Two-Phase Flow Modeling in Oil and Gas Applications

2015 ◽  
Author(s):  
M. M. Awad ◽  
S. D. Butt
Keyword(s):  
Experimental Data ◽  
Asymptotic Analysis ◽  
Liquid Flow ◽  
Oil And Gas ◽  
Two Phase Flow ◽  
Phase Flow ◽  
Flow Modeling ◽  
Two Phase ◽  
New Model ◽  
Gas Liquid Flow

In the current study, two-phase flow modeling in oil and gas applications using asymptotic analysis is presented. Examples of two-phase liquid-liquid flow in pipes, two-phase gas-liquid flow in fractures, and two-phase gas-liquid flow in porous media are presented. In the present study, a simple semi-theoretical method for calculating the two-phase frictional pressure gradient in oil and gas applications using asymptotic analysis is presented. The proposed model can be transformed into two-phase frictional multiplier as a function of the Lockhart-Martinelli parameter, X. The advantage of the new model is that it has only one fitting parameter (p). Therefore, calibration of the new model to experimental data is greatly simplified. The new model is able to model the existing multi parameters correlations by fitting the single parameter p. Comparison with experimental data for two-phase frictional multiplier versus the Lockhart-Martinelli parameter (X) is presented.

Flow Pattern Transition in Pipes Using Data-Driven and Physics-Informed Machine Learning

2020 ◽  
Author(s):  
André M. Quintino ◽  
Davi L. L. N. da Rocha ◽  
Roberto Fonseca Jr. ◽  
Oscar M. H. Rodriguez
Keyword(s):  
Machine Learning ◽  
Experimental Data ◽  
Flow Pattern ◽  
Liquid Flow ◽  
Two Phase Flow ◽  
Data Driven ◽  
Phase Flow ◽  
Two Phase ◽  
Flow Pattern Transition ◽  
Gas Liquid Flow

Abstract Flow pattern is an important engineering design factor in two-phase flow in the chemical, nuclear and energy industries, given its effects on pressure drop, holdup, and heat and mass transfer. The prediction of two-phase flow patterns through phenomenological models is widely used in both industry and academy. In contrast, as more experimental data become available for gas-liquid flow in pipes, the use of data-driven models to predict flow-pattern transition, such as machine learning, has become more reliable. This type of heuristic modeling has a high demand for experimental data, which may not be available in some industrial applications. As a consequence, it may fail to deliver a sufficiently generalized transition prediction. Incorporation of physics in machine learning is being proposed as an alternative to improve prediction and also to reduce the demand for experimental data. This paper evaluates the use of hybrid-physics-data machine learning to predict gas-liquid flow-pattern transition in pipes. Random forest and artificial neural network are the chosen tools. A database of experiments available in the open literature was collected and is shared in this work. The performance of the proposed hybrid model is compared with phenomenological and data-driven machine learning models through confusion matrices and graphics. The results show improvement in prediction performance even with a low amount of data for training. The study also suggests that graphical comparison of flow-pttern transition boundaries provides better understanding of the performance of the models than the traditional metric

Behavior of the Two-Phase Gas-Liquid Flow at the Inlet of a Catalytic Reactor

2019 ◽  
Vol 19 (2) ◽  
pp. 123-131
Author(s):  
O. P. Klenov ◽  
A. S. Noskov
Keyword(s):  
Liquid Phase ◽  
Uniform Distribution ◽  
Liquid Flow ◽  
Two Phase Flow ◽  
Phase Flow ◽  
Catalytic Reactor ◽  
Two Phase ◽  
Gas Consumption ◽  
Flow Diagrams ◽  
Gas Liquid Flow

The work was aimed at studying the behavior of the two-phase gas-liquid flow at the inlet pipe of a catalytic reactor. Apart from the classical approach using literature flow diagrams, methods of computational hydrodynamics were used for 3D simulation of the space propagation of phases in the pipeline. The results obtained demonstrated non-uniform distribution of the liquid phase through the outlet section of the pipeline and the time-unsteady mass consumption of the liquid phase. The maximal peak consumptions were ca. 3 times as high as the average values. With the data on the flow diagrams, the CFD simulation demonstrated that variations in the gas consumption within the range under study do not cause changes in the behavior of the two-phase flow but an increase in the gas consumption results in smoothening of the non-uniform distribution of the liquid phase at the outlet pipe. The data on the flow behavior are necessary for designing catalytic reactors to provide uniform propagation of the two-phase flow over the catalyst bed, for example, hydrotreatment reactors used in refineries.

Numerical Simulation of the Gas-Liquid Flow in a Rotary Gas Separator

1998 ◽  
Vol 120 (1) ◽  
pp. 41-48 ◽  
Author(s):  
G. Lackner ◽  
F. J. S. Alhanati ◽  
S. A. Shirazi ◽  
D. R. Doty ◽  
Z. Schmidt
Keyword(s):  
Void Fraction ◽  
Liquid Flow ◽  
Two Phase Flow ◽  
Numerical Procedure ◽  
Phase Flow ◽  
Two Phase ◽  
Free Gas ◽  
Gas Separator ◽  
Gas Liquid Flow ◽  
Gas Void Fraction

The presence of free gas at the pump intake adversely affects the performance of an electrical submersible pump (ESP) system, often resulting in low efficiency and causing operational problems. One method of reducing the amount of free gas that the pump has to process is to install a rotary gas separator. The gas-liquid flow associated with the down hole installation of a rotary separator has been investigated to address its overall phase segregation performance. A mathematical model was developed to investigate factors contributing to gas-liquid separation and to determine the efficiency of the separator. The drift-flux approach was used to formulate this complex two-phase flow problem. The turbulent diffusivity was modeled by a two-layer mixing-length model and the relative velocity between phases was formulated based on published correlations for flows with similar characteristics. The well-known numerical procedure of Patankar-Spalding for single-phase flow computations was extended to this two-phase flow situation. Special discretization techniques were developed to obtain consistent results. Special under relaxation procedures were also developed to keep the gas void fraction in the interval [0, 1]. Predicted mixture velocity vectors and gas void fraction distribution for the two-phase flow inside the centrifuge are presented. The model’s predictions are compared to data gathered on a field scale experimental facility to support its invaluable capabilities as a design tool for ESP installations.

scholarly journals Evaluation of Mixture Viscosity Models in the Prediction of Two-phase Flow Pressure Drops

2012 ◽  
Vol 29 (2) ◽  
pp. 115 ◽  
Author(s):  
N.Z Aung ◽  
T Yuwono
Keyword(s):  
Experimental Data ◽  
Pressure Drop ◽  
Two Phase Flow ◽  
Phase Flow ◽  
Two Phase ◽  
Pressure Drops ◽  
Viscosity Models ◽  
Oil Water ◽  
Mixture Viscosity ◽  
Gas Liquid Flow

Nine existing mixture viscosity models were tested for predicting a two-phase pressure drop for oil-water flow and refrigerant (R.134a) flow. The predicted data calculated by using these mixture viscosity models were compared with experimental data. Predicted data from using one group of mixture viscosity models had a good agreement with the experimental data for oil-water two-phase flow. Another group of viscosity models was preferable for gas-liquid flow, but these models gave underestimated values with an error of about 50%. A new and more reliable mixture viscosity model was proposed for use in the prediction of pressure drop in gas-liquid two-phase flow.

Sign in / Sign up

Export Citation Format

Share Document