Clustering techniques applied to detection of inefficiency in electrical submersible pumps startup

Electrical submersible pumps have been increasingly used in the oil industry. The startup cycle of this equipment causes it to be subjected to extreme conditions that can reduce its useful life. In addition, the oil flow produced during this process is lower than the normal operating condition. Currently, the control of this process is manual and subject to operator experience and sensitivity. In this way, mechanisms that allow to evaluate and increase the efficiency of this process are necessary. The methodology proposed in this work applies clustering technique to identify the possibility of reducing process time and was feasible.

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