool. In this work is presented an Evolutionary System to improve the performance of the Industrial Production in petroleum wells that require gas lift (LAG). The system must optimize an objective composed by two criteria: to maximize the production of oil and to minimize the flow of gas injection, based on the restrictions of the process and the operational cost of production.",

keywords = "Evolutionary computation, Model of production of well, Problem of optimization, Wells by artificial gas lift",

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

year = "2010",

language = "English",

isbn = "9789604742578",

series = "International Conference on Computational Intelligence, Man-Machine Systems and Cybernetics - Proceedings",

pages = "131--139",

booktitle = "Advances in Computational Intelligence, Man-Machine Systems and Cybernetics - 9th WSEAS International Conference on Computational Intelligence, Man-Machine Systems and Cybernetics, CIMMACS'10",

note = "9th WSEAS International Conference on Computational Intelligence, Man-Machine Systems and Cybernetics, CIMMACS'10 ; Conference date: 14-12-2010 Through 16-12-2010",

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Camargo, E, Aguilar, J, Ríos, A, Rivas, F & Aguilar-Martin, J 2010, Optimization model based on genetic algorithms for oil wells. En Advances in Computational Intelligence, Man-Machine Systems and Cybernetics - 9th WSEAS International Conference on Computational Intelligence, Man-Machine Systems and Cybernetics, CIMMACS'10. International Conference on Computational Intelligence, Man-Machine Systems and Cybernetics - Proceedings, pp. 131-139, 9th WSEAS International Conference on Computational Intelligence, Man-Machine Systems and Cybernetics, CIMMACS'10, Merida, República Bolivariana de Venezuela, 14/12/10.

Optimization model based on genetic algorithms for oil wells. / Camargo, Edgar; Aguilar, José; Ríos, Addison et al.
Advances in Computational Intelligence, Man-Machine Systems and Cybernetics - 9th WSEAS International Conference on Computational Intelligence, Man-Machine Systems and Cybernetics, CIMMACS'10. 2010. p. 131-139 (International Conference on Computational Intelligence, Man-Machine Systems and Cybernetics - Proceedings).

Producción científica: Capítulo del libro/informe/acta de congreso › Contribución de conferencia › revisión exhaustiva

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N2 - The Processes of optimization of oil wells involve an objective function that maximizes the commercial price and minimizes the production cost. For the solution of this type of problem, in the last decade the evolutionary technologies have demonstrated to be an effective and efficient tool. In this work is presented an Evolutionary System to improve the performance of the Industrial Production in petroleum wells that require gas lift (LAG). The system must optimize an objective composed by two criteria: to maximize the production of oil and to minimize the flow of gas injection, based on the restrictions of the process and the operational cost of production.

AB - The Processes of optimization of oil wells involve an objective function that maximizes the commercial price and minimizes the production cost. For the solution of this type of problem, in the last decade the evolutionary technologies have demonstrated to be an effective and efficient tool. In this work is presented an Evolutionary System to improve the performance of the Industrial Production in petroleum wells that require gas lift (LAG). The system must optimize an objective composed by two criteria: to maximize the production of oil and to minimize the flow of gas injection, based on the restrictions of the process and the operational cost of production.

KW - Evolutionary computation

KW - Model of production of well

KW - Problem of optimization

KW - Wells by artificial gas lift

UR - https://www.scopus.com/pages/publications/79958752392

M3 - Conference contribution

AN - SCOPUS:79958752392

SN - 9789604742578

T3 - International Conference on Computational Intelligence, Man-Machine Systems and Cybernetics - Proceedings

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BT - Advances in Computational Intelligence, Man-Machine Systems and Cybernetics - 9th WSEAS International Conference on Computational Intelligence, Man-Machine Systems and Cybernetics, CIMMACS'10

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Y2 - 14 December 2010 through 16 December 2010

ER -

Camargo E, Aguilar J, Ríos A, Rivas F, Aguilar-Martin J. Optimization model based on genetic algorithms for oil wells. En Advances in Computational Intelligence, Man-Machine Systems and Cybernetics - 9th WSEAS International Conference on Computational Intelligence, Man-Machine Systems and Cybernetics, CIMMACS'10. 2010. p. 131-139. (International Conference on Computational Intelligence, Man-Machine Systems and Cybernetics - Proceedings).