Avaliação térmica de motores de bombas centrífugas submersas empregando sensoriamento óptico distribuído

Abstract

Electric Submersible Pump (ESP) motors are fundamental components in artificial lift systems for oil production and operate in harsh environments in which thermal performance governs equipment reliability and service life. Stator heating, arising from electrical losses and influenced by the heat-transfer regime associated with annular flow, can accelerate insulation-system degradation and trigger premature failures with significant operational and economic consequences. This study investigates a distributed thermal-mapping approach for ESP motors using fiber-optic temperature sensing based on Raman scattering, aiming to overcome the limitations of point measurements typically employed in field applications and to obtain temperature profiles across different motor regions. The method relies on the ratio between the Raman Stokes and anti-Stokes components of the backscattered signal, while the position along the motor is inferred from the optical pulse time of flight, enabling temperature reconstruction along the installed fiber. Two submersible motors were instrumented with a continuous optical fiber routed through representative external and internal regions and tested under controlled variations of annular-flow rate and supply frequency. The results revealed thermal profiles with peak temperatures concentrated in the upper portion of the motor, as well as a reduction in mean temperatures with increasing flow rate. To deepen the physical interpretation of heat-transfer mechanisms and extend the analysis to motor regions not accessible to instrumentation, such as the rotor and the air gap, computational fluid dynamics simulations were performed, yielding good agreement between simulated thermal patterns and experimentally measured profiles. It is concluded that fiber-optic distributed temperature sensing is a promising technique for thermal monitoring of ESP motors, providing support for model calibration and operational decision-making based on temperature profiles, with the potential to enable early fault identification and improve the operational reliability of these systems.