Analysis and Prediction of Fluid Flow Behavior in Progressing Cavity PumpsSource: Journal of Fluids Engineering:;2017:;volume( 139 ):;issue: 012::page 121102DOI: 10.1115/1.4037057Publisher: The American Society of Mechanical Engineers (ASME)
Abstract: A progressing cavity pump (PCP) is a positive displacement pump with an eccentric screw movement, which is used as an artificial lift method in oil wells. Downhole PCP systems provide an efficient lifting method for heavy oil wells producing under cold production, with or without sand. Newer PCP designs are also being used to produce wells operating under thermal recovery. The objective of this study is to develop a set of theoretical operational, fluid property, and pump geometry dimensionless groups that govern fluid flow behavior in a PCP. A further objective is to correlate these dimensionless groups to develop a simple model to predict flow rate (or pressure drop) along a PCP. Four PCP dimensionless groups, namely, Euler number, inverse Reynolds number, specific capacity number, and Knudsen number were derived from continuity, Navier–Stokes equations, and appropriate boundary conditions. For simplification, the specific capacity and Knudsen dimensionless groups were combined in a new dimensionless group named the PCP number. Using the developed dimensionless groups, nonlinear regression modeling was carried out using large PCP experimental database to develop dimensionless empirical models of both single- and two-phase flow in a PCP. The developed single-phase model was validated against an independent single-phase experimental database. The validation study results show that the developed model is capable of predicting pressure drop across a PCP for different pump speeds with 85% accuracy.
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| contributor author | Al-Safran, Eissa | |
| contributor author | Aql, Ahmed | |
| contributor author | Nguyen, Tan | |
| date accessioned | 2017-11-25T07:16:38Z | |
| date available | 2017-11-25T07:16:38Z | |
| date copyright | 2017/28/8 | |
| date issued | 2017 | |
| identifier issn | 0098-2202 | |
| identifier other | fe_139_12_121102.pdf | |
| identifier uri | http://138.201.223.254:8080/yetl1/handle/yetl/4234103 | |
| description abstract | A progressing cavity pump (PCP) is a positive displacement pump with an eccentric screw movement, which is used as an artificial lift method in oil wells. Downhole PCP systems provide an efficient lifting method for heavy oil wells producing under cold production, with or without sand. Newer PCP designs are also being used to produce wells operating under thermal recovery. The objective of this study is to develop a set of theoretical operational, fluid property, and pump geometry dimensionless groups that govern fluid flow behavior in a PCP. A further objective is to correlate these dimensionless groups to develop a simple model to predict flow rate (or pressure drop) along a PCP. Four PCP dimensionless groups, namely, Euler number, inverse Reynolds number, specific capacity number, and Knudsen number were derived from continuity, Navier–Stokes equations, and appropriate boundary conditions. For simplification, the specific capacity and Knudsen dimensionless groups were combined in a new dimensionless group named the PCP number. Using the developed dimensionless groups, nonlinear regression modeling was carried out using large PCP experimental database to develop dimensionless empirical models of both single- and two-phase flow in a PCP. The developed single-phase model was validated against an independent single-phase experimental database. The validation study results show that the developed model is capable of predicting pressure drop across a PCP for different pump speeds with 85% accuracy. | |
| publisher | The American Society of Mechanical Engineers (ASME) | |
| title | Analysis and Prediction of Fluid Flow Behavior in Progressing Cavity Pumps | |
| type | Journal Paper | |
| journal volume | 139 | |
| journal issue | 12 | |
| journal title | Journal of Fluids Engineering | |
| identifier doi | 10.1115/1.4037057 | |
| journal fristpage | 121102 | |
| journal lastpage | 121102-11 | |
| tree | Journal of Fluids Engineering:;2017:;volume( 139 ):;issue: 012 | |
| contenttype | Fulltext |