Simulation of Amine Plants: Fundamental
Models and Limitations
2das Jornadas Técnicas Sobre Acondicionamiento del Gas Natural
30 de Septiembre al 3 de Octubre de 2008
El Calafate, Argentina
Jenny Seagraves
INEOS Oxide
GAS/SPEC Technology Group
IAPG 2008
Topics of Presentation
 General history and overview of fundamental models
 refer to paper and references in papers for more details
 Case Studies
 Important considerations or ideas for designing or optimizing an
amine plant
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History and Fundamentals of
Amine Simulation Models
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Improved simulation model are developed as solvent
technologies evolve and amine plant become more
complex….
TEA
1930
MEA
DEA
1940
DGA
1950
MDEA
Simple Models
(Hand Calculations)
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Specialty
Amine
1960
1970
1980 & Beyond….
DIPA
Complex Computer
Models
Simulation of MDEA and newer specialty solvents...
 MDEA-based and specialty solvents more difficult to simulate
 contain MDEA and sometimes blends of chemicals that yield specific
treating characteristics
 have components with different reaction kinetics
 MDEA solvent have different temperature profile than MEA or DEA.
 Simplified computer calculations are dangerously misleading for
MDEA and specialty amine designs
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Improved Simulation is Needed as
Amine Plant Designs Evolve...
 While 20 trays absorber & regenerator designs are still most
common ….
 We now are designing amine plants with
 multiple feeds and side draws
 Complex multi-staged flash to reduce energy
 New mass transfer devices to get more capacity
» new packing material or trays
» or a combination of the two.
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Example of Amine Plant with Multi-feeds and Flash
CO2
Lean Amine
T = 130 F (50 C)
Absorber
Semi-lean
Regenerator
Syngas
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Rich Amine
Reboiler
Definitions
 Vapor Liquid Equilibrium (VLE)
 Defines the solution chemistry / chemical species present
 model determines the maximum limit of H2S and CO2 absorbed
 Reaction Rates
 Defines how quickly H2S and CO2 are absorbed
 H2S react instantaneously with amines and CO2 react at various rates
depending on type of amine.
 Mass Transfer Rate
 Define the surface area and how quickly the surface area is refreshed
for H2S and CO2 absorption
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Vapor Liquid Equilibrium
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ionization of water
2 H2O  H3O+ + OH-
(eq. 1)
dissociation of hydrogen sulfide
H2O + H2S  H3O+ + HS-
(eq. 2)
dissociation of bisulfide
H2O + HS-  H3O+ + S2-
(eq. 3)
dissociation of carbon dioxide
2 H2O + CO2  H3O+ + HCO3-
(eq. 4)
dissociation of bicarbonate
H2O + HCO3-  H3O+ + CO32-
(eq. 5)
dissociation of protonated alkanolamine
H2O + RR’R’’NH+  H3O+ + R’R’R’’N
(eq. 6)
carbamate reversion to bicarbonate
RR’NCOO- + H2O  RR’NH + HCO3-
(eq. 7)
Vapor Liquid Equilibrium
The equations governing chemical equilibria for equations 1 to 7
may be written as:
K = i (xi i )i
(eq. 8)
where, K is the equilibrium constant
xi is the mole fraction of species i
i is the activity coefficient of species i
i is the stoichiometric coefficient
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Chemical Kinetics and Mass Transfer
Ni = Ei k°i,L a (yi interface - yi Bulk)
(eq 8)
NI = transfer rate
Ei = enhancement factor (accounts for chemical reaction)
k°i,L = Mass transfer coefficient
a = interfacial area
yi interface= acid gas conc. at interface (from Henry’s law)
yi bulk = acid gas conc. in bulk (from VLE)
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Evolution of Amine Simulation
 Pre 1980s - Equilibrium Stage
Approach was only method
 Uses simplified estimates
 More rigorous
 Estimate chemical species in
solution
 Calculate exact chemical
species present in solution
 Uses tray efficiencies lump
reaction and mass transfer rates
 Calculate reaction and mass
transfer rates
 Adequate for simulation of
MEA and DEA
 Accurate for MEA, DEA,
MDEA, and Specialty amine
solvents
 Not accurate for MDEA,
specialty solvents, and complex
amine mixtures
 Still used in many commercial
simulators today
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 After 1980s - Mass Transfer
Rate Based Approach
 Can be extended to systems
with heat stable salts and other
components if data is available
 Used in only a few simulators
History of Mass Transfer Rate Based Simulation
Approach
 Idea to combine mass transfer with chemical reactions in amine
simulation came about as a result of works by Astarita, Weiland,
Katti, and others.
 In early 1980s, GAS/SPEC funded a series of research projects to
developed the first amine simulator that combined
 rigorous vapor-liquid-equilibrium (VLE) modeling
 with mass transfer and chemical reactions calculations
 Mass Transfer Rate-based simulation has been used and refined
over the last 20+ years by the GAS/SPEC group
 Available in certain simulators such as
 GAS/SPEC APS Simulator (proprietary simulation program)
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 Commercially available ProTreat Simulator (Optimized Gas Treating
Inc.)
What is mass transfer rate-based?
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Example of GAS/SPEC APS Simulation
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Most Basic Amine Simulation Models
Use tray efficiencies to
account for
•mass transfer
•reaction rates
Tray Efficiency
Properties
Simulation
Efficiencies are empirically
derived
Ignore tower internals
•use equivalent stages to
represent a given number
of trays or packing height
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Material Balance
Phase Equilibrium
Predicted
Plant Performance
Mass Transfer Rate-based Simulations
More detailed approach
Avoid the use of efficiencies
Considers differences in
reaction rates of H2S and
CO2
Consider Mass Transfer rate
of absorption in different
tower internals (trays,
packing, etc.)
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Mass Transfer
(Tower internals)
Reaction Kinetics
Properties
Simulation
Material Balance
Phase Equilibrium
Predicted
Plant Performance
Advantages of MT Rate-based Models
 Makes more rigorous and accurate
prediction inside column
Example of Actual vs Predicted
21
 temperature profile
 identify trouble area in the
column
» equilibrium limits
» areas of corrosion concerns
due to high temperatures
17
Tray Number
 reaction or absorption zone
ProTreat
Actual
19
15
13
11
9
7
5
3
1
100
110
120
130
140
Temperature (F)
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150
Equilibrium Stage Approach
 No one-to-one correspondence
of theoretical stage with
position in column
 3 trays per stage ? Or 4 trays
per stage?…etc.
Top Tray
Stage 3
 Difficult to locate exact
temperature and composition of
feeds and side draws
Tray location?
Stage 2
Stage 1
Feed
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Tray location?
Temp?
Composition?
M.T. Rate-based Approach
 Know temperature and
composition on every actual
tray
 Can accurately locate
optimum points for feeds and
side draws
Top Tray
Tray is known
Tray is known
Temp is known
Feed
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Case Studies
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Case Study 1
 High pressure coal bed methane gas
 requires CO2 removal only
 plant have ability to treat a portion of the natural gas and blend to meet
3 mol% CO2 spec
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Case 1 - Flow Diagram
TREATED GAS
REFLUX
CONDENSER
LEAN AMINE
REFLUX
ACCUMULATOR
REGEN
ABSORBER
FILTER TRAIN
FEED
AMINE
COOLER
REBOILER
RICH AMINE
LEAN /RICH
CROSS-EXCHANGER
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Benchmark Performance Tests
Test 1
Test 2
Test 3
Raw Gas
Flow (Nm3/h)
Temperature (oC)
Pressure (kPa)
CO2 (mol%)
235500
40
6881
4.29
232100
40
6881
4.29
200900
40
6881
4.21
Lean Solvent
Flow (m3/h)
Temp (oC)
Wt% MDEA
227
40
48
186
43
48
227
39
48
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Performance Compared to Simulation
Solvent Rate (m3/h)
Gas Rate (Nm3/h)
Treated Gas
Measured CO2 (mol%)
Predicted CO2 (mol%)
Lean Amine
Actual mol/mol
Predicted mol/mol
Rich Amine
Predicted mol/mol
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Test 1
227
235500
Test 2
186
232100
Test 3
227
200900
1.54
1.57
1.98
1.95
1.20
1.20
0.008
0.0075
0.008
0.0059
0.007
0.0046
0.310
0.403
0.294
Performance Compared to Simulation
Solvent Rate (m3/h)
Gas Rate (Nm3/h)
Treated Gas
Measured CO2 (mol%)
Predicted CO2 (mol%)
Lean Amine
Actual mol/mol
Predicted mol/mol
Rich Amine
Predicted mol/mol
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Test 1
227
235500
Test 2
186
232100
Test 3
227
200900
1.54
1.57
1.98
1.95
1.20
1.20
0.008
0.0075
0.008
0.0059
0.007
0.0046
0.310
0.403
0.294
Actual versus Simulation Predicted Temperature
Test 2 - Absorber
Test 3 - Absorber
21
21
21
19
19
19
17
17
17
15
15
15
Tray Number
13
13
11
13
Tray Number
Tray Number
Test 1 - Absorber
11
9
7
9
7
11
9
7
5
5
3
3
3
1
38
1
38
1
38
49
60
71
Temperature (°C)
49
60
71
Temperature (°C)
Actual temperature measurements
Simulated Temperatures
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82
5
49
60
Temperature (°C)
Significance of Temperature Profile
 Concern with Temperature Profile because
 higher and broader profile have corrosion implications
 outlet gas temperature increase load on downstream dehydration
equipment
 high temperature may limit capacity or cause plant to go off spec difficult to absorb CO2
» near equilibrium loading
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Tower Temperature Profiles
Broad temperature
profile throughout
Poor liquid
distribution
GAS/SPEC technical service
engineers use these temperature
scans of towers to troubleshoot
amine plant. This is a method
to monitor performance
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Options for More Capacity
 Customer wants more capacity out of the plant
 However CO2 level in inlet gas is rising!
 Option 1 - Continue to treat with MDEA
 Treat to just below 3% CO2 specification
 Option 2 - Upgrade to a Specialty Solvent
 Treat CO2 to low levels of < 1000 ppm
 then blend with untreated gas to meet 3% CO2 specification
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Max Capacity with MDEA
600000
Pipeline Max
Treated
Gas Flow, Nm3/h
500000
Bypassed
Combined
400000
300000
200000
100000
0
3.5
4
4.5
5
Inlet CO2, mol%
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5.5
6
6.5
Max Capacity with Specialty Solvent
Gas Flo w, Nm3/h
900000
800000
Treated
700000
Bypassed
Pipeline Max
600000
Combined
500000
400000
300000
200000
100000
0
3.5
4
4.5
5
Inle t CO2, mol%
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5.5
6
6.5
Results after Conversion
Flow to Absorber (Nm3/h)
Inlet CO2, mol%
Outlet CO2, mol%
Amine Flow, Nm3/h
MDEA
235500
4.29
1.54
227
CS-2010
232100
4.5
< 0.1
202
Max Total Gas
Capacity (Nm3/h)
446400
502200 
 Currently
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limited by capacity of downstream pipeline
Conclusions - Case 1
 Demonstrates use of simulation tool to
 accurately predict temperature and CO2 in the column.
 identify opportunities for optimization of existing plant
 make decision on how to best utilize assets for present and future
treating conditions
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Case Study 2
 Offshore natural gas application
 H2S and CO2 removal
 Simulations used to
 design original plant
 modify plant to adapt to changing process conditions
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Case 2 - Flow Diagram
TREATED GAS
REFLUX
CONDENSER
LEAN AMINE
REFLUX
ACCUMULATOR
REGEN
ABSORBER
FILTER TRAIN
FEED
AMINE
COOLER
REBOILER
RICH AMINE
LEAN /RICH
CROSS-EXCHANGER
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Original Design Treating Conditions
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Inlet Gas Flow (Nm3/h)
Inlet Gas Pressure (kPa)
Inlet Gas Temp (°C)
502200
7419
49
Gas Composition:
CO2 (mol%)
H2S (mol%)
3.25
1.35
Treated Gas Specification:
CO2 (mol%)
H2S (ppmv)
<1
<4
Key Design Decisions
 Prior to INEOS involvement, customer decided on
 30 tray absorber (3.35 meters diameter with 10 cm weir height)
 design based on generic MDEA
 plant was already designed with “Equilibrium Stage”-based simulator
 Use of 30 trays is unusual in an offshore application due to weight
consideration
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Simulation - Design Rate
Gas Flow (Nm3/h)
Feed Tray from Top
MDEA Conc. (wt% )
Circulation Rate (m3/h)
502200
30
50%
545
Treated Gas
CO2 (mol%)
H2S (ppmv)
0.92
< 1 ppm
Lean Loadings / Rich Loadings
H2S (mol/mol)
0.0002 / 0.13
CO2 (mol/mol)
0.005 / 0.23
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Variations operating conditions were also
simulated...
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Simulations for Changing Condition
 Limited heat source at certain times
 57% of design duty available
 Plant will operate at reduced rate
 Increased CO2 pickup at reduced rate
 How to operate plant to minimize CO2 pickup
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Alternatives for Operating at Reduced Rates
Scenario 1
502200 Nm3/h
Reboiler Duty = X
30 trays
CO2 Out = 0.92 mol%
Scenario 2
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30 trays
279000 Nm3/h
340 m3/h of 50wt% MDEA
Reboiler Duty = 0.57 X
CO2 Out = 0.59 mol%
19 trays
279000 Nm3/h
340 m3/h of 50 wt% MDEA
Reboiler Duty = 0.57X
CO2 Out = 0.99 mol%
Outcome of Simulations
 Feed points added to trays 30,
24, 19 to allow for flexibility
under changing conditions
Tray 30
ABSORBER
Tray 24
Tray 19
Feed
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Prior to Startup
 Plant needed lower CO2 level
 Minimize corrosion in downstream pipeline
 Old spec 1% CO2 ; New spec 1000 ppmv CO2
 In order to maximize CO2 removal, customer has 2 options
 Option 1 - Continue with MDEA
» Higher amine circulation rate, L/V
» Use all 30 trays
 Option 2 - Specialty amine solvent
» Treat with less trays and less circulation
 Customer decide to proceed startup with MDEA and then upgrade
to a specialty solvent.
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After Startup
 After startup, the plant experienced foaming
 Plant had difficulty treating at high capacity
 Not making the 1% CO2 spec with MDEA
 Problem was caused by
 Hydrocarbon coming into the plant
 High amine flow and high tray count required by MDEA seem to
worsen foaming problem
» operate with only 19 trays
» over-circulate to keep the CO2 level down
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Conversion to Specialty Solvent
 After operating with MDEA for 5 months, customer converted to
GAS/SPEC* CS-2000 solvent
 Running conversion.
 Now plant treating at full capacity of 450 MMSCFD
 Meeting < 1000 ppmv CO2 spec
 Only the bottom 19 trays were needed
 Reduction in foaming tendency
» better separation / filtration
» higher loading decrease HC solubility
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Conclusions - Case 2
 Ideally want to design a plant with fewer trays and higher rich
loadings
 to reduce capital cost
 to minimize hydrocarbon absorption
 Simulation used to determined alternative feed points to improve
plant flexibility
 Simulations helped adapt plant to new treating requirements with
a specialty solvent
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Case Study 3
 Natural gas plant
 plant faced with rising CO2 composition
 Originally 7.8 mol%
 CO2 is now over 10%
 Plant operation was unstable because high outlet CO2 caused
coldbox to freeze
 Goal is to increase capacity and stabilize plant operations
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Operating Conditions versus Simulated
Flow (Nm3/h)
Temperature (°C)
Pressure (kPa)
Inlet CO2 (mol%)
Actual CO2 Out (ppm)
Predicted CO2 Out (ppm)
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34600
11
4440
10.2
10
10
Lean Solvent
Flow (m3/h)
Temperature (°C)
Wt% GAS/SPEC CS-2020
82
48
50
Rich Solvent
Temperature (°C)
Predicted Temp (°C)
79 to 81
81
Operating Conditions versus Simulated
Flow (Nm3/h)
Temperature (°C)
Pressure (kPa)
Inlet CO2 (mol%)
Actual CO2 Out (ppm)
Predicted CO2 Out (ppm)
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34600
11
4440
10.2
10
10
Lean Solvent
Flow (m3/h)
Temperature (°C)
Wt% GAS/SPEC CS-2020
82
48
50
Rich Solvent
Temperature (°C)
Predicted Temp (°C)
79 to 81
81
Effect of Rate on CO2 Concentration
CO2 in Vapor, ppmv
1
10
100
1
3
5
Tray # (Top down)
7
9
11
13
15
17
19
21
23
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36800 Nm3/h
35700 Nm3/h
34600 Nm3/h
1000
10000
100000
Effect of Rate on CO2 Loadings
Loading, mol/mol
0.00
0.05
0.10
0.15
0.20
0.25
0.30
0.35
0.40
0.45
1
3
36800 Nm3/h
5
35700 Nm3/h
Tray # (Top down)
7
34600 Nm3/h
9
11
13
15
17
19
21
23
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Little CO2
absorption
Effect of Rate on Column Temperature
Temperature, °F
120
1
Tray # (Top down)
140
150
160
170
180
190
200
36800 Nm3/h
3
35700 Nm3/h
5
34600 Nm3/h
7
9
11
13
15
17
19
21
23
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130
210
Outcome - Case 3
 Plant personnel confirmed maximum rate of 34600 Nm3/h
 Client considering upgrading pumps and exchangers in order to
increase/maintain capacity as inlet CO2 rises
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Conclusions - Case 3
 MT Rate based simulation gave insight on effect of gas rate on
treat and temperature profile
 Allows plant to make informed decisions for future
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Conclusions
 Discussed the advantages of Mass Transfer Rate Based Simulation
over other simulation methods
 Case studies have shown
 accuracy of column temperature/composition prediction
 effect of mass transfer (tray count) on performance
 how to use simulator to design/modify in changing conditions
 the importance in considering temperature effects
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Acknowledgement
Ulises Cruz - INEOS
Andy Sargent - INEOS
Ralph Weiland - Optimized Gas Treating, Inc.
* GAS/SPEC and CS-2000 are trademarks of INEOS Oxide
TM
ProTreat is a trademark of Optimized Gas Treating, Inc.
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QUESTIONS?
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