A Modified Version of the Aziz et al. Multiphase Flow Correlation Improves Pressure Drop Calculations in High-Rate Oil Wells

Author(s):  
Hazim Hassan Al-Attar ◽  
Mohamed Mohamed ◽  
Mohamed Amin
1999 ◽  
Vol 121 (2) ◽  
pp. 86-90 ◽  
Author(s):  
C. Kang ◽  
W. P. Jepson ◽  
M. Gopal

The effect of drag-reducing agent (DRA) on multiphase flow in upward and downward inclined pipes has been studied. The effect of DRA on pressure drop and slug characteristics such as slug translational velocity, the height of the liquid film, slug frequency, and Froude number have been determined. Experiments were performed in 10-cm i.d., 18-m long plexiglass pipes at inclinations of 2 and 15 deg for 50 percent oil-50 percent water-gas. The DRA effect was examined for concentrations ranging from 0 to 50 ppm. Studies were done for superficial liquid velocities between 0.5 and 3 m/s and superficial gas velocities between 2 and 10 m/s. The results indicate that the DRA was effective in reducing the pressure drop for both upflow and downflow in inclined pipes. Pressure gradient reduction of up to 92 percent for stratified flow with a concentration of 50 ppm DRA was achieved in ±2 deg downward inclined flow. The effectiveness of DRA for slug flow was 67 percent at a superficial liquid velocity of 0.5 m/s and superficial gas velocity of 2 m/s in 15 deg upward inclined pipes. Slug translational velocity does not change with DRA concentrations. The slug frequency decreases from 68 to 54 slugs/min at superficial liquid velocity of 1 m/s and superficial gas velocity of 4 m/s in 15 deg upward inclined pipes as the concentration of 50 ppm was added. The height of the liquid film decreased with the addition of DRA, which leads to an increase in Froude number.


2019 ◽  
Vol 4 (1) ◽  
pp. 54-59
Author(s):  
David Nwobisi Wordu ◽  
Felix J. K. Ideriah ◽  
Barinyima Nkoi

The study of multiphase flow in vertical pipes is aimed at effective and accurate design of tubing, surface facilities and well performance optimization for the production of oil and gas in the petroleum industry by developing a better approach for predicting pressure gradient. In this study, field data was analyzed using mathematical model, multiphase flow correlations, statistical model, and computer programming to predict accurately the flow regime, liquid holdup and pressure drop gradient which are important in the optimization of well. A Computer programme was used to prediction pressure drop gradient. Four dimensionless parameters liquid velocity number (Nlv), gas velocity number (Ngv), pipe diameter number (Nd), liquid viscosity number (Nl), were chosen because they represent an integration of the two dominant components that influence pressure drop in pipes. These dominant component are flow channel/media and the flowing fluid. The model was found to give a fit of 100% to the selected data points. Hagedorn & Brown, Griffith &Wallis correlations and model were compared with field data and the overall pressure gradient for a total depth of 10000ft was predicted. The predicted pressure gradient measured was found to be 0.320778psi/ft, Graffith& Wallis gave 0.382649Psi/ft, Hagedorn & Brown gave 0.382649Psi/ft; whereas generated model gave 0.271514Psi/ft. These results indicate that the model equation generated is better and leads to a reasonably accurate prediction of pressure drop gradient according to measured pressure gradient.


Author(s):  
C. Kang ◽  
W. P. Jepson

Abstract Experimental studies have been performed in a 10 cm diameter, 36 m long, multiphase flow loop to examine the effect of drag reducing agents using 6 cP oil. Studies were performed for superficial liquid velocities of 0.5, 1.0 and 1.5 m/s and superficial gas velocities between 2 and 12 m/s. Carbon dioxide was used as the gas phase. The drag reducing agent (DRA) concentrations were 20 and 50 ppm. The system was maintained at a pressure of 0.13 MPa and a temperature of 25 °C. The comparison of the conditioning of flow with DRA between 2.5 cP oil and 6 cP oil is presented. The results show that pressure drop in both 2.5 cP oil and 6 cP oil was reduced significantly in multiphase flow with addition of DRA. A DRA concentration of 50 ppm was more effective than 20 ppm DRA for all cases. As the oil viscosity was increased from 2.5 cP to 6 cP oil, the transition to annular flow was observed to occur at lower superficial gas velocities. For slug flow and lower superficial gas velocities, the effectiveness in 2.5 cP oil was much higher than that in 6 cP oil with addition of DRA. However, for higher superficial gas velocities, the effectiveness in both oils was similar. For annular flow, the effectiveness in 2.5 cP oil was higher than in 6 cP oil with 50 ppm DRA. At low superficial gas velocities, DRA in 2.5 cP oil was more effective in reducing the slug frequency. This led to a higher average pressure drop reduction in 2.5 cP oil. However, at higher superficial gas velocities, the slug frequency decreased in both oils almost the same magnitude.


1988 ◽  
Author(s):  
A. Roux ◽  
J. Corteville ◽  
M. Bernicot
Keyword(s):  

2017 ◽  
Vol 139 (12) ◽  
Author(s):  
Eissa Al-Safran ◽  
Ahmed Aql ◽  
Tan Nguyen

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.


Sign in / Sign up

Export Citation Format

Share Document