Simulation of Amine Plants: Fundamental Models and Limitations

2 das 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 IAPG 2008

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History and Fundamentals of Amine Simulation Models

Improved simulation model are developed as solvent technologies evolve and amine plant become more complex….

TEA 1930 MEA DEA 1940 DGA 1950 MDEA 1960 DIPA 1970 Specialty Amine 1980 & Beyond….

Simple Models (Hand Calculations)

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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 IAPG 2008

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 CO 2 Lean Amine T = 130 F (50 C) Absorber Semi-lean Regenerator Rich Amine Syngas

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Reboiler

Definitions

 Vapor Liquid Equilibrium (VLE)  Defines the solution chemistry / chemical species present  model determines the maximum limit of H 2 S and CO 2 absorbed  Reaction Rates  Defines how quickly H 2 S and CO 2 are absorbed  H 2 S react instantaneously with amines and CO 2 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 H 2 S and CO 2 absorption IAPG 2008

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Vapor Liquid Equilibrium

ionization of water 2 H 2 O  H 3 O+ + OH dissociation of hydrogen sulfide H 2 O + H 2 S  H 3 O+ + HS dissociation of bisulfide H 2 O + HS  H 3 O+ + S 2 dissociation of carbon dioxide 2 H 2 O + CO 2  H 3 O+ + HCO 3 dissociation of bicarbonate H 2 O + HCO 3  H 3 O+ + CO 3 2 dissociation of protonated alkanolamine H 2 O + RR’R’’NH+  H 3 O+ + R’R’R’’N carbamate reversion to bicarbonate RR’NCOO- + H 2 O  RR’NH + HCO 3 (eq. 1) (eq. 2) (eq. 3) (eq. 4) (eq. 5) (eq. 6) (eq. 7)

Vapor Liquid Equilibrium

The equations governing chemical equilibria for equations 1 to 7 may be written as: K =  i (x i  i )  i (eq. 8) where, K is the equilibrium constant x i is the mole fraction of species i  i is the activity coefficient of species i  i is the stoichiometric coefficient IAPG 2008

Chemical Kinetics and Mass Transfer

IAPG 2008 N i = E i k° i,L a (y i interface - y i Bulk ) (eq 8) N I = transfer rate E i = enhancement factor (accounts for chemical reaction) k° i,L = Mass transfer coefficient a = interfacial area y i interface = acid gas conc. at interface (from Henry’s law) y i bulk = acid gas conc. in bulk (from VLE)

Evolution of Amine Simulation

 Pre 1980s - Equilibrium Stage Approach was only method  Uses simplified estimates  Estimate chemical species in solution  Uses tray efficiencies lump reaction and mass transfer rates  Adequate for simulation of MEA and DEA  Not accurate for MDEA, specialty solvents, and complex amine mixtures  Still used in many commercial simulators today  After 1980s - Mass Transfer Rate Based Approach  More rigorous  Calculate exact chemical species present in solution  Calculate reaction and mass transfer rates  Accurate for MEA, DEA, MDEA, and Specialty amine solvents  Can be extended to systems with heat stable salts and other components if data is available  Used in only a few simulators IAPG 2008

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) IAPG 2008  Commercially available ProTreat Simulator (Optimized Gas Treating Inc.)

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What is mass transfer rate-based?

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Example of GAS/SPEC APS Simulation

Most Basic Amine Simulation Models

Use tray efficiencies to account for •mass transfer •reaction rates Efficiencies are empirically derived Ignore tower internals •use equivalent stages to represent a given number of trays or packing height IAPG 2008 Tray Efficiency Material Balance

Simulation

Phase Equilibrium Predicted Plant Performance Properties

Mass Transfer Rate-based Simulations

More detailed approach Avoid the use of efficiencies Considers differences in reaction rates of H 2 S and CO 2 Consider Mass Transfer rate of absorption in different tower internals (trays, packing, etc.) Reaction Kinetics Mass Transfer (Tower internals) Properties Material Balance

Simulation

Phase Equilibrium Predicted Plant Performance IAPG 2008

Advantages of MT Rate-based Models

 Makes more rigorous and accurate prediction inside column  temperature profile  reaction or absorption zone  identify trouble area in the column » equilibrium limits » areas of corrosion concerns due to high temperatures

21 19 17 15 13 11 9 7 5 3 1 100

Example of Actual vs Predicted ProTreat Actual

110 120 130 Temperature (F) 140 150

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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.

 Difficult to locate exact temperature and composition of feeds and side draws

Stage 3 Stage 2 Top Tray Tray location?

Tray location?

Temp?

Composition?

Stage 1 Feed

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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

Case Study 1

 High pressure coal bed methane gas  requires CO 2 removal only  plant have ability to treat a portion of the natural gas and blend to meet 3 mol% CO2 spec IAPG 2008

Case 1 - Flow Diagram TREATED GAS LEAN AMINE FEED ABSORBER FILTER TRAIN AMINE COOLER RICH AMINE REGEN REFLUX CONDENSER LEAN /RICH CROSS-EXCHANGER REBOILER REFLUX ACCUMULATOR

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Benchmark Performance Tests Test 1

Raw Gas

Flow (Nm3/h) Temperature ( o C) Pressure (kPa) CO 2 (mol%)

235500 40 6881 4.29

Lean Solvent Flow (m3/h) Temp ( o C) Wt% MDEA

227 40 48

Test 2

232100 40 6881 4.29

186 43 48

Test 3

200900 40 6881 4.21

227 39 48 IAPG 2008

Performance Compared to Simulation

Solvent Rate (m3/h) Gas Rate (Nm3/h) Treated Gas Measured CO 2 Predicted CO 2 (mol%) (mol%) Lean Amine Actual mol/mol Predicted mol/mol Rich Amine Predicted mol/mol

Test 1

227 235500 1.54

1.57

0.008

0.0075

0.310

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Test 2

186 232100 1.98

1.95

0.008

0.0059

0.403

Test 3

227 200900 1.20

1.20

0.007

0.0046

0.294

Performance Compared to Simulation

Solvent Rate (m3/h) Gas Rate (Nm3/h)

Test 1

227 235500

Treated Gas Measured CO 2 Predicted CO 2 (mol%) (mol%)

Lean Amine Actual mol/mol Predicted mol/mol Rich Amine Predicted mol/mol

1.54

1.57

0.008

0.0075

0.310

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Test 2

186 232100

1.98

1.95

0.008

0.0059

0.403

Test 3

227 200900

1.20

1.20

0.007

0.0046

0.294

Actual versus Simulation Predicted Temperature

Test 1 - Absorber

21 19 17 15 13 11 9 7 5 3 1 38 49 60 71 Temperature (°C)

Test 2 - Absorber

21 19 17 15 13 11 9 7 5 3 1 38 49 60 71 Temperature (°C) 82

Test 3 - Absorber

21 19 17 15 13 11 9 7 5 3 1 38 49 60 Temperature (°C)

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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 CO 2 » near equilibrium loading IAPG 2008

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 IAPG 2008

Options for More Capacity

 Customer wants more capacity out of the plant  However CO 2 level in inlet gas is rising!

 Option 1 - Continue to treat with MDEA  Treat to just below 3% CO 2 specification  Option 2 - Upgrade to a Specialty Solvent  Treat CO 2 to low levels of < 1000 ppm  then blend with untreated gas to meet 3% CO 2 specification IAPG 2008

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Max Capacity with MDEA

600000 500000 400000 300000 200000 100000 0 3.5

4

Pipeline Max

Treated Bypassed Combined 4.5

5

Inlet CO2, mol%

5.5

6 6.5

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Max Capacity with Specialty Solvent

900000 800000 700000 600000 500000 400000 300000 200000 100000 0 3.5

Pipeline Max

4 4.5

5

Inle t CO2, mol%

5.5

Treated Bypassed Combined 6 6.5

Results after Conversion

Flow to Absorber (Nm3/h) Inlet CO 2 , mol% Outlet CO 2 , 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 limited by capacity of downstream pipeline IAPG 2008

Conclusions - Case 1

 Demonstrates use of simulation tool to  accurately predict temperature and CO 2 in the column.

 identify opportunities for optimization of existing plant  make decision on how to best utilize assets for present and future treating conditions IAPG 2008

Case Study 2

 Offshore natural gas application  H 2 S and CO 2 removal  Simulations used to  design original plant  modify plant to adapt to changing process conditions IAPG 2008

Case 2 - Flow Diagram TREATED GAS LEAN AMINE FEED ABSORBER FILTER TRAIN AMINE COOLER RICH AMINE REGEN REFLUX CONDENSER LEAN /RICH CROSS-EXCHANGER REBOILER REFLUX ACCUMULATOR

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Original Design Treating Conditions

Inlet Gas Flow (Nm3/h) Inlet Gas Pressure (kPa) Inlet Gas Temp (°C) Gas Composition: CO 2 (mol%) H 2 S (mol%) Treated Gas Specification: CO 2 (mol%) H 2 S (ppmv) 502200 7419 49 3.25

1.35

< 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 IAPG 2008

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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 CO 2 (mol%) H 2 S (ppmv) 0.92

< 1 ppm Lean Loadings / Rich Loadings H 2 S (mol/mol) CO 2 (mol/mol) 0.0002 / 0.13

0.005 / 0.23

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Variations operating conditions were also simulated...

Simulations for Changing Condition

 Limited heat source at certain times  57% of design duty available  Plant will operate at reduced rate  Increased CO 2 pickup at reduced rate  How to operate plant to minimize CO 2 pickup IAPG 2008

Alternatives for Operating at Reduced Rates

Scenario 1 502200 Nm3/h Reboiler Duty = X 30 trays CO 2 Out = 0.92 mol% Scenario 2 30 trays 279000 Nm3/h 340 m3/h of 50wt% MDEA Reboiler Duty = 0.57 X CO 2 Out = 0.59 mol% 19 trays 279000 Nm3/h 340 m3/h of 50 wt% MDEA Reboiler Duty = 0.57X

CO 2 Out = 0.99 mol% IAPG 2008

Outcome of Simulations

 Feed points added to trays 30, 24, 19 to allow for flexibility under changing conditions

ABSORBER Tray 30 Tray 24 Tray 19 Feed

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Prior to Startup

 Plant needed lower CO 2 level  Minimize corrosion in downstream pipeline  Old spec 1% CO 2 ; New spec 1000 ppmv CO 2  In order to maximize CO 2 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% CO 2 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 CO 2 level down IAPG 2008

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 CO 2 spec  Only the bottom 19 trays were needed  Reduction in foaming tendency » better separation / filtration » higher loading decrease HC solubility IAPG 2008

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 IAPG 2008

Case Study 3

 Natural gas plant  plant faced with rising CO 2 composition  Originally 7.8 mol%  CO2 is now over 10%  Plant operation was unstable because high outlet CO 2 coldbox to freeze caused  Goal is to increase capacity and stabilize plant operations IAPG 2008

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Operating Conditions versus Simulated

Flow (Nm3/h) Temperature ( ° C) Pressure (kPa) Inlet CO 2 (mol%) Actual CO 2 Out (ppm) Predicted CO 2 Out (ppm) Lean Solvent Flow (m3/h) Temperature (°C) Wt% GAS/SPEC CS-2020 Rich Solvent Temperature (°C) Predicted Temp (°C) 34600 11 4440 10.2

10 10 82 48 50 79 to 81 81

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Operating Conditions versus Simulated

Flow (Nm3/h) Temperature ( ° C) Pressure (kPa) Inlet CO 2 (mol%) Actual CO 2 Out (ppm) Predicted CO 2 Out (ppm) Lean Solvent Flow (m3/h) Temperature (°C) Wt% GAS/SPEC CS-2020 Rich Solvent Temperature (°C) Predicted Temp (°C) 34600 11 4440 10.2

10 10 82 48 50 79 to 81 81

13 15 17 19 21 23 1 1 9 11 3 5 7

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Effect of Rate on CO2 Concentration 10 CO2 in Vapor, ppmv 100 1000 10000 100000 36800 Nm3/h 35700 Nm3/h 34600 Nm3/h

19 21 23 11 13 7 9 15 17 3 5 1 0.00

0.05

Effect of Rate on CO2 Loadings 0.10

0.15

Loading, mol/mol 0.20

0.25

0.30

0.35

0.40

36800 Nm3/h 35700 Nm3/h 34600 Nm3/h 0.45

Little CO2 absorption

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Effect of Rate on Column Temperature

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17 19 21 23 11 13 7 9 15 1 120 3 5 130 140 150 Temperature, °F 160 170 180 190 200 36800 Nm3/h 35700 Nm3/h 34600 Nm3/h 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 CO 2 rises IAPG 2008

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 IAPG 2008

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 IAPG 2008

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?