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This paper presents an approach to get a mathematical model for describing the production of an Electro Submersible Oil Pumping System (ESP). The determination of this mathematical model considering the variables of the process, is a very hard task. In this case, we propose the determination of this model using a data approach, in order to exploit the large quantity of data about the process obtained from its sensors. Our approach based on data uses the genetic programming techniques for the identification of the mathematical model, which follows an evolutionary process to solve the problem. Our approach has been implemented using an extension of R program. The training data were collected from an oil well. This paper presents the results of the training phase and of the generated models after several iterations. Additionally, the paper analyses the differences between the generated models, according to the number of variables considered, the complexity of the expressions, and the error.

Developing a Mathematical Model of Oil Production in a Well That Uses an Electric Submersible Pumping System