Desarrollo de un software de análisis predictivo para la detección temprana de tendencias que ocasionen fallas y consideraciones para la prevención de estos efectos en bombas electrosumergibles. (2021)
The use of submersible pumps has increased greatly in the industry over the years due to its versatility to operate in non-conventional environments, but it is also the artificial lifting system most likely to fail during operations, therefore, it is essential to have anomaly detection software that prevents the development of faults and thus generate a significant impact on the financial flow of a project and on the run life of the equipment. In this degree work, the development and implementation of a predictive algorithm is detailed in which the analysis of typical trends of some failures in the operation of an ESP equipment is condensed, for this purpose the behavior of the variables is addressed in the initial chapter more representative ones provided by the bottomhole sensor, in order to identifying the trends that represent a development of faults, subsequently the structuring and design of the work flow to be carried out for the consolidation of the modules involved that set up the base algorithm is described. of the software.