Optimized parameters of downhole all-metal PDM based on genetic algorithm

Abstract

Currently, deep drilling operates under extreme conditions of high temperature and high pressure, demanding more from subterranean power motors. The all-metal positive displacement motor, known for its robust performance, is a critical choice for such drilling. The dimensions of the PDM are crucial for its performance output. To enhance this, optimization of the motor's profile using a genetic algorithm has been undertaken. The design process begins with the computation of the initial stator and rotor curves based on the equations for a screw cycloid. These curves are then refined using the least squares method for a precise fit. Following this, the PDM's mathematical model is optimized, and motor friction is assessed. The genetic algorithm process involves encoding variations and managing crossovers to optimize objective functions, including the isometric radius coefficient, eccentricity distance parameter, overflow area, and maximum slip speed. This optimization yields the ideal profile parameters that enhance the motor's output. Comparative analyses of the initial and optimized output characteristics were conducted, focusing on the effects of the isometric radius coefficient and overflow area on the motor's performance. Results indicate that the optimized motor's overflow area increased by 6.9%, while its rotational speed reduced by 6.58%. The torque, as tested by Infocus, saw substantial improvements of 38.8%. This optimization provides a theoretical foundation for improving the output characteristics of all-metal PDMs and supports the ongoing development and research of PDM technology.