data and modelling for improved design and operations...kruger, f.j., kontogeorgis, g. m, solbraa,...
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opportunities in subsea dehydrationdata and modelling for improved design and operations
presented by Francois Kruger, supervisors: Nicolas von Solms & Georgios M. Kontogeorgis
references:1. Kruger, F.J., Kontogeorgis, G. M & von Solms, N. New association schemes for mono-ethylene glycol: Cubic-Plus-Association parameterization and uncertainty analysis. Fluid Phase Equilibria 458, 211–233 (2018).2. Kontogeorgis, G. M., V. Yakoumis, I., Meijer, H., Hendriks, E. & Moorwood, T. Multicomponent phase equilibrium calculations for water–methanol–alkane mixtures. Fluid Phase Equilibria 158–160, 201–209 (1999).3. Bjørner, M. G., Sin, G. & Kontogeorgis, G. M. Uncertainty analysis of the CPA and a quadrupolar CPA equation of state – With emphasis on CO2. Fluid Phase Equilibria 414, 29–47 (2016).4. Kruger, F.J., Danielsen, M.V., Kontogeorgis, G. M, Solbraa, E. & von Solms, N. Ternary Vapor−Liquid Equilibrium Measurements and Modeling of Ethylene Glycol (1) + Water (2) + Methane (3) Systems at 6 and 12.5 MPa. J. Chem. Eng. Data 63, 1789–1796 (2018).5. Kruger, F.J., Kontogeorgis, G. M, Solbraa, E. & von Solms, N. Multi-component vapor-liquid equilibrium measurement and modeling of ethylene glycol, water and natural gas mixtures at 6 and 12.5 MPa. Submitted for publication: J. Chem. Eng. Data (2018).6. graphic taken from https://www.equinor.com/en/magazine/the-final-frontier.html
acknowledgement the authors wish to thank Equinor for their permission to publish experimental data and financial support of this research - part of the CHIGP (Chemical in Gas Processing) project
project background• collaboration between KT-CERE and Equinor (formerly Statoil)
• evaluation of high-pressure subsea natural gas dehydration
• critical specifications:
• H2O dew point
• glycol in the gas phase
figure 1: planned workflow for the subsea processing project
does it matter?potential gains waiting to be unlocked
on-going experimental work at DTU #
• troubleshooting & re-commissioning
• installation of a new Agilent 7890B GC
• development of experimental method
• verification/validation of apparatus
• preliminary work with H2O + CH4
photo 1: three-phaseequilibrium cell located atthe CERE laboratory inLyngby – the red ROLSIsampling valves featureprominently
a fruitful partnership friends from the north#
• 6-month external research stay at Equinor in Trondheim, Norway
• state-of-the-art experimental phase equilibrium equipment: quantification of all components in all phases
starting simple MEG + H2O + CH4(4)
• experimental uncertainty ± 2-12%
• modelling with CPA yields errors between 5-20%
• very satisfactory results
adding complexity MEG + H2O + natural gas(5)
• addition of natural gas: 4% C2H6, 2.5% CO2 and trace components quantified to n-hexane (6 ppm)
• significantly larger modelling errors: 4-70% - can we improve?
• introduction of CO2 creates several modelling difficulties, especially for MEG in the gas phase
• MEG-hydrocarbon kij required to predict dissolved natural gas accurately
getting the thermodynamics right # #
new association schemes for MEG• three new association schemes proposed for MEG(1)
• CPA(2) parameter sets fitted to pure component experimental and liquid-liquid
equilibrium (LLE) data
• promising results (Figure 3) using the newly proposed 4F association scheme
• significantly smaller binary interaction parameters (kij)
finding (some) certainty in uncertainty (analysis)• bootstrap method:(3) parameter distributions indicate multiple optima
• highlighted value in use raw experimental data for parameter regression
figure 2: new associationschemes which have beenproposed and tested forMEG and make use of abipolar association site:these sites can act aselectron donors oracceptors and have beenused successfully in thedescription of 1-alkanols
1,2 ethanediolMono-ethylene glycol
Positive site Negative siteBipolar site
C C OO
4C-scheme
H H
C C OO
4E-scheme
H H
C C OO
4F-scheme
H H
C C OO
3C-scheme
H H
1% 2% 4% 6% 8% 10% 12% 14% 16% 18% 20% 22% 24%
% AARDP
Sat*
*
Tx (MEG - H2
O)
Ty (MEG - H2
O)
Tx (MEG - CH4
)
Ty (MEG - CH4
)
LLE (MEG - nC6
)*
LLE (MEG - nC7
)*
Lit - Derawi (4C)
This work (4F)
95% Conf. Int.
figure 3: radar plotcomparing the relativeperformance of thenew 4F associationscheme for MEGversus the literature4C parameter set
* data included in parameter regression
49.8 50 50.2 50.4
0.99
1
1.01
1.02
a0
vs b0
All points This work 95% Confidence Interval
49.8 50 50.2 50.4
2330
2340
2350
2360
/R vs b0
49.8 50 50.2 50.4
11.7
11.8
11.9
12
12.1
10 3 vs b0 figure 4: selected co-
parameter correlation plotsand confidence intervals forMEG modelled with the new4F association scheme
figure 5: experimental results for H2O in gas forternary MEG + H2O + CH4 data, with 90 wt% MEGat T = 288-323 K and P = 60 and 125 bar.modelling performed using literature 4C parameterset for MEG, yielding an AARD of 5.2%.
285 290 295 300 305 310 315 320 325 330
Temperature [K]
0
100
200
300
400
500
600
700
800
900
ppm
[m
ol]
y2
CPA (60 bar)
y2
Experimental (60 bar)
y2
CPA (125 bar)
y2
Experimental (125 bar)
10 20 30 40
Temperature [°C]
0
5
10
15
20
yM
EG
[ppm
]
Exp (60 bar)
Exp (125 bar)
CPA (60 bar)
CPA (125 bar)
10 20 30 40 50 60
Temperature [°C]
0
200
400
600
800
1000
yH
2O
[ppm
]
10 20 30 40 50 60
Temperature [°C]
4000
6000
8000
10000
12000
xN
G [m
ol/m
ol]
10 20 30 40 50 60
Temperature [°C]
4000
5000
6000
7000
8000
9000
xC
1 [p
pm]
10 20 30 40 50 60
Temperature [°C]
350
400
450
500
550
600
650
xC
2 [p
pm]
10 20 30 40 50 60
Temperature [°C]
500
1000
1500
2000
2500
xC
O2
[ppm
]
figure 6 (top): experimental results(left to right) for MEG in gas (70%),H2O in gas (24%) and total dissolvednatural gas
figure 6 (bottom): experimentalresults (left to right) for dissolvedmethane (5%), ethane (6%) andcarbon dioxide (14%)
%AARD given in brackets
table 1: lessons learnt from experimental data (arrow: temperature trend, relative colour: relative performance subsea vs onshore)
figure 7: combined uncertainty and sensitivity studies with Monte
Carlo approach
• real-world applications e.g. The Subsea FactoryTM (graphic 1)
• decreased pressure losses (single phase flow)
• improved operability
• recovery in marginal/isolated fields (increased tieback)
graphic 1: The Subsea FactoryTM (6)
decision-making in operations and design # # #
• where can we improve current operations?
• which design opportunities can be exploited?
• opportunities with high-pressure operation
a near future: building process simulations• process simulation in Aspen Plus
• find optimal process conditions, chemical req.
• from operating points to operating windows
• evaluate performance at confidence intervals
• determine sensitivity to process upsets
• Monte Carlo simulations in Matlab
• process feasibility studies
• probability-based production forecasting
• probability-based optimization
• equipment sizing
• economic analyses
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