1

CFD Simulation of the GALLOP System Designed for Horizontal

Gas Well Deliquifaction

Nicolas Perez Bustillo 201327303

Chemical Engineering Department Universidad de los Andes

General Objective

To evaluate the GALLOP system design for liquid removal in horizontal gas wells

using Computational Fluid Dynamics (CFD).

Specific Objectives

• To assess the liquid removal performance of the GALLOP system using CFD.

• To analyze the flow patterns along the double pipe of the GALLOP system.

• To examine the pressure drop in the entire system.

Nomenclature

D Pipe diameter [m] H Liquid holdup

" Viscosity [Pa s] # Velocity [m/s]

$ Density [kg/m3] % Friction coefficient

& Void fraction ' Roughness [m]

∆) Cell length [m] t Time [s]

∆* Time step [s] + Specific gravity

P Pressure [Pa] Re Reynolds number

, Compressibility factor C Courant number

-.-/

Pressure gradient [Pa/m] 0 Molecular weight

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Abstract

This paper shows the study of a new artificial lift system, known as GALLOP, for

horizontal gas well deliquifaction using CFD software. To begin with, the casing is

filled with water coming from the reservoir due to changes in the inner pressure

causing the valves to open. Afterwards, gas is injected in the double pipe system in

order to expel the water accumulated. For the simulations there were three

conditions of gas injection considered and the system was initially assumed to be

completely full of water. A low, a mid, and high gas injection were included, being

30, 50 and 70 CFM, respectively. Additionally, the valves on the mandrel were

simulated both as open or closed. The simulations were conducted using STAR-

CCM+ v12.02 software with a VOF model (Volume of Fluid model). Also, due to

computational cost and results quality, a normal mesh was implemented. All

simulations showed that the gas was able to travel all the way through the system

but did not expel the water completely, mainly because of gravitational force and the

extended height of the vertical pipe. As it was expected, the highest injection rate

was able to reach the vertical outlet first and thus had the most stable void fraction.

Likewise, it was clear that the void fraction was more stable when the valves were

closed, indicating that the liquid was removed successfully. Additionally, all of the

injection rates showed a clear annular pattern in the horizontal piping. On the other

hand, the pressure drop for an injection of 30 CFM with closed valve was compared

to experimental data showing an error of 34.4 %, where more experimental data

must be conducted, a finer mesh, and more specialized mathematical model must

be implemented to achieve more accurate results. Lastly, the other two conditions

were compared using the non-slip model since there is no experimental data yet

available.

Keywords: CFD, GALLOP, artificial lift, VOF, multiphase flow, gas well, flow pattern.

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1. Introduction

In the oil and gas industry, multiphase flows of gas, solid particles and liquids are

commonly found. Multiphase flows are complex due to the simultaneous presence

of different substances and phases in the same stream. The combination of

experimental data and computational modelling has shown to improve the

understanding on the flow behavior of multiphase mixtures in pipelines (Tutkun,

N.D). A deep understanding of the effects of liquids produced by gas wells may have

a significant bearing on the economics of gas extraction (Hewitt, 2005). In this sense,

the aim of this research is to study the gas-liquid flow in a novel system for liquid

removal in gas wells.

1.1 Problem Statement

Gas wells, in the oil and gas industry, have a particular problem related to the

formation and accumulation of liquids along the pipes and reservoirs. Usually, the

condensation of hydrocarbons or water present in the reservoir matrix creates liquid

loading that complicate its operation (Turner et al, 1969). Every well has a certain

maturity after which it is no longer economically feasible to extract oil or gas. In this

sense, as the well matures and losses pressure, gases are not able to transport the

liquid phase to the surface, causing an accumulation of liquid in the bottom.

Shale formations are characterized by a low permeability that makes fluid

transportation from the formation to the wellbore difficult. Consequently, innovative

techniques must be used to increase the permeability. The most frequently used are

horizontal drilling and hydraulic drilling (Brito et al., 2016). Now, it must be noted that

horizontal does not necessarily mean that the wellbore is completely horizontal.

However, the inclination throughout the well may vary, resulting in toe up or toe down

trajectories, as well as more complex configurations with undulating profiles (Figure

1). Hence, these complex well configurations, along with the low gas production

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rates do not allow the water flow to maintain, causing water accumulation along the

horizontal section (Sarica, 2013).

Figure 1. Horizontal well trajectories. (a) Toe-down (b) Toe-up (c) One-undulation sump

(d) One-undulation hump. Adapted from Brito et al, 2016.

Recent developments in the oil and gas production technology has made the

process of deliquification much efficient by using novel lift techniques such as: gas

lift, plunger lift and foam lift. Plunger lift improves the gas production by taking

advantage of the energy of the reservoir to move a free piston that allows the gas to

pass through. On the other side, gas lift technology enhances the extraction process

by injecting gas, thus increasing the pressure in the wellbore. The foam lift method

reduces the density of the liquid phase by injecting foam and thereby, reducing the

hydrostatic pressure of the liquid column (Lea, 2008). Nonetheless, the multiple

kinds of trajectories along the horizontal wells, added to the rare flow patterns that

appear throughout the pipes, represent important challenges to the existing artificial

lift techniques.

This study focuses on a new artificial lift method called Gas Assisted Liquid

Oscillating Pressure (GALLOP). The GALLOP operates with a double pipe system,

compressed gas and two valves that open or close depending on the system’s

pressure (Figure 2). During the first stage, the outside pressure is larger than the

inside, resulting in the opening of the valves and allowing the fluids to enter the

double pipe. Afterwards, the valves close and compressed gas is injected in order

to remove liquids from the pipe. The gas injection process is carried out in multiple

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cycles, and as the liquids are removed, the pressure inside the wellbore decreases,

improving the production of the well. In this study, Computational Fluid Dynamics

(CFD) simulations were developed to study the flow patterns along the horizontal

and vertical sections of the double pipe system.

Figure 2. GALLOP artificial lift system. Adapted from Croce, 2016.

1.2 Literature Review

It must be noted that since the GALLOP system is a completely new design. There

are no previous studies about its functioning. Consequently, the following literature

review provides information about flow patterns along horizontal and vertical wells.

According to the simulations performed by Bahrami along inclined wells (Bahrami et

al., 2010), the three main flow regimes are: segregated, distributed and intermittent.

However, the maturity of the well is one of the conclusive factors in the type of flow

pattern. In consequence, studies have determined that during the life of the well

there are six intermediate types of flows related to the well’s pressure and fluids’

velocities. Throughout the beginning of the production, the well’s pressure and fluid’s

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velocities are at their maximum levels, resulting in a mist flow. Subsequently, both

the pressure and the velocity decrease as a function of time, causing a shift in the

flow regime to an annular flow, in which the liquid film flows around the walls and the

gas flows in the center of the pipe (Shoham, 2006). Afterwards, caused by a

significant decrease in the well’s pressure, slug flow, stratified wavy and stratified

flows appear. Finally, the well’s productive life comes to an end when the bubble

flow regime occurs.

Based on the above, the segregated pattern comprehends the stratified, wavy and

annular flows. This flow regime is characterized by a low flow rate, and its

development starts off with the liquid located at the bottom and the gas at the top

(stratified flow). Eventually, as the production level rises, a higher flow results in

undulations in the liquid phase resulting in a stratified wavy flow. Finally, at the

highest level of production, when the liquid and gas flow rates are at their maximum,

annular flow occurs.

On the other hand, intermittent regimes, such as plug and slug flow, might appear at

the higher flow levels. The plug flow forms gas bubbles inside the liquid phase, while

the latter only appears if the bubbles become large enough (Brennen, 2005). Finally,

there are two types of distributed flow patterns: the first one is characterized by the

formation of small gas bubbles inside the liquid phase, this is called bubble flow. The

latter appears only at high flow rates, and is defined by the formation of liquid

particles in the gas phase (Thome, 2007). It must be mentioned, if the pipe’s

inclination is greater than 70°, wavy and stratified patterns do not occur. In addition,

all of these are graphically shown in Figure 3 for horizontal pipes and in Figure 4 for

vertical ones.

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Figure 3. Flow patterns along horizontal pipes (Behrami et al.,2010).

Figure 4. Flow patterns along vertical pipes. (a) single phase liquid flow (b) bubbly flow (c)

slug flow (d) churn flow (e) annular flow (f) mist flow (N.A, 2013)

Finally, if more rigorousness is required, the void fraction and the pressure drop

should be included as the analyzed variables. This is because of the high correlation

between these two quantities and the velocity of the fluid. In addition, if a lower

amount of gas is present in the pipe, the lower the pressure of the system. Therefore,

the void fraction and the pressure drop play a significant role in the determination of

the flow regime in the pipe. In this sense, these two variables will help to achieve a

higher level of accuracy in the CFD model. The void fraction is the ratio between the

volume of the gas and the volume of the pipe's section (Shoham, 2006).

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1.3 State of the art

In Table 1, a thorough examination of previous CFD studies on artificial lift and flow

along horizontal and vertical wells can be found.

Table 1. CFD Researches

Author Orientation Fluids Model Objective Comparison

Bahrami et

al. (2010)

Horizontal

- Inclined

Air-water

Multiphase:

VOF (Volume

of Fluid)

Multiphase flow

modeling in

horizontal deviated

wells and velocity

profile analysis.

Experimental

Zeboudj et

al. (2010) Horizontal

Incompressible

Newtonian

fluid

Turbulence:

1 − ' model

Single phase flow

in horizontal well

for velocity and

pressure profile

analysis.

Correlation

Longfellow

et al. (2014) Horizontal

Air

Turbulence:

1 − ' model

Plunger lift

modeling for

horizontal wells.

Experimental

Dabirian et

al. (2015) Horizontal

Air-water

Turbulence:

1 − ' model

Multiphase:

VOF

Simulation of

turbulent flow

structure in

stratified gas/liquid

flow.

Experimental

Ejim et al.

(2016) Horizontal

Air-oil

Turbulence:

1 − ' model

Multiphase:

homogeneous

multiphase

Gerotor pump

simulation

designed for single

and multiphase

flow system inside

wells.

Experimental

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2. Materials and Methods

2.1 Experimental facility

The engineering department of the Colorado School of Mines, located in Denver,

Colorado (United States), is in the process of building an experimental facility to

model the GALLOP performance inside a well. Given that the facility is still under

construction, few tests have been performed, thus there are little experimental data

on this matter. The experimental facility of the GALLOP system is shown in Figure

5.

Figure 5. Experimental facility (Iglesias, 2017, Croce, 2017)

Now, as shown in Figure 5, the system is enclosed with a casing that emulates the

wellbore. The casing is made of PVC crystal pipe, which has a length of 3.23 m and

an internal diameter of 0.01016 m. This is connected to a water injection system that

emulates the entrance of water from the reservoir into the well. Inside the casing

there are two PVC pipes, one used for production and the other for injection. Each

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pipe has a diameter of 0.00191 m. These two sections are connected through a

15.64 m long hose.

In addition to this, the PVC pipe from the vertical section has a length of 12.5 m with

the same diameter as the production and injection pipes. This is connected to a

discharge tank that recirculates the water to the water injection pipe. Finally, there

are three high definition cameras, six pressure transducers and two flowmeters, one

to measure the flow of water entering the casing and the other one connected to the

gas injection line.

2.2 Experimental conditions

First of all, the same gas flow rates as the one used by Iglesias (Iglesias, 2017) will

be implemented. The minimum, medium, and maximum gas flow rates used to

simulate the liquid removal from the double pipe will be 30, 50, and 70 CFM,

respectively. Additionally, both the gas density and viscosity were calculated using

the real gas law, where the compressibility factor was obtained from (Perry, 1984),

and Lee correlation (Annex A). Finally, the temperature considered for each gas flow

was 18 ºC.The other experimental conditions are shown in Table 2.

Table 2. Experimental conditions Low gas flow rate

(30 CFM) Medium gas flow

rate (50 CFM) High gas flow rate

(70 CFM)

Pressure [Bar] 3.103 4.481 5.861

Density [kg/m3] 2.449 3.274 4.098

Viscosity [Pa s] 1.816 x10-5 1.812 x10-5 1.818 x10-5

Volumetric flow [m3/s] 0.014 0.024 0.033

Velocity [m/s] 49.609 82.683 115.756

Reynolds Number 127529 284170 497395

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2.3 CFD simulation

In order to model the GALLOP system, the process was divided in three stages, pre-

processing, processing and post-processing. During the pre-processing stage the

geometry was defined and built with the parameters that were given before.

Additionally, the mathematical models were also determined, as were the

boundaries and initial conditions. All of this was achieved by the use of the CFD

program STAR CCM+ v12.02 (Siemens, Germany).

2.3.1 Geometry

The geometry was designed and built on Autodesk Inventor Professional v2015

(Autodesk, United States). The geometry was based on the lengths and diameters

given in section 2.1. The valves were configured as open or closed. Finally, the balls

inside the mandrel were not modeled.

Figure 6.CFD model Geometry. Adapted from Iglesias, 2017.

Additionally, four monitors were placed along the geometry in order to evaluate the

performance of the system. These monitors were placed at the the inlet of the gas

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and production section and at the outlet of the injection and production section. This

is shown in Figure 7.

Figure 7.CFD model Geometry monitors – top view. (Iglesias, 2017)

Likewise, another monitor was placed at the end of the vertical section. This was

implemented in order to measure the pressure drop in this section.

2.3.2 Mathematical models

2.3.2.1 7 − 8 Turbulence model

The turbulence model must be used whenever there is turbulent flow present in the

system. As it is shown in Table 2, all flows -low, medium, and high- showed a strong

turbulent behavior. Taking this into account, it was necessary to include a turbulence

model.

The turbulence model selected for this case study was the 1 − 9 model. It was

selected given its good computational cost in relation to its accuracy and robustness.

This model solves two equations, one regarding the turbulent kinetic energy and the

other one solves the turbulent kinetic energy dissipation rate (Siemens, 2016).

2.3.2.2 Volume of fluid model

The volume of fluid (VOF), model is used to simulate flows of immiscible fluids. This

model is capable of solving equations of the interface between each phase of the

mixture. It requires the grid cells, developed to solve the equations, to be smaller

than the phases particles (Siemens, 2016). In addition to this, the VOF model tracks

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the volume of every fluid throughout the entire system and solves momentum

equations.

Equations 1 to 4 solve the properties of the fluids as a function of the volume fraction.

On the other hand, Equation 5 describes the transport of volume fraction.

$ = $;&;;

(1)

" = ";&;;

(2)

<= =<=;$;$

;

(3)

&; =>;>

(4)

--* &;-> + &; @ − @A ∗ -C

DE

D;=

FE

F;(HI; −

&;$;

FE

F;

J$;J* )

(5)

2.4 Boundary conditions

Initially the system was configured to be filled with liquid in order to model the

displacement of this fluid as the gas was injected. The inlet of gas was set as a mass

flow boundary condition with a void fraction of one. On the other hand, the outlet of

the fluid from the double pipe located at the top of the vertical section was set as a

pressure boundary condition. In this case the pressure was presumed to be equal to

the atmospheric pressure. Lastly, the intersection of the valves chambers with the

casing were set as a contact interface or as a wall interface, this was determined

based on the case. It is important to mention that the valves were modeled as open

and closed in both cases. In Figure 8 it is shown, in pink, where the boundary

conditions were placed more precisely.

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(a) (b) (c)

Figure 8. Boundary conditions (a) Mass flow inlet (b) Vertical pipe pressure outlet (c)

Valves gates set as open or closed. (Iglesias, 2017)

2.5 Mesh

The mesh represents the discretization of the volume into cells. A volumetric mesh

discretizes the interior object to solve the equations of the model in each cell. As the

volume is discretized in smaller and more cells, the results become more exact.

However, the computational cost also increases. There are several ways in which a

geometry can be divided into cells. For the present study, the polyhedral and the

prism layer mesher were selected. The prism layer generates a special condition

near the walls to solve the boundary layer equations. Polyhedral mesher produce

accurate solutions using arbitrary polyhedral cell shapes (Siemens, 2016). Two

meshes were generated; one for the casing, and one for the double pipe system.

(Iglesias, 2017)

Figure 9. Geometry mesh- top view

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2.6 Stability constraint

In order to ensure that the mathematical solutions are precise, it is necessary to add

constraints to the time step size. It is necessary to guarantee that fluid does not jump

to the adjacent cell in the following time step (Abdulkadir, 2011). Taking this into

account, the convective Courant number was applied to analyze the constraint was

fulfilled, as shown in Equation 6.

< = # ∗∆*∆)

(6)

Where < is the Courant number, # is the phase velocity, ∆* the time step and ∆) the

cell’s width. To guarantee the fluid is moving through adjacent cells, the convective

Courant number should be lower than 1 (Abdulkadir, 2011). Therefore, a 5E-5

second time step was selected for all flows in order to fulfill the condition mentioned

previously.

2.7 Mesh independency study

It is important to implement an ideal mesh in order to achieve precise results with a

low computational cost. Given this, the mesh independency study is used to establish

the minimum mesh density where any mesh refinement would show insignificant

changes in the solution (Iglesias, 2017). Therefore, generating more cells would not

change the resulting flow (Abdulkadir, 2011). The base mesh was set at 1,125,131

cells. The fine mesh was set at 30 % more than the base and the coarse mesh 30 %

less. Thus, the fine mesh generated 1,462,670 cells, while the coarse mesh generated

787,591 cells.

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Figure 10. Geometry fine mesh- top view

Figure 11. Geometry coarse mesh- top view

3. Results

In this section the results obtained during the simulations will be discussed. First,

there will be a comparison with the results obtained by Iglesias (Iglesias, 2017), such

as, the flow pattern inside the pipe, the void fraction and the pressure drop.

Additionally, a mesh independency study will be included in order to verify the

results. Also, the analysis of the pressure drop will be conducted taking into the

account the whole system, which means the vertical section will be included. In

addition to this, most of the analysis will be made on the 30 CFM closed simulation

given that at this condition there are several experimental data available.

Now, it is important to mention that all the simulations converged properly and that

the reports show logical results. The residuals showed stability throughout all the

simulations, confirming what was previously mentioned.

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3.1 Mesh independency study

The mesh independency study was conducted as a form of verifying the results. This

was experimented on the 70 CFM simulation. The computer used to run the

simulations had a 9-core processor and 36 GB of RAM. In order to be able to

compare the results, the computational time it took the gas to reach the vertical outlet

monitor was recorded. The results are shown in table 3.

Table 3. Mesh independency study

Mesh Fine Normal Coarse

Number of cells 1,462,670 1,125,131 787,591

Computational time [h] 748 624 486

Displacement time [s] 1.61 1.52 1.13

Error [%] 0 5.59 29.81

Also, the error was calculated to be able to compare the performance of the three

meshes. This was calculated using equation 7.

LMMNM % = PQRSTUPSVWXYZ/\VYW]T

PQRST∗ 100 (7)

In terms of computational time there is a significant difference between each mesh,

over a 100-hour difference is observed. In terms of results, the difference between

the normal and the fine mesh is very low. On the other hand, the difference between

the coarse and the fine mesh is rather significant, well an error of approximately 30

% was reported. Therefore, it was concluded that the normal mesh presents

appropriate results with suitable computational costs.

The results obtained show a high similarity with Iglesias (2017). Evidently, the

computational time and the displacement time are significantly higher given that the

length of the piping is 10 meters longer. However, the errors obtained are similar

and therefore the normal mesh allows an excellent approximation of the results.

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3.2 Flow pattern

In Figures 12 and 13 the injection of the gas is shown. More specifically, Figure 12

shows the displacement of the liquid with an open valve, where it is shown that gas

enters the casing. On the other hand, Figure 13 shows the displacement of the liquid

with a closed valve. From these, it is important to mention that the gas clearly

reached the furthest part of the vertical pipe. However, the liquid was not fully

displaced and therefore there are sections in the vertical pipe which show small

portions of water. The flow pattern in this section shows a churn flow. As a solution

to this, more computational time is suggested to ensure that the water if fully

expelled. However, these results are logical given the large length of the system and

to the force of gravity acting opposite to the fluids flow.

Figure 12. Void fraction longitudinal section view (a) 30 CFM Open (b) 50 CFM Open (c)

70 CFM Open (Volume fraction of air: 0 [blue] - 1 [red])

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Figure 13. Void fraction longitudinal section view (a) 30 CFM Closed (b) 50 CFM Closed

(c) 70 CFM Closed (Volume fraction of air: 0 [blue] - 1 [red])

Now, to be able to observe and determine the horizontal flow pattern it is necessary

to perform a zoom on the beginning of the vertical section. For this, only the

simulations with closed valve will be analyzed. The results are shown in Figure 14.

Figure 14. Void fraction cross section view (a) 30 CFM Closed (b) 50 CFM Closed (c) 70

CFM Closed

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In Figure 14 it is observed that an annular flow pattern is formed as the gas displaces

the liquid. In addition to this, in the cross section view the layer around the wall

becomes thinner as the velocity of the injection increases. However, the layer formed

with a 30 CFM injection is still considerably small. It is also important to mention that

the pictures were taken from an early stage, where the gas had only ejected a small

part of the liquid. In addition to this, the analysis was made from the point of injection.

The results obtained validate the work from Iglesias 2017, where the flow pattern

also showed an annular flow pattern. Additionally, the layer of voided air got thinner

as the flow velocity rose.

3.3 Void fraction

The void fraction was measured in the five sensores that were mentioned in section

2.3.1. These were placed in the right inlet, left inlet, left contact, right contact, and

vertical outlet. Figure 15 shows the computational time it took the gas to reach each

monitor. The high fluctuation shown at the begging of each line indicates the

presence of both phases. Likewise, the lines begin to stabilize when the gas

displaces the liquid, meaning that when the line is completely horizontally all the

liquid from the section has been displaced. As it is shown in Figure 15, the void

fraction at the vertical outlet does not stabilize completely at any moment, confirming

that the liquid was not fully displaced. This indicates that the computational time was

not enough to achieve this. Consequently, the vertical outlet will be used to compare

each condition.

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Figure 15. Void fraction 30 CFM Closed

Now, Figure 16 shows the change of void fraction for the three flow rates for the

open and closed condition. As expected, the highest flow rate reached the vertical

outlet first. Likewise, the lowest flow rate reached the monitor last. In addition to this,

it is clear that void fraction is highly more stable as the flow increases given that the

fluctuation is considerably smaller , meaning that the gas displaces more efficiently

the liquid. However, it does not stabilize completely, indicating that again the

computational time was not enough.

On the other hand, open valves showed higher fluctuations. This is logical given that

part of the gas goes into the casing implicating that there will be less gas to displace

the liquid. Taking this into account, the efficiency of the system decreases when the

valves are not closed.

0

0,1

0,2

0,3

0,4

0,5

0,6

0,7

0,8

0,9

1

0,00 0,50 1,00 1,50 2,00

Voidfractio

n

Time(s)AirFraction- Closed30CFMRightInlet AirFraction- Closed30CFMRightContactAirFraction- Closed30CFMLeftContact AirFraction- Closed30CFMLeftOutletAirFraction- Closed30CFMVerticalOutlet

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Figure 16. Void fraction Closed/Open

3.4 Pressure drop

First, it is important to mention that there are only experimental results for the 30

CFM closed simulation. Therefore, at this condition the pressure drop obtained

from the simulation was compared with the experimental data. On the other hand,

for the rest of the conditions, the no-slip model equations were used (Shoham,

2006). These equations require calculating the average fluid properties using no-

slip liquid holdup for a concurrent flow. Since for this study, the gas is displacing

the liquid, average fluid properties cannot be determined. Therefore, two

pressure drops will be computed in order to compare them with the results. One

will be assuming only the liquid moving along the pipe, and the other, only the

gas (Iglesias, 2017). In annex B a more detailed explanation is given for this

matter. It is important to mention that the acceleration component was considered

as negligible when the pressure drop of the liquid was computed. Also, the

pressure drop was measured from the moment it entered the pipe system until it

finally was expelled from the vertical outlet.

The results and comparison between the experimental and simulated data is

shown in table 4. The error was calculated using Equation 8. An error of 34.34

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% was obtained between the simulations and the experimental data.

Furthermore, the pressure drop shown included the vertical and thus the

gravitational component implied. It is not possible to determine whether the error

obtained is in the experimental data or in the simulated ones. As a solution to

this, conducting more experimental trials in this matter is suggested. Additionally,

providing a finer mesh and a more thorough and specialized mathematical model

would guarantee more exact results. However, given the early stage of the

experimentation this is considered a positive result.

_MMNM % = `a`bcQd

U`a`befgTWRXTShYZ`a`befgTWRXTShYZ

∗ 100 (8)

Table 4. Experimental and simulated pressure drop

30 CFM dP/dL CFD [Pa/m] 98762

dP/dL Experimental [Pa/m] 73469 Error [%] 34.43

On the other hand, the results for the remaining conditions and the ones calculated

with the non-slip equation are shown in table 5. As it is shown, the pressure drop

from the simulations are similar to the ones computed for the water, presenting errors

between 9 and 15 %. Additionally, taking into the account that the system is initially

filled with water the pressure calculated has to be larger than the one simulated, well

as the gas displaces the liquid the pressure drop will decrease. However, once there

are experimental data in this matter it will be possible to conduct a more thorough

and complete analysis.

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Table 5. Pressure drop simulations and non-slip equations

50 CFM 70 CFM dP/dL CFD [Pa/m] 158764 211658

dP/dL Equations - Water [Pa/m] 174562 243564 dP/dL Equations - Air [Pa/m] 634 1232

Error CFD – Water [%] 9.95 15.07

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4. Conclusions

The present study was elaborated in order to evaluate the performance of the

GALLOP system that is under construction in the University of Mines, Denver,

Colorado (United States), with the use of CFD’s simulations conducted in STAR

CCM+ v.12.02. For this, the system was initially assumed to be full of water and

three different gas injection rates were used to simulate the expulsion of the liquid.

The three rates studied were 30, 50, and 70 CFM.

Firstly, it is important to mention that there are only experimental data available to

the date on the 30 CFM gas flow rate. Through a mesh independency study, it was

determined that, due to the quality of the results obtained and computational costs,

the normal mesh was the best option. During all experimental conditions the gas

reached the vertical outlet of the system. However, the liquid was not fully expelled

in any of the flow rates. This was mainly due to the extended length of the system of

the vertical piping and to the opposed force that gravity forced on to the up flowing

flow of the multiphase mixture.

Additionally, in all of the injections an annular pattern was observed in the horizontal

flow and a churn pattern was observed in the vertical flow. The liquid surrounding

the wall was observed to get thinner as the flow rate increased, and therefore the

gas occupied a larger section of the tube. Also, it was observed that at the highest

flow rate the gas reached the vertical outlet first and a more stable void fraction was

reached, indicating that a larger portion of water was expelled. Likewise, when the

valves were simulated as closed the void fraction was also more stable and the gas

expelled the water more rapidly, thus increasing the efficiency of the system.

On the other hand, the pressure drop analysis on the 30 CFM closed condition

showed a 34% error between the experimental and the simulated result. Considering

the early stage of experimentation this is considered as a positive result. Meanwhile,

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the other conditions compared using the no-slip model showed errors between 9 and

15 % when using a system full of water.

Also, it is important to mention that other experimental conditions have proven to

achieve better results at injection rates of 3.5, 7, and 15 CFM. However, these results

were obtained after the initiation of this project. Therefore, an analysis was not made

on these conditions. Finally, in order to obtain more precise results, further

experimental tests must be performed, just like implementing a finer mesh and more

specialized mathematical models in the simulations on the conditions that

experimentally have proven to be the best.

27

References

Brennen, C. E. (2005). Fundamentals of multiphase flow. Cambridge: Cambridge University Press. Bahrami, H., Hosseinian, A., Rasouli, V., Siavoshi, J., Mirabolghasemi, M., Sinanan, B., & Bagherian, B. (2010). Prediction of Downhole Flow Regimes in Deviated Horizontal Wells for Production Log Interpretation. Proceedings of Trinidad and Tobago Energy Resources Conference. Dabirian, R., Mansouri, A., Mohan, R., Shoham, O., & Kouba, G. (2015). CFD Simulation of Turbulent Flow Structure in Stratified Gas/Liquid Flow and Validation with Experimental Data. SPE Annual Technical Conference and Exhibition. Ejim, C. E., Oshinowo, L., & Xiao, J. (2016). Gerotor Pump Performance in Artificial Lift for Single-Phase and Multiphase Conditions. Abu Dhabi International Petroleum Exhibition & Conference. Hewitt,G. F.(2005). Three-phase gas-liquid-liquid flows in the steady and transient states. Nuclear Engineering and Design, vol. 235, 1303-1316. Longfellow, N., & Green, D. (2014). Computational Fluid Dynamics for Horizontal Well Plunger Lift System Design. SPE Western North American and Rocky Mountain Joint Meeting. Shoham, O. (2006). Mechanistic modeling of gas-liquid two-phase flow in pipes. Richardson, TX: Society of Petroleum Engineers. Thome, J. R. (2007). Engineering Data Book III. Lausanne: Wolverine Tube Inc. Tutkun, M. (N.D). Multiphase pipe flow- a key technology for oil and gas production. Institute for Energy and University of Oslo.

Croce, D. (2016, October 18). GALLOP – Novel Artificial Lift System to Improve

Liquid Removal. Lecture, Colorado.

Abdulkadir, M. (August de 2011). Studies of Gas-Liquid Flow in Bends.�

Perry, J. H. (1984). Chemical engineering handbook. S.l.: S.n.

Siemens. (2016). STAR-CCM+ Documentation.�

Iglesias, M. (2017). CFD Simulation of the GALLOP System Designed for Horizontal Gas Well Deliquifaction. Undergraduate Thesis. Bogota.

28

N.A. (2013). Flow regimes in horizontal and vertical pipes. [Online]. Available at: http://www.ingenieriadepetroleo.com/flow-regimes-in-horizontal-and-vertical-pipes/

29

Annexes

Annex A. Gas density and gas viscosity equations

In order to calculate the air density at the specific conditions of temperature and pressure in

which the system was working it was necessary to use the following equations and

correlations.

$i;j =2.7 ∗ l ∗ +A, ∗ (m + 460)

Where , is the compressibility factor, l the pressure (psi), m the temperature (ºF) and +A the

specific gravity.

In addition to this, the lee correlation that was mentioned in section 2.2 is shown next,

"A = p ∗ 10Uq ∗ exp u ∗ 0.0433+A ∗l

, ∗ m + 460

v

p =9.4 + 0.020A ∗ m + 460 x,z

209 + 190A + (m + 460)

u = 3.5 +986

m + 460+ 0.010A

} = 2.4 − 0.2u

Where 0Ais the molecular weight of the gas (28.967 g/mol) and "A the viscosity (cP).

Annex B. No- slip pressure drop equations

In this section the equations and correlations that were used to calculate and deduct the

pressure drop in the system are shown (Iglesias,2017).

• Frictional component

−-.-/~

=2J∗ %~ ∗ $�D ∗ @ÄÅ =

2J∗ %~ ∗

ÇÅ

$�D

• Gravity component

−-.-/É

= $�D ∗ Ñ ∗ ÖÜáà

• Acceleration component

30

−-.-/â

= ÇÅ ∗--/

1$�D

−ÇÅ

$�D∗1ä=

∗-ä=-/

$�D = $ã ∗ åã + $É ∗ 1 − åã

• Haaland Friction factor equation

1

%~xÅ= −1.8 ∗ çNÑ

6.9é_

+'-3.7

x.xx