Anand S. Nagoo, Ph.D. - Multiphase Flow Science Group at … · code is for design and optimization...

2017 DOE-NETL Multiphase Flow Science

1D simulations of averaged CMFD results for combined 1D-CMFD process flows (Nagoo)

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Anand S. Nagoo, Ph.D.

Department of Petroleum & Geosystems Engineering

The University of Texas at Austin, USA

Improved Speed and Reliability of Averaged (1D)

Multiphase Flow Calculations for Use in Combined

1D-CMFD Field-Scale Process Simulations:

Validation of PipeFractionalFlow and CMFD codes



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What is PipeFractionalFlow?

What is PipeFractionalFlow? An analytical averaged (1D) code

for rapid and reliable predictions of steady-state and transient

multiphase flow variables along wellbores and pipelines. The

code is for design and optimization of field-scale processes.

GUI EXE

XLS RPi



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Theory Overview + Four CMFD Applications

• Introduction to the Pipe Fractional Flow Theory underlying the

PipeFractionalFlow™ C++ code

• Use of the Pipe Fractional Flow Theory to reformulate and unify prior

volume fraction models

• Benchmarking against current and former commercial1D codes

• Experimental validation against PipeFractionalFlow and multiphase

CFD codes

– Converging-diverging-converging gas-liquid nozzle flow

– Transient riser-base gas lift for liquids removal

– Non-Newtonian multiphase gas-liquid-solid slurry flow

– Dilute pneumatic conveying gas-solid flow



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Several Modeling Approaches



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Averaging in Space and Time



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Some 1D modeling applications in Oil & Gas

- Real-time drawdown management and downhole surveillance & monitoring

- Minimize need (and huge costs) for permanent DHPG installs in new wells

- Provide reliable DHPG simulation in old wells with faulty/non-functioning gauges

- Steady-state and transient three-phase flow analytical predictions from surface

- Fast simulations for closed loop optimization & reservoir model calibration

- System modeling at discrete level (multi-segmented approach)

- Analytical phase volume fraction modeling

- Minimize need (and huge costs) for multiple field flow meters & maintenance

- Gas lift, ESP pump intake modeling, liquids loading, plunger lift optimization, etc.

• Accurate downhole pressure from surface at low cost (THE PRIZE)

• Transient real-time modeling for surveillance & optimization

• Wellbore and pipeline flow rate calculations (virtual flow metering)

• Horizontal well artificial lift modeling



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Some CMFD modeling applications in Oil & Gas

• Heat transfer in Christmas tree

• Severe slugging in riser

• Sand transport in pipes (PnC, slurries)

• Cuttings transport modeling in wellbores (mud rheology, density, etc.)

• Hydrate formation

• Slug flow around pipe elbow

• Non-Newtonian multiphase flows

• Three phase separator

• Temperature effects in transportation of viscous oil

• Etc…



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Goal: Combined 1D-CMFD Co-Simulation

• Fast enough to provide to provide answers within design timeframe

• Accurate enough to provide sufficiently insightful answers for better

design decisions

• 1D simulator for long wellbores and pipelines; 3D CMFD simulator for

3D equipment, transition regions

• User friendly environment for activating the right mix of high-fidelity tools for the problem of interest

• Why?

– It’s cheaper and safer to be wrong in the virtual world!

– Expand the modeling scope and lifecycle

– Dynamic boundary specs. vs. fixed (invalid) boundary specs.



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What Differentiates Us – Analytical Theory



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What We Generate – Fractional Flow Curves



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How We Standout – A Modern Approach



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Rationale for Fractional Flow Method

mixu

uf

2

2

1

2

1,2v

vH

2

21,2

1,2

2122

222

2111

ssH

H

svsv

sv

u

uf

mix



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Rationale for Fractional Flow Method

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1

2

2

1,2

2

f

fH

s

1

2

2

2

2

1,2

11

f

f

s

sH



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Volume Fraction Models as Slip Ratios

2

2

1,21

102.1

,2

0

f

s

uH

mix

v

Cmix

1

2

2

71.0,]12[

1.0

1

2

4.0

1

2

9.0

2

2

1,2

1128.0

f

f

f

fH

ttXparameterMartinelliandLockhart

2

2

5.0

1,21

135.02.1

,2

0

f

s

u

gDH

mix

v

C

mix

5.0

1

2

1,2

Fauske

H

And so on…



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Drift-Flux Equations as Slip Ratios

mix

mix

u

vC

s

f ,2

0

2

2

2

2,2

01,21

1

f

s

u

vCH

mix

mix

mixv

parameter

slipparticle

averaged

parametersparticletoparticle

averaged

mix

velocityslip

averaged

s

vssuCS

,2

2

1,22

201,211

Different quantities! (relation between “global” and “local”)



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E.g. Woldesmayat and Ghajar (2007)

Fractional flow paths (solid lines in left chart above) as compared against

two published datasets (diamond and circular points above) from Spedding

and Nguyen (1976), spanning a wide range of flow patterns and flow rates



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Insight 1 – Capture Interrelationships



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Insight 2 – Reduce Uncertainty



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Benchmarking and Validation



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Publicly Verifiable Benchmarking

Cousins, Denton and Hewitt

(1965) – Exp. # 49, data also in

Table . of Wallis’s One Dimensional Flow textbook



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Owen, D. G.: An

experimental and

theoretical analysis

of equilibrium

annular flows, Ph.D.

Dissertation, Dept.

of Chem. Eng., U. of

Birmingham (1986)

Also available from

Theofanous, T. G.,

Amarasooriya, W.

H.: Dataset no. 1 -

pressure drop and

entrained fraction in

fully developed

flow, Multiphase Sci.

and Tech., v. 6, part

1, pp. 5-13 (1992)



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• Crowley et al. (1986)

• Slug Flow

• Large Diam., Fr12-Water

High Gas Density

• Johnson (1996)

• Stratified Roll Waves*

• Med. Diam., SF6-Water

High Gas Density



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Experimental Validation – PFF vs. CMFD

Pougatch, K.,

Salcudean, M., Chan,

E., Knapper, B.:

Modeling of

compressible gas-liquid

flow in a convergent-

divergent nozzle,

Chem. Eng. Sci., v. 63,

pp. 4176-4188 (2008)



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Same

scale! Multiple cases in the paper - lines

are our predictions. Demonstrates

the accuracy of our in-situ phase

flow rate calculations.



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Kapok

Choke (2004) Flambouyant

Flowline (1996)

Eroded

Choke

Internals

Immortelle

Separator

Dangers of

sand/solids

production in

oil and gas –

an unforgiving

problem!



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Luo and Gidaspow (1997)

Dissertation Data

3” diameter riser

Air-Glass Beads (520 μm)



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Luo and Gidaspow (1997)

Dissertation Data

3” diameter riser




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Rautiainen et al. (1999)

J. Powder Technology

8” diameter riser




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Wang and Zhu (2005)

Intl. J. Multiphase Flow

1” diameter riser


Electrostatics and Adhesion

CMFD model

in paper



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Zenz Plot



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CMFD model

in paper

Henthorn and Curtis (2005)

J. Ind. Eng. Chem. Res.

1” diameter riser

Air-Glass Beads (70, 200 μm)



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Take Home Message

• Insightful analytical modeling leads to improved understanding of averaged

(1D) multiphase flow behaviors. Analytical prediction brings significant practical

implications for 1D codes – breaking speed and accuracy limits in field-scale

design and optimization of multiphase flow problems

• The new analytical formulation underlying the PipeFractionalFlow code have

been successfully used to predict (and compared side-by-side) the macroscopic

averaged results from published CMFD papers and experiments.

• The net of the co-existing and competing local flow microphysics (the resultant

collective behavior of the flowing multiphase mixture) are captured in our

physics-based averaged analytical equations.

• New value outcome = integrating via up-scale and down-scale calculations fast

and reliable field-scale 1D simulation with advanced, local CMFD codes for

process simulations, i.e. PipeFractionalFlow can be used as reliably accurate

boundary conditions for CMFD codes (such as MFiX, STAR-CCM+, Fluent, etc.)



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Thanks to all for your time!

Acknowledgements

• Department of Petroleum & Geosytems Engineering | pge.utexas.edu

• Pipe Fractional Flow, LLC | pipefractionalflow.com

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Anand S. Nagoo, Ph.D. - Multiphase Flow Science Group at … · code is for design and optimization...

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