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espanolRESUMEN La seleccion del sistema de levantamiento artificial es un factor clave para mejorar la eficiencia energetica, aumentar los beneficios y ampliar la vida util de los activos en cualquier pozo productor de petroleo. Teoricamente, esta seleccion debe tener en cuenta un gran numero de variables, lo que dificulta la eleccion del sistema optimo. Sin embargo, en la practica, este proceso involucra un numero limitado de variables y conocimiento empirico lo cual aumenta la probabilidad de falla del sistema debido a la incompatibilidad entre la bomba y el pozo. Los metodos de toma de decisiones multicriterio presentan modelos matematicos para procesos de seleccion con alternativas finitas y un alto numero de criterios. Estas metodologias hacen factible tomar una decision considerando todas las variables involucradas. En este articulo, presentamos una aplicacion software basada en un analisis matematico secuencial jerarquico de variables, una validacion numerica de datos de entrada y una implementacion de metodos multicriterio para toma de decisiones (MCDM, por sus siglas en ingles): SAW, ELECTRE y VIKOR. Esto con el fin de seleccionar el sistema de levantamiento artificial mas adecuado. Su novedoso algoritmo esta disenado para clasificar siete sistemas, considerando diversas variables en la toma de decision. Los resultados se validan con datos de un campo colombiano, enfocandose en reducir el indice de falla de los pozos de dicho campo. EnglishABSTRACT Artificial Lift system selection is a key factor in enhancing energy efficiency, increasing profit and expanding asset life in any oil-producing well. Theoretically, this selection has to consider an extensive number of variables, making hard to select the optimal Artificial Lift System. However, in practice, a limited number of variables and empirical knowledge are used in this selection process. The latter increases system failure probability due to pump - well incompatibility. The multi-criteria decision-making methods present mathematical modelling for selection processes with finite alternatives and high number of criteria. These methodologies make it feasible to reach a final decision considering all variables involved. In this paper, we present a software application based on a sequential mathematical analysis of hierarchies for variables, a numerical validation of input data and, finally, an implementation of Multi-Criteria Decision Making (MCDM) methods (SAW, ELECTRE and VIKOR) to select the most adequate artificial lift system for crude oil production in Colombia. Its novel algorithm is designed to rank seven Artificial Lift Systems, considering diverse variables in order to make the decision. The results are validated with field data in a Case study relating to a Colombian oilfield, with the aim of reducing the Artificial Lift Failure Rate.

Modelling approach for multi-criteria decision-making selection process for artificial lift systems in crude oil production