A critical analysis and improvements of empirical models for predicting the performance of Electrical Submersible Pumps under viscous flow

被引:2
|
作者
Verde, William Monte [1 ]
Kindermann, Ellen [2 ]
Bulgarelli, Natan Augusto Vieira [1 ]
Pastre, Luiz Fernando [2 ]
Foresti, Bernardo [3 ]
Bannwart, Antonio Carlos [1 ]
机构
[1] Univ Estadual Campinas, Ctr Energy & Petr Studies, Sao Paulo, Brazil
[2] Univ Estadual Campinas, Sch Mech Engn, Sao Paulo, Brazil
[3] Petrobras SA, Cenpes, Rio De Janeiro, Brazil
来源
GEOENERGY SCIENCE AND ENGINEERING | 2024年 / 238卷
关键词
Electrical Submersible Pump (ESP); Viscous flow; Performance degradation; Performance prediction; Correction factors; Empirical model; VISCOSITY;
D O I
10.1016/j.geoen.2024.212871
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
One of the main challenges associated with Electrical Submersible Pumps (ESPs) system is the correct sizing of the pump. High viscosity fluids, emulsions, or compressible fluids significantly impact the pump's ability to transfer energy to the fluid. Obtaining ESP characteristic curves in conditions resembling real applications is complex but essential for the correct design, operation, optimization, and safeguarding of ESP systems. The objective of this study is to critical assess the traditional methods for predicting the ESP performance under viscous flow. This study also improves these methods driven by ESP performance data. The results show that the original models have limitations because their databases are primarily based on data from conventional centrifugal pumps. Consequently, using these methods can result in significant errors in the sizing of the production system. The accuracy of the models improved significantly after modifying the methods. Reductions in errors were observed in all correction factors, and particularly in the prediction of global performance. The improvements were effective in mitigating the effects of increased deviations with the reduction in Reynolds number observed when applying the original models to predict flow rate and efficiency.
引用
收藏
页数:15
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