Experimental analysis and simulation of progressing cavity pump performance in single-phase flow liquid condition.

摘要

Progressing cavity pump (PCP) is known as an artificial lift method which is best suitable for high viscosity and high solids content producing wells. Even though the pump had been effectively adopted and used in oil and gas industry for decades, there is a lack of understanding of how the pump design affects its performance.;This study incorporated the pure mechanistic model developed by Nguyen et al. (2014) to predict the theoretical pump performance for multi-lobes PCPs and a semi-empirical correlation, which takes care of the pump slippage, to predict the actual pump performance under real operating conditions. This unified model is embedded into a simulator written in Visual Basic for Applications (VBA) with a friendly graphical user interface (GUI). The simulator offers two different functions: (1) prediction of pump performance under real conditions, and (2) optimization of pump design. In other words, the simulator can be a powerful tool for pump manufacturers and operating companies not only to optimize pump design, but also to select the proper pump and the operating conditions for a particular well.;A number of tests were conducted by using the New Mexico Tech Pumping Facility (NMTPF) to validate the results obtained from the simulator. A 1:2 PCP was used as a testing pump. Natural oil with the viscosity ranging from 100--500 cP was used to study the effect of viscosity on the pump slippage. During the tests, the back pressures and the rotational speeds were varied from 0--300 Psi and 100--500 RPM, respectively to simulate the field conditions. The experimental results show that the simulator predicts well the pump performance with an average error of 2% under the testing conditions. In addition, simulators results also show similar behavior to experimental study in Gamboa et al. (March 2003) for metallic stator PCP. These validations give and amplify support to the accuracy and reliability of the model prediction and the developed simulator. Results of this research can be utilized to optimize PCP design as well as to improve PCP performance and efficiency under downhole conditions.