Development and construction of a test bench emulating an artificial lift system with Progressive Cavity Pumps (PCPs).
Progressing cavity pump; artificial lift systems; backspin; hydraulic torque; dynamic modeling; condition monitoring; artificial intelligence
This work investigates the backspin phenomenon in artificial lift systems employing progressing cavity pumps (PCPs), with emphasis on dynamic modeling, analysis of the underlying physical mechanisms, and the development of a dedicated experimental platform for its controlled reproduction. Mathematical models are first established to describe the electromechanical and hydraulic coupling of the system, enabling the assessment of pressure variations, dynamic fluid level, and hydraulic torque effects on the motor–rod string–pump dynamics. In this framework, the hydraulic torque is identified as the main dynamic component of the total torque applied to the pump rotor, particularly during transient operating conditions that precede undesired rotational reversal.
Based on these foundations, an experimental platform capable of safely and repeatably reproducing critical operating conditions associated with backspin is presented. This infrastructure allows the synchronized acquisition of electrical and mechanical variables, enabling the identification of characteristic patterns in electrical signals that precede the onset of the phenomenon. Building upon this experimental basis, the work explores the use of artificial intelligence techniques for early diagnosis and prediction of backspin, demonstrating their potential as effective tools for monitoring and for the development of preventive strategies in progressing cavity pumping systems.