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VALIDATION AND IMPROVEMENT OF SPPS IN LOW LIQUID LOADING AND ANNULAR FLOW XIV-1

November 2011

XIV. VALIDATION AND IMPROVEMENT OF SPPS IN LOW LIQUID LOADING AND ANNULAR FLOW

Introduction

Solid particle erosion of piping and fittings is caused as a result of entrained sand particles in the flow impacting the inner surface of pipe. This is one of the major concerns in the oil and gas industry. Every year the oil and gas industry suffers the loss of several million dollars in the form of loss in production and repair costs. Solid particle erosion occurs due to entrained sand particles in the flow crossing streamlines and impinging on the inner surfaces of pipes, fittings and other components. Certain components that redirect the flow such as pipe elbows, T-joints and other components are more susceptible to erosion damage. In order to minimize the damage due to this phenomenon, investigators at the Erosion/Corrosion Research Center (E/CRC) are working on developing more accurate models for sand erosion prediction.

Prediction of erosion in multiphase flow is a complex problem due to lack of accurate models for calculating particle impact velocities that cause erosion. The particle impact velocity is affected by the pipe geometry, carrying fluid velocity, flow pattern, particle size and distribution in the flow. The complexity of erosion prediction increases significantly for two-phase flow in elbows because of complicated flow patterns that occur when both liquid and gas are present in the flow. Among different flow patterns in horizontal and vertical flows, severe erosion is most severe when particles are transported in gas dominant systems such as low liquid loading gas and annular flows. Recent experiments have shown that for annular flows erosion does not consistently decreases with an increase in liquid rate for a given gas rate.

For application in a number of industries, from compact heat exchangers to large diameter deep-water risers in hydrocarbon production, extension of the current knowledge on gas/liquid flows in a wider range of pipe diameter is necessary. In oil and gas industry, with the increase of demand and major discoveries of hydrocarbon fields becoming rarer in the conventional offshore the deeper water exploration is emerging. Risers employed for deep water are normally operated under friction dominant conditions. To minimize pressure losses, risers tend to be of diameters larger than those for which both multiphase flow and erosion research data are available [1]. It has been recognized [2] that gas/liquid flow in such larger diameter pipes is different from that in smaller pipes.

In many industrial applications such as heat exchangers, process equipment and oil and gas industry it is important to be able to predict pressure drop, friction and heat transfer

VII-2 EROSION/CORROSION RESEARCH CENTER

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in various pipe sizes. In the oil and gas industry, because of large transport pipelines, it is important to have a good understanding of multiphase flow in larger diameter pipes. Also, for predicting erosion, it is important to be able to calculate particle impact velocities in larger diameter pipes. Therefore it is essential to have a better understanding of multiphase flow in various pipe fittings in order to predict erosion. Furthermore, experiments conducted at Tulsa University Sand Management Projects (TUSMP) have shown that flow orientations impact the severity of erosion in annular flows.

The Erosion/Corrosion Research Center (E/CRC) and The Tulsa University Sand Management Projects (TUSMP) have years of experience in erosion prediction and sand detection. The investigators at E/CRC have developed several simplified mechanistic models to predict metal loss rate. One of the most prominent models is in the form of Sand Production Pipe Saver (SPPS) computer program developed at E/CRC to predict material loss caused by sand impacts for different conditions. Erosion data collected from Harwell, DNV as well as the University of Tulsa E/CRC and TUSMP served as erosion data bank for modeling work. The SPPS extension for multiphase flows was developed based on limited data for 1” and 2” pipe diameters. However, some recent measurements collected at TUSMP for larger diameter pipes indicate that the SPPS model must be validated and improved. The main goal of this research is to collect additional data in multiphase annular and low liquid loading regimes and develop a more accurate extension of the SPPS procedures that more accurately accounts for the physics of multiphase flows for gas dominants flows and the effect of pipe size and pipe orientation on the severity of the amount of erosion.

Objective and Approach

The primary objective of this research is to investigate erosion behavior under gas dominant multiphase flows. Additional experiments will be conducted in multiphase annular flow and low liquid flow conditions. In addition, using new empirical data that will be gathered at E/CRC for low liquid loading and annular flows conditions and new developments in erosion calculation for different oilfield materials, the results of this investigation will be applied to validate and improve the E/CRC erosion prediction model (SPPS), thus making SPPS more reliable for predicting erosion in larger diameter pipes and different pipe flow orientations.


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Background and Literature Review

Background of Gas Dominant Flows

Low-liquid loading and annular gas-liquid flow conditions are commonly encountered in gas transportation pipelines. They may also occur in other production facilities as gas/condensate production systems where the liquid phase flows partly as a wavy film along the pipe circumference, and partly as entrained droplets in the turbulent gas core.

A typical gas/condensate production system contains mainly methane (CH4) and propane in addition to impurities such as ionic formation water, CO2 and H2S. Also, unconsolidated and partially consolidate wells contain sand that can cause erosion. In addition, provided the wall is wetted by corrosive water, the presence of small quantities of sand and CO2 could result in erosion-corrosion of production equipment. The presence of small quantities of sand particles will normally not alter the global flow conditions significantly, but could by interaction with the confining walls result in erosion and erosion-corrosion. Experience gained from production of hydrocarbons has shown that severe degradation of production equipment may occur under erosion-corrosion conditions.

Sand erosion in multiphase flows with entrained sand is a complex phenomenon. There are many issues that remain unanswered. The severity of erosion depends on a multitude of factors such as fluid properties, flow rate, sand size and rate, material type, geometry as well as many others. However, trying to isolate the effect of one of these factors and making the findings applicable to a wide range of conditions is challenging. One factor that affects the severity of erosion that has not been addressed directly in literature but has been observed experimentally is the pipe orientation, horizontal or vertical. A semi-mechanistic erosion prediction procedure (SPPS) was previously created by E/CRC. The SPPS extension for multiphase flows was developed based on limited data for 1” and 2” pipe diameters. Experiments have shown that pipe size and flow orientation impact the severity of erosion in annular and low liquid loading flows. Also, the current version of SPPS is for vertical orientation only.

It becomes necessary to develop an extension of the current mechanistic model procedures that account for:

• Physics of low-liquid loading and annular multiphase flows. • Effect of pipe size and flow orientation on the severity of sand erosion.


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Annular flow and low liquid loading flow regimes are the most common flow patterns encountered in natural gas wellbores and pipelines. They occur under conditions of high gas flow rates and very low to medium liquid flow rates. The liquid flows as a film around the pipe inner wall, surrounding a high velocity core, which may contain entrained liquid droplets. The interface between the gas core and the liquid film is very wavy, and atomization and deposition of liquid droplets occur through this interface. Most of the experimental and theoretical studies on annular flow have been carried out either for vertical or for horizontal conditions. Changes in the physical phenomena occur as the inclination angle varies from vertical through inclined to horizontal flow conditions. Under vertical flow conditions, the time-average liquid film distribution is nearly uniform around the pipe inner periphery. As the pipe is inclined from the vertical to off vertical, the film thickness distribution becomes non-uniform. Due to gravity, the liquid phase tends to accumulate at the bottom part of the pipe. This results in a thicker film at the bottom and a thinner film at the top. The non-uniform film thickness distribution becomes more and more pronounced as the pipe inclination angle approaches horizontal. This phenomenon has a significant effect on the liquid holdup and pressure drop in the system and must be accounted for in order to enable proper design of pipelines, wellbores, and separation facilities.

The following is a brief representation of the pertinent literature for annular flow in vertical and horizontal pipes:

For vertical flow, Wallis [3] and Hewitt and Hall-Taylor [4] presented general discussions of annular flow. Earlier models for annular flow were developed by Dukler [5] and Hewitt.[6] Other models have been published by Hasan and Kabir [7], Yao and Sylvester [8], Oliemans et al.[9], Caetano [10] and Alves et al.[11]. The physical mechanisms associated with annular flow have also been studied extensively. Turner et al. [12] and Ilobi and Ikoku [13] studied the minimum gas velocity required for liquid removal from vertical gas wells. Wallis [3], Henstock and Hanratty [14], Whalley and Hewitt [15] and Asali et al. [16] developed interfacial shear stress correlations. The entrainment process was studied by Hanratty and Asali [17], Schadel et al. [18] and Whalley and Hewitt [15].

For horizontal flow, measurements of the circumferential film thickness distribution were reported by McManus [19], Butterworth [20] and Fisher and Pearce [21]. Experimental data on film thickness distribution and pressure drop were acquired by Dallman [22], Laurinat [23] and Laurinat et al. [24]. In a later study, Laurinat et al. [25] developed a model for film thickness distribution. Jepson [26] evaluated the proposed model and found it suitable for use in large diameter pipes. Williams [27] conducted comprehensive studies on the effect of pipe diameter on annular flow in horizontal pipes. Annular flow in small diameter pipes was studied by Luninski et al. [28].


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Previous Erosion Models for Gas Dominant Systems

A variety of erosion prediction models are available in literature. Representatively, the Erosion Corrosion Research Center (E/CRC) at The University of Tulsa has been developing and improving the program Sand Production Pipe Saver (SPPS) which is capable of predicting the maximum sand penetration in single and multiphase flow for multiple oil field geometries including elbow, tee, and straight pipe. E/CRC has also developed a Computational Fluid Dynamics (CFD) based erosion prediction procedure with which the erosion in arbitrary geometries can be calculated in single-phase flow. A review of the previous studies and efforts done to characterize erosion profile in elbow are presented.

Bourgoyne [29] collected experimental data in various fittings for gas/liquid annular-mist flow and provided recommendations for values of specific erosion factor in his erosion prediction model. Salama [30] reported the data obtained by Det Norske Veritas (DNV) in elbows for a broad range of flow regimes including bubbly flow, slug flow, and annular flow. Salama also proposed an empirical correlation that accounts for mixture fluid properties of multiphase flow as an alternative of API RP 14E [31]:

WdSV m

e

ρ= (XIV-1)

where eV is the erosional velocity limit; S is an empirical constant; D is pipe diameter; mρ

is the fluid mixture density; and W is sand production rate. The models proposed by Bourgoyne [29] and Salama [30] share the advantage of simplicity as well as the weakness of trying to reflect the multiphase flow effect by using a simple empirical coefficient. More recently, Mazumder [32] at E/CRC presented a mechanistic model for annular flow that was grounded on previous models that were based on mixture properties for multiphase flows. McLaury et al. [33] refined the annular flow erosion model by accounting for 2-D particle tracking through the annular film. Erosion Prediction for Annular Flow

McLaury et al. [33] developed an annular flow erosion model that accounted for the flow pattern and flow orientation. In the model, the erosion is assumed to result from both particles in the core and in the liquid film and separate calculations are performed for each.


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Models from literature to predict liquid film thickness and entrained fraction are incorporated in the erosion calculation procedure.

Based on experimental results obtained by Santos [34] in a 1” pipe, the model also assumes that sand is uniformly distributed in the liquid for sand concentration in annular flow. The model determines the erosion damage caused by particles in both regions and sums them to determine the total amount of erosion. Particles in the liquid film

The particles traveling in the gas core must pass through the gas core and the liquid film before impacting the wall, so two different particle track routines are used to determine the representative impact velocity.

The original form of the model [35] is applied to examine the motion of the particle through the gas core. In order to apply the original model, the following parameters must be known: stagnation length, characteristic velocity, fluid density and viscosity.

The stagnation length is calculated based on the relation for the original model using the inner diameter of the pipe.

The characteristic velocity is a function of the average velocity of the gas velocity in the gas core. This is calculated [36] using the following Equation:

2

2 ⎥⎦⎤

⎢⎣⎡

−=

δddVV SGG (XIV-2)

where SGV is the superficial gas velocity, d is the inner diameter of the pipe, δ is the film

thickness. Particles in the gas core

The initial velocity of the particle entering the liquid film is assumed to be the particle velocity calculated at the intersection between the gas core and the liquid film calculated in the previous particle tracking routine.

The average film velocity is calculated by:

( )( )δδ −−

=ddEVV SLFilm 4

1 2

(XIV-3)


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Entrainment fraction calculation

Many models have been employed to predict the entrainment fraction ( )E in sand

erosion prediction models. Mazumder [32] used the correlation developed by Ishii and Mishima [37]. The entrainment liquid fraction is predicted as follows:

( )25.025.17 ReWe1025.7tanh LE −×= (XIV-4)

where the Weber number We and the liquid Reynolds number LRe .

Nakazatomi and Sekoguchi [38] investigated the pressure effects on the entrainment flow rates in vertical gas-annular annular two-phase flow. Cross sectional entrainment flow rates were measured using isokinetic probe method. They found that the behavior of cross-sectional entrainment flow rate profiles is divided into low and high-pressure regions. Two different correlations for different operating pressure ranges were proposed. For operating pressure in the range of 0.12 MPa to 5.0 MPa the entrainment liquid fraction is predicted as:

( )ba nFrE −−×= 5.14 WeC101tanh (XIV-5)

where the Weber number (We ) and the Froude number (Fr ) are defined as:

σρ dVSL

2LWe = ;

dgSGVFr = (XIV-6)

while the parameters C , a , b and n are calculated as:

75.175.1

8.010

NNNC+

+= ; L

GNρρ100= (XIV-7)

2168.0

mma −

= , ( )mb −= exp5.2 ; ⎟⎟⎠

⎞⎜⎜⎝

⎛=

G

Lmρρln (XIV-8)

For operating pressure in the range of 7.0 MPa to 20.0 MPa the entrainment liquid fraction is predicted as:


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⎟⎠⎞

⎜⎝⎛

+−

= − 2.035.0exp 25.114.0 NFrWemE m (XIV-9)

An empirical correlation of liquid entrainment fraction was proposed by Oliemans et

al. [39] using AERE Harwell data bank,

9876543210101

ββββββββββ σμμρρ gVVdEE

SGSLGLGL=−

(XIV-10)

where β parameters as listed in the Table 1:

Table 1 - Summary of Parameters used in Equation (XIV-10)

Parameter Physical Quantity

Parameter Estimate

0β Intercept -2.52

1β Lρ 1.08

2β Gρ 0.18

3β Lμ 0.27

4β Gμ 0.28

5β σ -1.80

6β d 1.72

7β SLV 0.70

8β SGV 1.44

9β g 0.46 Zhang et al. [40] reorganized this correlation as a function of six non-dimensional

groups,

97.038.07.024.192.08.1 ReRe003.0

1 ⎟⎟⎠

⎞⎜⎜⎝

⎛⎟⎟⎠

⎞⎜⎜⎝

⎛=

−−−

G

L

G

LSLSGSGSG FrWe

EE

μμ

ρρ (XIV-11)

where WeSG, FrSG, ReSG and ReSL are given by:

σρ dV

We SGGSG

2

= (XIV-12)


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dgVFr SG

SG = (XIV-13)

G

SGGSG

dVμ

ρ=Re (XIV-14)

L

SLLSL

dVμ

ρ=Re (XIV-15)

After this reorganization, Zhang et al [40] found that 4β should be changed to 0.27

to satisfy the dimensionless requirement. E/CRC Erosion Equations

In order to overcome shortcomings of previous erosion prediction models and correlations, McLaury and Shirazi [35] developed a semi-empirical procedure to predict erosion in multiphase flow. The model was an extension of a previous model that was originally developed for single-phase flow and based on Computational Flow Dynamics modeling and data [41]. The key to the model is to predict a representative particle impacting velocity, and then apply an erosion equation to quantify the erosion rate from the particle impact information. For carbon steel pipes, the form of the equation can be written as:

( ) ( ) nPPS VfFFHBCER θ59.0−= (XIV-16)

where ER is the dimensionless erosion ratio which is the loss of wall material divided by the mass of particles, C is a material dependant constant, HB is the Brinell hardness, SF is the particle sharpness factor, PF is a penetration factor that depends on the material density and geometry, ( )θf is a function of particle impact angle that depends on the material, PV

is the particle impact velocity and n is another empirical constant. The hardness function ( ) 59.0−HB was developed for carbon steels. Every term in Equation (XIV-16), with the

exception of the particle velocity, is empirically based. The main difference between this model and earlier models in the literature is that a representative solid particle to metal impact velocity PV is used to calculate erosion instead of the flowstream velocity. The

investigators [41] developed a simplified method for calculating the characteristic particle


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impact velocity, which is obtained by creating a simple model of the stagnation layer representing the pipe geometry. The stagnation zone is a region that the particles must travel through to strike the pipe wall for erosion to occur. The particle velocity in this zone and resulting erosion depend on a series of factors such as fitting geometry, fluid properties, flow regimes, pipe material properties and sand properties. The initial particle velocity is set equal to the characteristic fluid velocity used at the initial particle location. A particle equation of motion is then used to determine the velocity of the particle as it approaches the wall. When the particle is a radius away from the wall, the particle tracking is stopped and the particle velocity at this location is the impact velocity. Erosion Prediction for Low-Liquid Loading Conditions

As the gas velocity is increased, intense turbulence in the gas stream may cause all the liquid to break into droplets. This type of flow is usually called ‘dispersed liquid’ or “mist” flow. This situation can be seen as a limiting case of annular flow for a negligible film thickness.

In this research, low liquid-loading conditions refers to gas dominant flows where there is insufficient liquid to form a continuous liquid film around the pipe creating annular flow. For very low liquid rates, liquid flows in the form of droplets forming liquid stripes on the pipe walls. Higher erosion rates are observed in gas dominant wells that can damage production equipment, piping and fittings. The erosion in low liquid gas flow ranges from the erosion in gas only flows to erosion in annular flow depending on the liquid rate.

To develop the erosion model for low liquid gas flows, the boundaries of the flow pattern must be determined. An empirical fit was developed [42] for very low liquid-high gas flow where the superficial liquid velocity ranges from 0.001 ft/s to the local minimum erosion near the annular flow transition. The erosion in the very low liquid- high gas flow region is given by Equation (XIV-17):

1

1sl

2sl

1sl

sl

12 ER

VVln

VVln

)ERER(ER +

⎥⎥⎥⎥⎥

⎦

⎤

⎢⎢⎢⎢⎢

⎣

⎡

⎟⎟⎠

⎞⎜⎜⎝

⎛

⎟⎟⎠

⎞⎜⎜⎝

⎛

−= (XIV-17)

where:

slV = Superficial liquid velocity of interest

1slV = Superficial liquid velocity of 0.001 ft/s


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2slV = Superficial liquid velocity at local minimum in erosion near the transition to annular flow

1ER = Erosion prediction for Vsl1 (assuming gas only)

2ER = Erosion observed for Vsl2 (using annular flow model)

In order to apply Equation (XIV-17), the value for 2slV must be determined. Dosila

[42] compared this local minimum to a ratio of particle diameter to film thickness, where the film thickness values for different flow conditions was calculated using the SPPS program. Additional comparisons were made for other low liquid gas conditions in the 2 and 3-inch loops. The results demonstrated that the local minimum in erosion occurs at film thickness to particle diameter ratios between 0.8 and 2.0. Other results showed that the predicted trends of erosion obtained from SPPS program using a ratio of film thickness to particle diameter value of 1 are also relatively close to the experimental normalized erosion obtained from ER probes for other flow conditions. Previous Experimental Work on Erosion Measurements in Gas Dominant Systems

The experimental approach requires using a flow geometry of interest (such as pipe, elbow, and tee) or a representative test specimen to conduct the erosion tests under specific flow conditions. The erosion ratio (mass loss of the geometry/ mass of the sand that causes erosion) and/or penetration rates (thickness loss per unit sand throughput, mils/lb) are then calculated from the mass loss or thickness loss data, geometry, flow and test conditions. This experimental erosion data can be used to validate erosion models.

An extensive empirical information has been gathered at TUSMP for examining sensitivity of ER probes in low liquid loading multiphase flow. For example, Antezena [43] used electrical resistant (ER) probes in 1” pipes and plug tees. Pyboyina [44] conducted experiments in two different orientations, vertical and horizontal for 2” pipes. Nuguri [45] carried out experiments to examine the effect of low-liquid rates on ER probe erosion for gas dominant flows for 2” and 3” pipe diameters. Dosila [42] modified and compared with experimental data a previous erosion model that was developed for very low liquid-high gas flow. Fan [46] examined ER probes for 3” and 4” pipes under low liquid loading.

Although those experiments provide valuable information for erosivity, these ER probe data were collected in short period of time and repeatability of erosion data needs to be examined. Also, all these experiments used ER probes that are fixed at a location and distribution of erosion pattern under low liquid loading and annular flow is unknown.


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Experimental Work

To further investigate the applicability of the models developed to predict erosion rates under high gas and low liquid rates, multiple experiments has been conducted in three different multiphase flow loops at different gas, liquid and sand rates. These facilities were designed and constructed by keeping sufficient upstream length to promote fully developed flow near the erosion test section. All the experiments in this facilities were conducted by keeping the flow loop in the horizontal and vertical positions. Table 2 shows the experimental database that currently exists at the E/CRC and TUSMP. Also, it should be noted that some of the data obtained at TUSMP were aimed at examining the sensitivity of intruments and erosion data were obtained during a short period of time were large uncertainity may exist on the absolute values of data that was collected. Table 2 - Experimental Database at the E/CRC and TUSMP for Low-Liquid Loading

and Annular Flow Conditions.

Pipe Diameter

Vertical Flow

Horizontal Flow

Max. Erosion

1 in ✔ ✔ ✔

2 in ✔ ✔ ? 3 in ✔ ✔ ? 4 in ✔ ✔ ?

At present, only three and four-inch test sections are being used to conduct erosion

experiments at E/CRC. One-Inch Flow Loop

Mazumder [32] used a 1” test facility to measure local thickness loss measurements in elbows specimens. In this test facility, sand and liquid were mixed in a small slurry tank. Then sand and liquid were injected into the gas stream. The gas flow velocity in this one-inch test section can reach to about 100 ft/s at a pressure of about 40 psig. The gas-liquid-sand mixture then flows through the test section. After the test section, the mixture flows to a cyclone separator where liquid and sand are separated from the gas stream. The liquid and


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sand are discharged and the gas flows back to the existing gas-liquid separator before it flows back to the compressor.

These test sections uses test cells with an erosion specimen. The test cell containing the test specimen was made of two halves of CPVC. A 90° elbow specimen of ¼” x ¼” cross-section was placed in the test cell that simulates the outer wall of a 1 inch elbow. Two-Inch Flow Loop

The two-inch Flow Loop was constructed to perform tests in different flow regimes [44]. The two inch flow loop consists of two 100-scfm compressors, one 90 gpm liquid pump, a 1000 gallon liquid tank, gas and liquid flow meters, approximately 90 feet section of 2 inch pipe. A section of the 2-inch pipe is constructed using Plexiglas for flow visualization. The two-inch flow loop is capable of superficial liquid velocity of up to about 10 ft/sec and a superficial gas velocity of up to approximately 100 ft/sec. This facility was used to develop the existing mechanistic prediction model through many experimental studies using ER probes and acoustic monitors. Large Scale Boom Loop

The large scale flow loop has a basic working procedure similar to the two-inch flow loop. Schematic views of the testing facilities are shown in Figures 1 and 2.

Figure 1 - Schematic of Large Scale Boom Loop


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Figure 2 - Test Section of Large Scale Boom Loop

The main difference between the small loops and the large boom loop is that more operating and control devices were added to achieve a broader range of conditions and allowing higher gas velocities. Two-inch, three inch and four-inch sections can be mounted on the large boom loop which can be positioned at any angle. Comparison of Erosion Data with Previous SPPS Model

The previous mechanistic model was compared with available multiphase erosion data reported in the literature or/and obtained at E/CRC for flat-head probes at 45° in the elbow.

The experiments were carried out using sands with different average sizes and two diferent pipe diameters. A comparison of the experimental data with results obtained from the mechanistic model for both vertical and horizontal orientations is shown from Figures 3 to 5:


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0.0E+00

1.0E‐03

2.0E‐03

3.0E‐03

4.0E‐03

5.0E‐03

6.0E‐03

7.0E‐03

8.0E‐03

0 0.02 0.04 0.06 0.08

Superficial Liquid Velocity, Vsl [ft/s]

Erosion, [mils/lb]

DATA SPPS 4.1

Figure 3 - Comparison of Erosion Data with SPPS version 4.1

Annular-Mist Flow 4”, VSG=75 ft/s, 1 cP, 300 μm Sand. Data from Fan [46]

0.0E+00

2.0E‐04

4.0E‐04

6.0E‐04

8.0E‐04

1.0E‐03

1.2E‐03

0 0.01 0.02 0.03 0.04 0.05 0.06 0.07


Erosion, [mils/lb]

DATA SPPS 4.1

Figure 4 - Comparison of Erosion Data with SPPS Annular-Mist Flow 4”, VSG=50 ft/s, 1 cP, 150 μm Sand. Data from Fan [46]


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0.0E+00

1.0E‐03

2.0E‐03

3.0E‐03

4.0E‐03

5.0E‐03

6.0E‐03

0.02 0.03 0.04 0.05 0.06 0.07 0.08 0.09


Erosion, [m

ils/lb]

DATA SPPS 4.1

Figure 5 - Comparison of Erosion Data with SPPS

Annular-Mist Flow 3”, VSG =50 ft/s, 1 cP, 150 μm Sand. Data from Dosila [42]

From Figures 3 to 5, it can be seen that the results obtained from the previous mechanistic model of SPPS 4.1 under-predicts the amount of erosion in the elbow for annular flows, specifically for large diameter pipes. Present Improvements of Erosion Models

The erosion model for annular flow and low liquid loading, previously developed based on earlier data for smaller pipes and based on data that was obtained at TUSMP for evaluating ER probes. Also, experimental work on two-phase vertical upward flow has shown that pipe diameter has an effect on many flow structure parameters in annular flows such as film thickness and entrainment rate. Thus, it becomes necessary to carefully evaluate multiphase flow models that are incorporated in SPPS.

The model development is based on many components and in the present work all components of the model are being evaluated. Figure 6 show a flowchart that describes all the various components that the erosion model is based upon.


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Figure 6 - Model Development Flowchart for Erosion in Low-Liquid Loading and Annular Flows

The specifications of model development for sand erosion prediction under low-liquid conditions and annular flows include: a) Selection and validation of mechanistic models for entrainment fraction and film thickness calculation in both vertical and horizontal flows. b) Estimation of sand rate and particle velocities. c) Measure sand distribution and sand concentration in low-liquid and annular flows to study how sand distribution can affect erosion results under both horizontal and vertical orientations. d) Evaluation and improvement of equations that are used to calculate the equivalent flowstream velocity; computation of the characteristic impact velocity of the particles through particle tracking routines. e) Evaluation and validation of new erosion equations developed to predict erosion rate for different materials used in oilfield industry. f) Improvement of flow field estimation in elbows geometries and calculation of representative particle trajectories that are used as the impingement information in erosion equations to determine a penetration rate. g) Using new erosion measurements in elbows geometries, validate the model.


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h) If the model does agree with erosion data, it can be include in SPPS modules. If not, the results can be used as feedback for future improvements.

Different actions related to some of these specific steps explained in the flowchart are presented. Erosion Ratio Equations

Recently, E/CRC developed new erosion models for Aluminum 6061, Stainless Steel 316 [47] and Inconel 625 based on direct impingement test results in air. Air is used as the carrier fluid to generate erosion. At first, velocities of particles that are flowing out of a straight nozzle are calculated. At step 2, erosion measurements of selected materials are conducted in air. The weight loss method is used for these measurements. The erosion rates of various particle impact angles and velocities were measured to provide enough information to develop an erosion equation. Finally, utilizing the erosion results from step 2 and the particle velocity from step 1, an erosion equation for each material was developed. Particle velocities of 42, 28, and 14 m/s were used as velocity conditions. At each velocity, the measurements were taken for impact angles of 90, 60, 30, and 15 degrees for Stainless Steel [47] and 90, 75, 60, 45, 30 and 15 degrees for Aluminium 6061, Carbon Steel 1018 and Inconel 625 [48]. At each particle velocity and angle, the measurements were taken at least 3 times with 300 g of Oklahoma #1 (150 μm) sand each time [47]. Erosion rates were calculated by mass loss of a target coupon divided by the total mass of sand throughput.

Utilizing the information gained through erosion measurements in air, erosion models for each material were generated.

The angle function as shown by Equation (XIV-18) is a modified version of the angle function suggested by Oka et al, [49] and was used with parameters n1, n2, and n3 which are chosen to fit the experimental data.

( ) ( ) ( )( )( ) 231 sin11sin nnn HvAF θθθ −+××= (XIV-18)

Vicker’s hardness for each material Hv and constants 1n , 2n and 3n , were found

based on the experimental data. Since the experimental data are normalized, the angle function must be normalized as well by dividing the function by A , which is the maximum value of the function. After the angle function is defined, the entire modified erosion equation can be defined based on the earlier work at the E/CRC. Equation (XIV-19) is the erosion equation developed by Zhang [50] at the E/CRC. 2.41 is used as an exponent for the particle velocity, which was also used in the case of Inconel.


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( )θFVFKkgkgER PS ×××=⎟⎟

⎠

⎞⎜⎜⎝

⎛ 41.2 (XIV-19)

where 59.0−×= BHCK for carbon steels.

Since Brinnell hardness BH , sharpness factor SF (0.5 for Oklahoma sand), impact velocity PV and angle function ( )θF are constants for each test condition, an empirical

constant C is found by simply dividing the measured erosion rate by these constants for each test condition. The empirical constant C is calculated for each material for Okita and Fan’s data [48]. Table 3 and 4 represents the summary of erosion equation empirical constants of four oilfield materials.

Table 3 - Summary of Erosion Equation Empirical Constants for Aluminium 6061, Inconel 625 and Stainless Steel 316

Constant Aluminium6061

INCONEL 625

SS 316

n1 0.68 0.49 1.4

n2 2.1 1.3 1.64

n3 10.7 1.44 2.6

Hv 1.089 2.481 1.5

K 5.873E-09 6.858-09 7.444E-09

Table 4 - Summary of Erosion Equation Empirical Constants for Carbon Steel 1018

Constant CS 1018

n1 0.98

n2 1.7

n3 2.91

Hv 1.716

C 1.65E-07

BH 167

K 8.055E-09


November 2011

Figures 7 to 10 are the measured erosion rates vs. impact angle for each velocity condition plotted with the new modified E/CRC equation and Oka’s modified equation.

0.0E+00

5.0E‐06

1.0E‐05

1.5E‐05

2.0E‐05

2.5E‐05

3.0E‐05

0 15 30 45 60 75 90

Impact Angle (Degrees)

Erosion Rate (kg/kg)

Data Vp = 42 m/s Data Vp = 28 m/s Data Vp = 14 m/s E/CRC Equation

Figure 7 - Erosion vs. Angle – Exp. Data and Model for Aluminium 6061

Sand Size 150μm Data from Fan [48]

0.0E+00

5.0E‐06

1.0E‐05

1.5E‐05

2.0E‐05

2.5E‐05

3.0E‐05

3.5E‐05

0 15 30 45 60 75 90




Figure 8 - Erosion vs. Angle – Exp. Data and Model for Carbon Steel 1018 Sand Size 150μm Data from Fan [48]


November 2011

0.0E+00

5.0E‐06

1.0E‐05

1.5E‐05

2.0E‐05

2.5E‐05

3.0E‐05

0 15 30 45 60 75 90




Figure 9 - Erosion vs. Angle – Exp. Data and Model for Inconel 625

Sand Size 150μm Data from Fan [48]

0.0E+00

1.0E‐05

2.0E‐05

3.0E‐05

4.0E‐05

5.0E‐05

0 15 30 45 60 75 90




Figure 10 - Erosion vs. Angle – Exp. Data and Model for Stainless Steel 316

Sand Size 150μm Data from Okita [47] Validation of Stainless Steel E/CRC Erosion Equation using CFD

Several sets of erosion data can be used to examine erosion equations. These erosion data were obtained under a variety of test conditions, including different carrier fluids, a


November 2011

wide range of flow velocities, several types of sand, and different test geometries and materials.

Kesana [51] at E/CRC collected erosion data on a 3” ID Stainless Steel Elbow using Ultrasonic Transducers. The sand used in these test had an average diameter of 150 μm (OK #1 sand). The carried fluid was air. The erosion data was provided en MPY.

A CFD tool, Fluent 6.3, has been selected for the simulation of the flow field inside the piping and for the simulation of the particle trajectories and their impact on the bend walls. A three dimensional mesh has been set up. As far as the numerical and turbulence models are concerned, a segregated, implicit, steady-in-time solver has been adapted, together with a Reynolds Stress Turbulence model. Standard wall functions for the near-wall zone treatment have been selected. Table 5 lists the test conditions and the CFD simulation results for each case.

Table 5 - 3” Standard Elbow Test using UT Data from Kesana [51]

Air (20 psia), Horizontal Flow, 150μm OK#1 sand, UT Data

Gas Velocity (ft/s) 110 108 95

Sand Rate (kg/s) 0.00113 0.00115 0.001165

Data (MPY) 2481 1711 984

CFD Prediction (MPY) Maximum Erosion 2524 2470 1861

Air (20 psia), Horizontal Flow, 150μm OK#1 sand, UT Data

Gas Velocity (ft/s) 110 108 95

Sand Rate (kg/s) 0.00113 0.00115 0.001165

Data (MPY) 2481 1711 984

CFD Prediction (MPY) Maximum Erosion 2524 2470 1861

0

500

1000

1500

2000

2500

3000

110 108 95Gas Velocity, (ft/s)

Eros

ion,

(MPY

)

UT Data CFD E/CRC SS316

Figure 11 - Comparison of Measured and Predicted Erosion on Stainless Steel Elbows


November 2011

3.25e-05

3.08e-05

2.92e-05

2.76e-05

2.60e-05

2.44e-05

2.27e-05

2.11e-05

1.95e-05

1.79e-05

1.62e-05

1.46e-05

1.30e-05

1.14e-05

9.74e-06

8.12e-06

6.49e-06

4.87e-06

3.25e-06

1.62e-06

0.00e+00

ZY

X

Figure 12 - Erosion Contours on Elbow in kg/m2-s

The comparison of preliminary CFD results with erosion data obtained under different conditions shows that the new E/CRC Stainless Steel equation perform relatively well for most cases. In order to improve CFD validation of erosion equations, new mesh sensibility analysis and turbulence model validation are necessary. Additionally, exiting data [52] for Carbon Steel and Cr13 will be analyzed. Also, new data will be collected for both horizontal and vertical conditions for gas only conditions in stainless steel elbows. Mechanistic Model for Gas-Liquid Annular Flows

Entrainment Fraction Validation

Alamu and Azzopardi [53] carried out experiments on a 19 mm (0.75 in) internal diameter vertical pipe with air and water as fluids. A laser diffraction-based measurement instrument was used in drop data acquisition. Then, entrainment was calculated from drop concentration using Equation (XIV-20):

LE

DL

mCVE

&

ρ= (XIV-20)

where DV is the drop velocity, C is the volumetric drop concentration (part per million) and

LEm& is the total liquid mass flux. In the present work, the reported data in the literature by

Alamu and Azzopardi [53] obtained for entrained liquid fraction in the gas core is compared


November 2011

with the models of Ishii-Mishima [37], Nakazatomi [38] and Zhang et al. [40] for two different liquid velocities, 0.05 m/s (0.16 ft/s) and 0.15 m/s (0.33 ft/s) for different superficial gas velocities of 14-43 m/s (45-138 ft/s) in 0.75” pipe diameter.

0

0.1

0.2

0.3

0.4

0.5

40 60 80 100 120 140

Superficial Gas Velocity, Vsg [ft/s]

Entrainment Fraction, E [‐]

DATA Ishii and Mishima Nakazatomi Zhang et al.

Figure 13 - Comparison of Different Entrainment Model Predictions with

Experimental Entrainment Fraction Data at VSL of 0.05 m/s (0.16 ft/s)

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

40 60 80 100 120 140


Entrainment Fraction, E [‐]

DATA Ishii and Mishima Nakazatomi Zhang et al.

Figure 14 - Comparison of Different Entrainment Model Predictions with

Experimental Entrainment Fraction data at VSL of 0.15 m/s (0.49 ft/s)

E

0.75”Dia

E

0.75”Dia


November 2011

As it can be seen in Figures 13 and 14, the predicted entrainment rates using Ishii and Mishima model underpredict entrainment for all gas velocities. The results obtained with the models of Nakazatomi and Zhang agree well with data at higher liquid velocities and lower gas velocities and slightly overpredict entrainment at lower liquid velocities and higher gas velocities. In the present work, Equation (XIV-11) has been included in SPPS 4.2 for entrainment fraction calculation.

The entrainment fraction is used in the mechanistic model to determine the fraction of sand particles in the gas and in the liquid film. Since prediction of entrainment rate is important in development and improvement of the current mechanistic model, further experimental entrainment fraction data is required on two-phase vertical flow in 3” and 4” diameter pipes.

Film Thickness Calculation in Vertical Annular Flow

Kaji and Azzopardi [54] correlated the film thickness with liquid film Reynolds number as in the following Equation:

BLFL ARe=+δ (XIV-21)

where A and B are constants,

L

FFLLF

dVμ

ρ=Re (XIV-22)

( )ddd LL

Fδδ −

=4 (XIV-23)

L

i

L

LL ρ

τμδρδ =+ (XIV-24)

where LFRe is the Reynolds number of the liquid film, Fd is the hydraulic diameter of the liquid film, δ is film thickness. The interfacial shear stress iτ is given by:

2

21

SGGii Vf ρτ = (XIV-25)

where if is interfacial friction factor. Asali [55] proposed a correlation for the interfacial

friction factor in annular flow. The correlation was modified by Ambrosini [56] as:


November 2011

⎟⎟⎠

⎞⎜⎜⎝

⎛−+= +−

L

GLGD

G

i Weff

ρρ

δ 200Re8.131 6.0175.0 (XIV-26)

where the Weber number GWe , and the Reynolds number GRe are defined as:

σρ dV

We CGG

2

= (XIV-27)

G

CGG

dVμ

ρ=Re (XIV-28)

The film velocity FV and gas core velocity CV is given, respectively, by:

( )( )LL

SLF ddEVVδδ −

−=

41 2

(XIV-29)

( )( )2

2

2 L

SLSGC d

dEVVVδ−

+= (XIV-30)

The dimensionless thickness of the liquid film is:

G

i

G

GG ρ

τμδρδ =+ (XIV-31)

and the single phase friction factor is:

2.0Re046.0 −= GGf (XIV-32)

Film Thickness Model Validation using Experimental Data

Since the liquid films involved in most types of film flows are rather thin ( )mm3<

accurate measurement of their thickness is not easy and many alternative methods for their measurement and calculation have been proposed. The methods can be classified into three main groups: film average methods, localized methods and point methods. Alamu and Azzopardi [53] used ring-type conductance probes to measure void fraction in air-water annular flow on a 19 mm internal diameter vertical pipe. The data was collected for superficial gas velocity of 14-43 m/s (45-138 ft/s) and superficial liquid velocities of 0.05 m/s (0.16 ft/s) and 0.15 m/s (0.33 ft/s). Van der Meulen [57] also used conductance probes in annular gas-liquid in a 127 mm (5 in) diameter vertical pipe. The data was collected for


November 2011

superficial gas velocities from 4.5 m/s (15 ft/s) to 23 m/s (75 ft/s) and superficial liquid velocities from 0.014 m/s (0.0459 ft/s) to 0.3 m/s (0.98 ft/s). The predictions were compared with both groups of experimental data for the purpose of their validation.

0

0.2

0.4

0.6

0.8

1

40 60 80 100 120 140


Film Thickness, δ [mm]

DATA Film Thickness Model

Figure 15 - Comparison of Film Thickness Model Predictions with Experimental Data

at VSL=0.49 ft/s

0

0.2

0.4

0.6

0.8

1

1.2

1.4

50 55 60 65 70 75


Film Thickness, δ [m

m]

DATA Film Thickness Model

Figure 16 - Comparison of Film Thickness Model Predictions with Experimental Data

at VSL=0.0459 ft/s

0.75”Dia

δ

δ

5”Dia


November 2011

As it can be seen in Figures 15 and 16, the correlation overestimates film thickness

for a small pipe diameter and slightly underestimates film thickness for a larger pipe

diameter. In the present work, the correlation used by Kaji and Azzopardi [54] has been

included in SPPS 4.2 calculations. New film thickness data for both small and large

diameter pipes available in literature will be used to validate the presented model.

Film Thickness Prediction in Annular Two-Phase Flow through Pipes and Elbows

using CFD

A preliminary CFD calculation has been made to examine CFD capability in predicting various parameters. The presented simulation for annular gas-liquid flow focused in the reconstruction of the gas-liquid interface. This was achieved by using VOF (Volume of Fluid) model included in the commercial CFD package STAR-CD. In this model, a single set of momentum equation is shared by the liquid film and the gas core. The volume fraction of all the fluids in each computational cell is tracked throughout the domain. The gas-liquid interface is tracked based on the distribution of the volume fraction of the liquid in the computational cells.

The flow domains were two-dimensional. The minimum cell size was Δx = 0.1mm. A scheme of the mesh made up by 39445 Cells and 79296 faces is depicted if Figure 17.

Figure 17 - Schematic Representation of the Geometry and Details of Computational Grid.


November 2011

The simulations were implicit unsteady with a time step set at 0.5 s. The Realizable K-Epsilon Two Layer turbulence model was used. The VOF High Resolution Interface Capturing (HRIC) with 2nd Order Discretization scheme was applied for the convective terms in the volume fraction equation. The simulation time was 200 s. All physical and geometrical parameters were determined by annular air-water experimental set-up used by Van Der Meulen [57]:

• Experimental conditions: Pipe diameter = 127mm ≅ 5” VSL =0.301 ft/s, VSG=19.51 ft/s Pressure = 2 Bar

• Liquid Inlet Boundary Experimental Film Thickness =δ 1.92 mm with E=0.44789 Liquid film velocity = smVL /7902.2=

• Inlet boundary and gas properties Liquid film velocity = smVG /88.20=

Gas Core properties = 3/23.8 mkgC =ρ , sPaC −×= −51050.2μ • Outlet: average static pressure (2 Bar)

• Air-Liquid Interaction (Surface Tension σ = 0.073N/m)

0.0

0.5

1.0

1.5

2.0

2.5

3.0

0 2000 4000 6000 8000 10000

Axial distance, [mm]

Film Thickne

ss, [mm]

CFD VOF Prediction Calculated Experimental

Figure 18 – Axial Development of the Liquid Film Thickness in Vertical Pipe


November 2011

From Figure 18, it is observed that as the present model does not consider liquid entrainment in the gas core, the VOF predictions slightly overpredict both calculate and experimental values in the straight section of the pipe. Figure 19 shows the film thickness distribution at the outer wall of the bend. It can be observed that for the expected location of maximum erosion (40°-55°) in vertical flows, the film thickness is similar to the value obtained at the inlet of the elbow.

0.0

0.5

1.0

1.5

2.0

2.5

3.0

0 20 40 60 80Angle, (degrees)

Film Thickness, (mm)

CFD VOF Prediction

Figure 19 - Film Thickness Distribution at the Outer Wall of the Bend

A complete CFD model for gas-liquid annular flows should include three components: the calculation of the core flow, tracking of droplets and the calculation of the film and its interaction with the gas core flow and the liquid droplets. Therefore, these results can be considered preliminary and 3-D simulations may be needed to examine film thickness distribution in an elbow. Sensitivity Analysis of Film Thickness and Entrainment Fraction in Erosion Calculations

In order to increase understanding relationships between annular flow characteristics and erosion predictions models, a sensitivity analysis (SA) is presented. The values of entrainment fraction and film thickness in vertical gas-liquid flows were changed in the current erosion prediction model to determine the effects of such changes in sand erosions

δ


November 2011

calculations. An experimental condition applied in ER probe erosion tests for 4” bends was used. The parameters are presented in Table 6:

Table 6 – Physical conditions and Flow Parameters for Erosion Sensitivity Analysis

Dia

[in]

SGV

[ft/s]

SLV

[ft/s]

Gρ

[kg/m3]

Gρ

[kg/m3]

Gμ

[cp]

Lμ

[cp]

σ

[dyne/cm]

SDia

[μm]

SANDρ

[kg/m3]

Sand Conc.

[kg/kg]

4 75 0.01-0.07 1.2 1000 0.018 1 73 150 2650 1%

0.0E+00

5.0E‐04

1.0E‐03

1.5E‐03

2.0E‐03

2.5E‐03

3.0E‐03

0 0.01 0.02 0.03 0.04 0.05 0.06 0.07


Erosion, [mils/lb]

DATA 0.5δ 1.0δ 1.75δ 2.0δ

Figure 20 - Vertical Annular Erosion Model Sensitivity to Film Thickness (δ) Dia=4”

As it can be seen in Figure 20, as the value of film thickness decreases 50%, the

erosion prediction values increase 40% approximately. On the other hand, if the film thickness increases 100%, the erosion prediction decreases 35% approximately.

From Figure 21, it is observed that if the entrainment fraction decreases 75%, the erosion prediction values also decreases 75% approximately. On the other hand, if the entrainment fraction increases 50%, the erosion prediction also increases 50% approximately.


November 2011

From the presented results it can be said that the erosion prediction model is more sensitive to changes in the entrainment fraction than the film thickness calculation.

0.0E+00

5.0E‐04

1.0E‐03

1.5E‐03

2.0E‐03

2.5E‐03

3.0E‐03

0 0.01 0.02 0.03 0.04 0.05 0.06 0.07


Erosion, [m

ils/lb]

DATA 0.25E 0.75E 1.0E 1.5E

Figure 21 - Vertical Annular Erosion Model Sensitivity to Entrainment Fraction (E)

Pipe Diameter=4” Preliminary Sand Distribution Measurements

A proved method for measuring sand distribution and sand concentration profile [34] was used for measure concentration profile. The experiment was carried out in horizontal orientation. Future experiments will be developed for vertical flows.

Sand distribution measuremets were conducted in the large multiphase flow loop. In the test section of the large multiphase flow loop (3”pipe diameter), shown in Figure 18, an intrusive probe was placed in the horizontal section downstream of the elbow section. The intrusive probe consists of a bend pipe, a ball valve set at one end and a modified compression fitting connected PVC pipe fo the loop. The probe can be traversed across the diameter in order to reach different positions across the pipe; samples at different probe location were obtained and analyzed. For improving the method to collect all sand and water, a hose was connected to the valve. All of the experiments were performed with the probe valve full open.

The fluid considered in this experiment were water and air. The nominal sand size used in this research has an average size of aproximately 300 microns. The flow regime of


November 2011

the experiments conducted during this research was annular flow. Table 7 shows the sand distribution experimental conditions for the tests.

Table 7 - Sand Distribution Experimental Conditions

SLV (ft/s)

SGV (ft/s)

Lμ (cp)

Sand Throughput

(g)

Water Throughput

(gal)

Sand Conc. (%)

Flow Orientation

Flow Regime

0.65 100 1.0 9000 227 1.05 Horizontal Annular

The experiment began by determining the sand concentration using the following

formula:

locationliquidatLiquidlocationprobeatSand

locationprobeationconcentratSand = (XIV-33)

Three measurements for each probe location were collected. The results for the

experimental conditions are shown in the following Table:

Table 8 – Sand Distribution Data

Probe Location

Water Sand Sand Concentration

Sand Concentration Average

(mL) (m3) mass (g) (g) (g/g) (%) (%)

Bottom 164 0.000164 164 2.6 0.01585 1.58537

1.727 185 0.000185 185 3.32 0.01795 1.79459 204 0.000204 204 3.6754 0.01802 1.80167

Bottom Middle

62 0.000062 62 0.5132 0.00828 0.82774 0.837 57 0.000057 57 0.511 0.00896 0.89649

78 0.000078 78 0.61336 0.00786 0.78636

Centerline

52 0.000052 52 0.5494 0.01057 1.05654

1.056 50.5 0.0000505 50.5 0.3765 0.00746 0.74554

50.5 0.0000505 50.5 0.6904 0.01367 1.36713


November 2011

0.00

0.50

1.00

1.50

2.00

1 2 3

Probe Location

Weigh

t Percent(%

)

Sand Concentration

`

Figure 22 - Sand Concentration Profile VSG=100ft/s VSL=0.65ft/s

The results from Figure 22 are very important because it shows that larger amounts

of sand were observed on the bottom of the pipe that in the centerline in all cases; sand near the bottom moves with a slower velocity than in the core region.

Also this figure shows that the sand concentration profile is not uniform. The maximum sand concentration appears to be skewed slightly toward Location number 1.

In order to accurately predict erosion under horizontal and vertical conditions, new sand distribution experiments are required to understand the impact characteristics of the particles. Sand Erosion Detection Technologies

ER Probe

In the present work, experimental erosion measurements were performed with electrical resistance (ER) probes while varying superficial liquid and gas velocities, sand sizes and flow orientations..

The basic principle of ER probe measurement stems from electrical resistance measurements. The core element of the ER probe structure is a pair of spiral electrodes that are attached to each other, namely the sample element (or exposed element) and reference element. The sample element is exposed to the flow, where sand particles impinge the


November 2011

sample element; the reference element is built inside the probe and protected from direct contact with flow. The electrical resistance of the reference element remains the same since it is protected from the flow, while the electrical resistance of sample element changes since the sand particles are causing erosion changing the cross-sectional area of the element. Then, the Cormon transmitter unit along with data acquisition software measures the real-time electrical resistance for both the sample element and reference element. The difference between the two is related to the corresponding metal loss. Ultrasonic Erosion Rate Monitoring (UT)

In the present work, a non-invasive technique for measuring erosion based on ultrasonic measurements was used to collect erosion data for multiphase flows under annular conditions.

The ultrasonic device used was developed by Scott Grubb, PhD Student and ConocoPhilips. It includes a process for measuring a thickness of a sound conducting material which involves a ultrasonic source to provide a pulse into the material and a ultrasonic receiver to collect reflections from the opposite side of the material. The temperature of the pipe is measured while a series of pulses is emitted from the source into the material. A temperature corrected wall thickness is determined based on the calculated average time for an ultrasonic sound wave to travel through the wall along with the coefficient of thermal velocity expension in a temperature compensation model. Measured Effects of Flow Orientation on Sand Erosion

Experimental erosion studies on flat-head ER probes at 45° in the elbow were conducted by Dosila [42] on the Large Boom Loop in two different orientations, horizontal and vertical for 3” pipe diameter. Experiments were performed for different flow regimes ranging from low liquid loading to annular flow with differents sand and gas velocities. The results of ER probe measurements at 45° for both flow orientations using 300 µm Sand for a superficial gas velocity of 50 ft/s are shown in Figure 24.


November 2011

0.0E+00

4.0E‐03

8.0E‐03

1.2E‐02

1.6E‐02

2.0E‐02

0 0.02 0.04 0.06 0.08 0.1


Erosion, [mils/lb]

Vertical Horizontal

Figure 23 - Erosion for 300 µm sand for 1 cp fluid at VSG= 50 ft/s

on 3-inch loop

From Figure 23, it can be seen that considerable change in metal loss rate is observed when the velocity of gas changes under different flow orientations. With a further increase in the amount of liquid added, a transition to an intermediate regime between low-liquid gas flow and annular flow starts. Then, for vertical flow orientations, erosion reaches a local minimum value as the liquid velocity approaches annular flow.

In this research, new ER-Probe measurements were conducted using flat-head ER probes at 45° in the elbow on the Large Boom Loop in two different orientations, horizontal and vertical for 4” pipe diameter. Experimental condition are shown in Table 9. The results of metal loss rate for both flow orientations are shown in Figure 24.

Table 9 – Experimental Condition for ER-Probe Measurements

Horizontal vs. Vertical - Air Water Annular Flow 4” Pipe

SLV (ft/s)

SGV (ft/s)

Sand Size (μm)

Water Viscosity

(cp)

Sand Throughput

(g)

Water Throughput

(gal)

Sand Concentration

(%) 0.65 100 300 1.0 9000 227 1.053


November 2011

Horizontal Vertical

0.00E+00

1.00E‐04

2.00E‐04

3.00E‐04

4.00E‐04

5.00E‐04

6.00E‐04

7.00E‐04

Flow Orientation

Erosion, (mils/lb)

Figure 24 - Comparison Horizontal vs. Vertical - Air Water Annular Flow 4” Pipe

It can be seen that at a superficial gas velocity of 100 ft/s for vertical flow

orientation, the metal loss rate is approximately 1.5 times higher than the metal loss rate for horizontal flow orientation at a superficial liquid velocity of 0.65 ft/s. UT Erosion Measurements

In the present work, UT measurements were taken on a 3” ID Stainless Steel elbow on the Large Boom Loop in two different orientations, horizontal and vertical. Experimental condition are shown in Table 10. The results of metal loss rate for both flow orientations are shown in Figures 25 to 28:

Table 10 – Experimental Condition for UT Measurements Horizontal vs. Vertical - Air Water Annular Flow 3 Pipe

SLV (ft/s)

SGV (ft/s)

Sand Size (μm)

Water Viscosity

(cp)

Sand Throughput

(g)

Water Throughput

(gal)

Sand Concentration

(%) 0.7 115 300 1.0 9000 227 1.053


November 2011

Figure 25 - UT Erosion Rate Measurements in MPY. Horizontal Annular Flow, VSG=115 ft/s and VSL=0.7 ft/s

Figure 26 - UT Erosion Rate Measurements in mils/lb. Horizontal Annular flow; VSG=115 ft/s and VSL=0.7 ft/s

From Figures 25 and 26 it can be seen that for horizontal flow orientation, the

maximum erosion values obtained were localized approximately in the middle and upper section at 45° in the elbow.


November 2011

Figure 27 - UT Erosion Rate Measurements in MPY. Vertical Annular flow, VSG=115 ft/s and VSL=0.67 ft/s

Figure 28 - UT Erosion Rate Measurements in mils/lb. Vertical Annular flow, VSG =115 ft/s and VSL=0.67 ft/s


November 2011

From Figures 27 and 28 it can be seen that for vertical flow orientation, the maximum erosion values obtained were localized approximately in the middle plane section at 45° in the elbow. Also, the values obtained were approximately 10 times higher than the metal loss rate for horizontal flow orientation.

Up to this point, it is clear that the orientation can have an impact on the amount of erosion. However, it is not clear whether the increase in erosion corresponds to an increase in the maximum penetration rate. Comparison of Erosion Data with current SPPS Model

The modifications made in the mechanistic model for gas-liquid annular flows were included in the current version of SPPS. The results were compared with available multiphase erosion data reported in the literature or/and obtained at E/CRC for flat-head probes at 45° in the elbow. A comparison of the experimental data with the mechanistic model is shown from Figures 29 to 31:

0.0E+00

5.0E‐03

1.0E‐02

1.5E‐02

2.0E‐02

2.5E‐02

3.0E‐02

0 0.02 0.04 0.06 0.08


Erosion, [mils/lb]

DATA SPPS 4.2




November 2011

0.0E+00

1.0E‐03

2.0E‐03

3.0E‐03

4.0E‐03

5.0E‐03

6.0E‐03

0.02 0.03 0.04 0.05 0.06 0.07 0.08 0.09


Erosion, [mils/lb]

DATA SPPS 4.2



0.0E+00

5.0E‐04

1.0E‐03

1.5E‐03

2.0E‐03

2.5E‐03

3.0E‐03

0 0.01 0.02 0.03 0.04 0.05 0.06 0.07


Erosion, [m

ils/lb]

DATA SPPS 4.2


Annular-Mist Flow 3”, VSG=50 ft/s, 1 cP, 150 μm Sand. Data from Dosila [42] Comparison of Erosion Data with current SPPS Model including New Erosion Equation for Stainless Steel 316

The modifications made in the erosion ratio equation for Stainless Steel 316 were included in the current version of SPPS 1D. Preliminary SPPS results were compared with multiphase UT erosion showed in Figure 32:


November 2011

UT Data

SPPS

0.00E+00

2.00E‐03

4.00E‐03

6.00E‐03

8.00E‐03

1.00E‐02

Annular Flow

Erosion, (mils/lb)

Figure 32 - Comparison of UT Erosion Data with current SPPS Model including New

Erosion Equation for Stainless Steel 316

The comparison of preliminary SPPS results with erosion data obtained shows that the new E/CRC Stainless Steel equation performs relatively well. In order to improve this result, new data will be collected for both horizontal and vertical conditions for gas only and multiphase flow conditions.

Summary and Research Tasks

The main objective of this research is to improve the existing mechanistic model to accurately predict erosion under low-liquid loading gas and annular flow conditions.

The mechanistic model available for predicting erosion in multiphase flow was developed using data for 1” and 2” pipe diameters. New data has been collected for 3” and 4” pipe diameters for both vertical and horizontal flows. When compared with this experimental erosion data, the current model over-predicts the erosion ratio for 3” and 4” pipe diameters.

The existing model needs to be refined further by comparing with new erosion test results in vertical and horizontal flow. More erosion tests at low-liquid velocities and high gas rates for large diameters should be conducted. Erosion testing will be carried out with air and water with different gas conditions, liquid flow rates and various sand sizes to improve reliability and accuracy of the data. Erosion test results will be compared with


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SPPS output. The test results will be used to validate, modify and refine the E/CRC erosion prediction model (SPPS). Also, the location of maximum erosion for high gas/low liquid rates in 2”, 3” and 4” pipes should be determined. The Large Boom Loop will be used to conduct erosion tests at different flow regimes.

In order to improve the existing erosion prediction model in multiphase flow and based on the preliminary investigation realized in the E/CRC, the following tasks need to be performed: • Run Experimental Cases in a PVC Test Cell and determine the location of Maximum Erosion in elbow Specimens (3” Pipe diameter) • Continue gathering erosion data for annular flows in 3” and 4” pipes using ER Probes in Pipe Vertical and Horizontal Flows • Continue Ultrasonic Measurements under Vertical and Horizontal for low-liquid and annular flow regimes • Run UT measurements under Vertical Gas Only conditions and compare results with current E/CRC Model for Stainless Steel and Inconel 625 (via CFD) • Measure the relative concentration of sand at various radial positions upstream of the bend for both horizontal and vertical orientations in 3” and 4” pipes (mist-stratified and mist-annular flows) • Measure the relative concentration of sand at various radial positions upstream of the bend for both horizontal and vertical orientations in 3” and 4” pipes (mist-stratified and mist-annular flows) • Relate results of sand distribution with particle impact characteristics and erosion patterns obtained from both UT and specimen measurements. • Improve results of E/CRC Erosion prediction models for different oilfield materials • Run CFD simulations and validate equation with new erosion data • Continue CFD Multiphase flows simulations


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