Contents
Cover
Title page
Copyright page
Preface
Introduction
Part I: Carbon Capture and Storage
Chapter 1: Carbon Capture Storage Monitoring (“CCSM”)
1.1 Introduction
1.2 State of the Art Practice
1.3 Marmot’s CCSM Technology
1.4 Principles of Information Analysis
1.5 Operating Method
1.6 Instrumentation and Set up
Abbreviations
References
Chapter 2: Key Technologies of Carbon Dioxide Flooding and Storage in China
2.1 Background
2.2 Key Technologies of Carbon dioxide Flooding and Storage
2.3 Existing Problems and Technical Development Direction
Chapter 3: Mapping CCUS Technological Trajectories and Business Models: The Case of CO2 -Dissolved
3.1 Introduction
3.2 CCS and Roadmaps: From Expectations to Reality …
3.3 CCS Project Portfolio: Between Diversity and Replication
3.4 Going Beyond EOR: Other Business Models for Storage?
3.5 Coupling CCS and Geothermal Energy: Lessons from the CO2 -DISSOLVED Project Study
3.6 Conclusion
Acknowledgements
References
Chapter 4: Feasibility of Ex-Situ Dissolution for Carbon Dioxide Sequestration
4.1 Introduction
4.2 Methods to Accelerate Dissolution
4.3 Discussion and Conclusions
Acknowledgments
References
Part II: EOR
Chapter 5: CO2 Gas Injection as an EOR Technique – Phase Behavior Considerations
5.1 Introduction
5.2 Features of CO2
5.3 Miscible CO2 Drive
5.4 Immiscible CO2 Drives and Density Effects
5.5 Asphaltene Precipitation Caused by Gas Injection
5.6 Gas Revaporization as EOR Technique
5.7 Conclusions
List of Symbols
References
Appendix A Reservoir Fluid Compositions and Key Property Data.
Chapter 6: Study on Storage Mechanisms in CO2 Flooding for Water-Flooded Abandoned Reservoirs
6.1 Introduction
6.2 CO2 Solubility in Coexistence of Crude Oil and Brine
6.3 Mineral Dissolution Effect
6.4 Relative Permeability Hysteresis
6.5 Effect of CO2 Storage Mechanisms on CO2 Flooding
6.6 Conclusions
References
Chapter 7: The Investigation on the Key Hydrocarbons of Crude Oil Swelling via Supercritical CO2
7.1 Introduction
7.2 Hydrocarbon Selection
7.3 Experiment Section
7.4 Results and Discussion
7.5 Conclusions
Acknowledgments
Nomenclature
References
Chapter 8: Pore-Scale Mechanisms of Enhanced Oil Recovery by CO2 Injection in Low-Permeability Heterogeneous Reservoir
8.1 Introduction
8.2 Experimental Device and Samples
8.3 Experimental Procedure
8.4 Quantitative Analysis of Oil Recovery in Different Scale Pores
8.5 Conclusions
Acknowledgments
References
Part III: Data – Experimental and Correlation
Chapter 9: Experimental Measurement of CO2 Solubility in a 1 mol/kgw CaCl2 Solution at Temperature from 323.15 to 423.15 K and Pressure up to 20 MPa
9.1 Introduction
9.2 Literature Review
9.3 Experimental Section
9.4 Results and Discussion
9.5 Conclusion
Acknowledgments
References
Chapter 10: Determination of Dry-Ice Formation during the Depressurization of a CO2 Re-Injection System
10.1 Introduction
10.2 Thermodynamics
10.3 Case Study
10.4 Conclusions
Chapter 11: Phase Equilibrium Properties Aspects of CO2 and Acid Gases Transportation
11.1 Introduction
11.2 Experimental Work and Description of Experimental Setup
11.3 Models and Correlation Useful for the Determination of Equilibrium Properties
11.4 Presentation of Some Results
11.5 Conclusion
Acknowledgments
References
Chapter 12: Thermodynamic Aspects for Acid Gas Removal from Natural Gas
12.1 Introduction
12.2 Thermodynamic Models
12.3 Results and Discussion
12.4 Conclusion and Perspectives
Acknowledgements
References
Chapter 13: Speed of Sound Measurements for a CO2 Rich Mixture
13.1 Experimental Section
13.2 Results and Discussion
13.3 Conclusion
References
Chapter 14: Mutual Solubility of Water and Natural Gas with Different CO2 Content
14.1 Introduction
14.2 Experimental
14.3 Thermodynamic Model
14.4 Results and Discussion
14.5 Conclusion
Acknowledgement
References
Chapter 15: Effect of SO2 Traces on Metal Mobilization in CCS
15.1 Introduction
15.2 Experimental
15.3 Results and Discussion
15.4 Conclusions
Acknowledgements
References
Chapter 16: Experiments and Modeling for CO2 Capture Processes Understanding
16.1 Introduction
16.2 Chemicals and Materials
16.3 Vapor-Liquid Equilibria
16.4 Speciation at Equilibrium
Acknowledgment
References
Part IV: Molecular Simulation
Chapter 17: Kinetic Monte Carlo Molecular Simulation of Chemical Reaction Equilibria
References
Chapter 18: Molecular Simulation Study on the Diffusion Mechanism of Fluid in Nanopores of Illite in Shale Gas Reservoir
18.1 Introduction
18.2 Models and Simulation Details
18.3 Results and Discussion
18.4 Conclusions
Acknowledgements
References
Chapter 19: Molecular Simulation of Reactive Absorption of CO2 in Aqueous Alkanolamine Solutions
References
Part V: Processes
Chapter 20: CO2 Capture from Natural Gas in LNG Production. Comparison of Low-Temperature Purification Processes and Conventional Amine Scrubbing
20.1 Introduction
20.2 Description of Process Solutions
20.3 Methods
20.4 Results and Discussion
20.5 Conclusions
Nomenclature
References
Chapter 21: CO2 Capture Using Deep Eutectic Solvent and Amine (MEA) Solution
21.1 Experimental Section
21.2 Results and Discussion
21.5 Conclusion
References
Chapter 22: The Impact of Thermodynamic Model Accuracy on Sizing and Operating CCS Purification and Compression Units
22.1 Introduction
22.2 Thermodynamic Systems in CCUS Technologies
22.3 Operating Conditions of Purification and Compression Units
22.4 Quality Specifications of CO2 Capture Flows
22.5 Cubic Equations of State for CCUS Fluids
22.6 Influence of EoS Accuracy on Purification and Compression Processes
22.7 Purification by Liquefaction
22.8 Purification by Stripping
22.9 Compression
22.10 Conclusions
Nomenclature and Acronyms
References
Index
End User License Agreement
Guide
Cover
Copyright
Contents
Begin Reading
List of Illustrations
Chapter 1
Figure 1.1 Phase Diagram CO2 . (Source: www.chemistry-blog.com).
Figure 1.2 Principle of the ULF-PSSM Analysis.
Figure 1.3 Frequency Conversion – Stochastic Resonances – Spectral Anomalies and SLSE.
Figure 1.4 Signal – Information Flow.
Figure 1.5 Forensic Data Base.
Figure 1.6 Schematic Process Flow.
Figure 1.7 Processing Hierarchy.
Figure 1.8 ULF Signal Converter Pat. Application [10].
Figure 1.9 SPIDER directional antenna.
Figure 1.10 Terminal Array (symbolic).
Chapter 3
Figure 3.1 Levelized cost of electricity estimates of the Boundary Dam retrofit by cost category compared to a base load NGCC plant. Source: V. Clark, 2015 [16].
Figure 3.2 Schematic view of the CO2 -DISSOLVED concept [17]. * Technology patented by Pi-innovation, Inc. (USA)
Chapter 4
Figure 4.1 Storage security depends on a combination of physical and geochemical trapping. Over time, the physical process of residual CO2 trapping and geochemical processes of solubility trapping and mineral trapping increase (IPCC, 2005).
Figure 4.2 Schematics of conventional (a) and suggested engineering approach (b).
Figure 4.3 Schematic drawing of reservoir geometry. Brine injectors in all cases are located directly below the cap-rock.
Figure 4.4 Dissolved fraction as a function of time.
Figure 4.5 Schematics of ex-situ dissolution.
Figure 4.6 Turbulent droplet dissolution.
Figure 4.7 A droplet in a cell of neighbors.
Figure 4.8 Diffusive droplet dissolution.
Chapter 5
Figure 5.1 Vapor pressure curves for CO2 and light hydrocarbons simulated using SRK equation of state.
Figure 5.2 Recovery curve from slim tube simulation at 121 °C with CO2 injection gas.
Figure 5.3 Recovery curve from slim tube simulation at 121 °C with hydrocarbon injection gas.
Figure 5.4 Density profiles from slim tube simulation at 121 °C and 210 bara close to miscibility with CO2 as injection gas. The plot is made for 263 gas injection steps out of 1000.
Figure 5.5 Density profiles from slim tube simulation at 121 °C and 330 bara close to miscibility with hydrocarbon injection gas. The plot is made for 500 gas injection steps out of 1000.
Figure 5.6 K-factor profiles from slim tube simulation at 121 °C and 210 bara close to miscibility with CO2 as injection gas. The plot is made for 251 gas injection steps out of 1000.
Figure 5.7 Recovery curve from slim tube simulation for Oil B at 48 °C with CO2 injection gas.
Figure 5.8 Phase envelope for mixture of Oil B and 200 mole% added CO2 .
Figure 5.9 Swelling curve and asphaltene Px-diagram for Oil A in Table A6 at 56 °C with CO2 injection gas.
Figure 5.10 Asphaltene Px-diagram for Oil A in Table A6 at 56 °C with C1 injection gas.
Figure 5.11 Asphaltene Px-data with N2, C1, and CO2 injection gases [19].
Chapter 6
Figure 6.1 The diagram of CO2 in oil-water partition coefficient measurement.
Figure 6.2 Measurement of CO2 in oil-water partition coefficient.
Figure 6.3 The ratio of CO2 dissolution in oil and brine at different water saturation values.
Figure 6.4 Three types of sandstone sample.
Figure 6.5 Erosion rate of mineral dissolution for carbonate water.
Figure 6.6 Permeability change curve with injection time of carbonate water.
Figure 6.7 NMR test before and after carbonate water dissolution.
Figure 6.8 CT scanning image before and after carbonate water dissolution.
Figure 6.9 Relative permeability hysteresis in CO2 flooding.
Figure 6.10 Relationship between CO2 retention factor and dimensionless pressure.
Chapter 7
Figure 7.1 Schematic diagram of JEFRI PVT apparatus.
Figure 7.2 Crabon number versus swelling factor of n-alkanes + CO2 at 50 °C and 30 MPa.
Figure 7.3 CO2 molar fraction versus swelling factor of C6 (diferent molecular strcture) + CO2 at 50 °C and 30 MPa.
Figure 7.4 Relationship of swelling factor versus mass density at 50 °C and 30 MPa.
Figure 7.5 Relationship of swelling factor versus molar mass (molecular weight) at 50 °C and 30 MPa.
Figure 7.6 Relationship of swelling factor versus molar density at 50 °C and 30 MPa.
Figure 7.7 Swelling factor of hydrocarbon with different carbon number and molecular structure at 50 °C and 30 MPa.
Chapter 8
Figure 8.1 Experimental device picture.
Figure 8.2 Inner model structure picture.
Figure 8.3 Magnification of the inner model.
Figure 8.4 Image of different scale pores at the pressure of 6–8 MPa.
Figure 8.5 Image of different scale pores at the pressure of 9–9.4 MPa.
Figure 8.6 Image of different scale pores at the pressure of 9.5–9.7 MPa.
Figure 8.7 Image of different scale pores at the pressure of 9.6 MPa.
Figure 8.8 Image of different scale pores at the pressure of 9.7 MPa.
Figure 8.9 Magnification Image of different scale pores at the pressure of 9.8 MPa.
Figure 8.10 The oil recovery in different scale pores under different interfacial tension conditions.
Chapter 9
Figure 9.1 Description of the apparatus.
Figure 9.2 Titration graph: the black line is the pH curve, the grey line is the conductivity curve.
Figure 9.3 Solubility of carbon dioxide in 1 mol/kgw CaCl2 solution between 1 and 20 MPa at 323.15K: ●, this study; ▲, Zhao et al. [22]; 373.15 K: ●, this study; ▲, Zhao et al. [22]; ♦, Tong et al. [20]; ■, Prutton and Savage[12]; 423.15 K: ○, this study; Δ, Zhao et al. [22]; ◊, Tong et al. [20].
Chapter 10
Figure 10.1 VMG Phase Diagram (P-H) for pure CO2 distributed in GPSA Data Book.
Figure 10.2 VMG Phase Diagrams for mixtures CO2 -CH4 with different compositions.
Figure 10.3 Study of the effect of a third component (H2 S) on equilibrium of mixtures CO2 –CH4 –H2 S.
Figure 10.4 Phase Envelopes of gas streams involved in the study.
Figure 10.5 P-T Depressurization curves.
Figure 10.6 Amount of CO2 formed during depressurization.
Chapter 11
Figure 11.1 Phase diagram for different CO2 – N2 mixtures () 99.99%mol CO2 +0.01%mol N2 . () 90%mol CO2 +10%mol N2 . () 80%mol CO2 +20%mol N2 , Hajiw [3].
Figure 11.2 Acid gas compression conditions. Solid lines: compression steps. Dotted lines: Pressure – Temperature envelope of dry acid gas (gas (H2 S/CO2 : 22/78) from Kopperson et al. [5]. Broken dotted lines: P – T envelope of Mixture AG: AL (3:1) (H2 S/CO2 = 25/75). Dashed lines: P – T envelope of Mixture (H2 S/CO2 = 25/75) without aromatics. Extract from GPA Research report Hajiw et al. [6].
Figure 11.3 Phase diagrams according to van Konynenburg and Scott classification [7].
Figure 11.4 PT envelopes of mixture 1 (solid line) and mixture 2 (dashed line). (●): predicted mixture 1 critical point, (▲): predicted mixture 2 critical point.
Figure 11.5 Schematic diagram of the VLE equipment: EC, equilibrium cell; LB, liquid bath; LS, liquid sampler; PP, platinum resistance probe; PT, pressure transducer; TR temperature regulator, VS, vapor sampler; VP, vacuum pump. Extract from Gonsalez-Perez [X].
Figure 11.6 Plot showing an example of (a) bubble point determination from plot of change in cell pressure versus volume and (b) dew point determinations from equilibrium step-heating data using the isochoric method.
Figure 11.7 (P, x, y) phase diagrams for the N2 + NO binary system at –146, –153.6 (data from Scheunemann and Wagner (1985)), –159.3 °C (data from Scheunemann and Wagner [18]) and 167.5°C.
Figure 11.8 New VLE data and calculations (solid line) using the PR EoS for the NO + SO2 binary system at 273.07 K.
Figure 11.9 Pressure-composition diagram of the Ar + H2 S system using the PR EoS with W-S mixing rules and NRTL activity coefficient model at 273.01, 298.00 and 322.96 K.
Figure 11.10 Pressure – composition diagram of the CO2 (1) + H2 S (2) system. This work: (▲), T = 258.41 K (○), T = 273.15 K (●), T = 293.47 K (♦), T = 313.02 K. (○), T =273.15 K from [23] (●)) T = 293.15 K from [23] (♦), T = 313.15 K from [23] (◊), T = 333.15 K from [7] (Δ), T = 333.15 K from [24] (*), T = 348.15 K from [23]. Solid lines: prediction using PPR78 model.
Figure 11.11 Pressure composition phase diagram of the CO2 (1) + SO2 (2) binary system. (▲) 333.15 K, (●): 263.15 K. (×): experimental critical point from Caubet [25]. Solid lines: calculated using PR model with kij = 0.0274, dashed line: corresponding mixture critical point line.
Figure 11.12 New VLE data and calculations (solid line) using the PR EoS with kij determined at each temperature for the N2 (1) + CO (2) system at: (a) 95.10 K (Δ), 100.02 K (×), 110.07 K (○). (b) 120.05 K (Δ), 127.07 K (×), 130.07 K (○). Dotted line: predicted mixture critical line using the PR EoS and an average binary interaction parameter value for temperatures above critical temperature of nitrogen.
Figure 11.13 New VLE data and calculations (solid line) using the PR EoS at 283.02 and 263.17 K.
Figure 11.14 Pressure composition phase diagram of the CO2 (1) + NO2 (2) binary system at 262.5 (Δ) and 273.5 K (○). Solid line: PR EoS prediction.
Figure 11.15 Experimental and predicted bubble/dew points for MIX 1 (Model predictions are independent from experimental data, Blue and Red Lines: PR-EoS with tuned kij; Dotted lines: PR-EoS with kij=0).
Chapter 12
Figure 12.1 Schematic flow diagram of acid gas removal process [3].
Figure 12.2 Association schemes utilized in this work (a) water, (b) aromatic hydrocarbons and mercaptans c) CO2 /H2 S, d) alkanolamines according to Rodriguez et al. [16].
Figure 12.3 Deviations of hydrocarbon and mercaptan solubility in aqueous alkanolamine solution. C1 = methane, C2 = ethane, C3 = propane, C4 = butane, C5 = pentane, C6 = hexane, B = benzene, T = toluene, MM = methyl mercaptan, EM = ethyl mercaptan.
Figure 12.4 Solubility of methane at 10 MPa in function of temperature.
Figure 12.5 Prediction of total pressure of CO2-MDEA-water ternary system with 25 wt% MDEA. solid lines: PR-CPA EoS, Dotted Lines: DM model. (♦)=298 K, (▲)=313 K, (■)=348 K from Sidi-Boumedine et al. [17].
Figure 12.6 Prediction of vapor phase composition of MEA and water for CO2 -MEA-water ternary system with 30 wt % MEA at 333K Solid line: ywater , dashed line: yMEA , (▲) = ywater , (♦) = yMEA , from Hilliard [18].
Figure 12.7 Prediction of liquid phase electrolytes speciation of CO2 -MEA-water ternary system with 30 wt % MEA at 313.15K. Solid line: HCO3 –1 , dashed line: MEACOO-, dotted line: MEA + MEAH +, (Δ)=HCO3 –1 ,(◊)= MEACOO– (○)=MEA+MEAH+ from Hilliard [18], (▲) = HCO3 -1 ,(♦) = MEACOO– (●) = MEA + MEAH + from Bottinger et al. [19].
Figure 12.8 Prediction of enthalpy of absorption of CO2 in a 30 wt% solution of MEA. Lines: PR-CPA EoS prediction, symbols: experimental data from Kim et al. [20]. (a) T = 313 K, (b) T = 393 K
Figure 12.9 Prediction with PR-CPA EoS for H2 S and CO2 partial pressure of H2 S and CO2 mixture in a 15 wt% MEA solution. (Δ) = PCO2 , (♦) = PH2S , from Muhlbauer and Monaghan [22].
Figure 12.10 Prediction of vapor phase composition for CO2 -MDEA-water-methane-EM system, (▲) = yEM ,(♦) = yCO2 (●) = yCH 4 from Eric et al. [23].
Chapter 13
Figure 13.1 Measured and predicted speed of sound in pure CO2 for different isotherms; 323.28 K (○), 347.09 K (◊), 369.40 K (Δ), 397.28 K (×), 415.90 K (□) and Span & Wagner EoS predictions (–).
Figure 13.2 Measured and predicted speed of sound in the sample mixture for different isotherms; 323.37 K (○), 347.01 K (◊), 369.45K (ρ), 397.28 K (×), 415.89 K (□) and GERG predictions (–).
Chapter 14
Figure 14.1 Flow chart for the test of water vapor content. High-pressure displacement pump; Sample container; Liquid nitrogen cold trap; Gas-water separator; Gasometer; Electronic balance; Gas chromatography; Gas and water samples; Oven.
Figure 14.2 Association schemes for water.
Figure 14.3 The compositions of CO2 in liquid phases at 308 K.
Figure 14.4 The compositions of H2 O in vapor phases at 308 K.
Figure 14.5 The compositions of CO2 in liquid phases at 373 K.
Figure 14.6 The compositions of H2 O in vapor phases at 373 K.
Figure 14.7 The compositions of CO2 in liquid phases at 473 K.
Figure 14.8 The compositions of H2 O in vapor phases at 473 K.
Figure 14.9 The compositions of CO2 in liquid phases at 308 K.
Figure 14.10 The compositions of H2 O in vapor phases at 308 K.
Figure 14.11 The compositions of CO2 in liquid phases at 373 K.
Figure 14.12 The compositions of H2 O in vapor phases at 373 K.
Figure 14.13 The compositions of CO2 in liquid phases at 473 K.
Figure 14.14 The compositions of H2 O in vapor phases at 473 K.
Figure 14.15 The compositions of CO2 in liquid phases at 308 K.
Figure 14.16 The compositions of H2 O in vapor phases at 308 K.
Figure 14.17 The compositions of CO2 in liquid phases at 373 K.
Figure 14.18 The compositions of H2 O in vapor phases at 373 K.
Figure 14.19 The compositions of CO2 in liquid phases at 473 K.
Figure 14.20 The compositions of H2 O in vapor phases at 473 K.
Figure 14.21 The solubility of natural gas with different CO2 content in water phase.
Figure 14.22 The content of gaseous water in natural gas.
Chapter 15
Figure 15.1 Experimental set-up.
Figure 15.2 Autoclave reactor.
Figure 15.3 Effect of the SO2 traces on the pH. In parentheses the gas phase of the experiment, (CO2 ) in the case of CO2 atmosphere and (SO2 ) in the case of CO2 with SO2 traces.
Figure 15.4 Concentration of calcium and sulphates in brine. In parentheses the gas phase of the experiment, (CO2 ) in the case of CO2 atmosphere and (SO2 ) in the case of CO2 with SO2 traces.
Figure 15.5 Predominance diagram of calcium species at experimental conditions using pure CO2 . Red cross indicates the experimental data.
Figure 15.6 Predominance diagram of calcium species at experimental conditions in presence of SO2 traces. Green circles indicate the experimental data.
Figure 15.7 Evolution of metal concentration in brine. In parentheses the gas phase of the experiment, (CO2 ) in the case of CO2 atmosphere and (SO2 ) in the case of CO2 with SO2 traces.
Figure 15.8 Predominance diagram of strontium species at experimental conditions in the case with only CO2 . [SO4 2 ] = 20 mM. Red crosses indicate the experimental data.
Figure 15.9 Predominance diagram of strontium species at experimental conditions in the case with SO2 traces. [SO4 2 ] = 140 mM. Green circles indicate the experimental data.
Figure 15.10 Predominance diagram of manganese species at experimental conditions in the case with only CO2 . [SO4 2 ] = 20 mM. Red crosses for pure CO2 and green circles for CO2 + SO2 .
Figure 15.11 Predominance diagram of copper species at experimental conditions. The differences in the diagram from considering the SO2 traces were negligible. Red crosses for pure CO2 and green circles for CO2 + SO2 .
Figure 15.12 Predominance diagram of zinc species at experimental conditions. The differences in the diagram from considering the SO2 traces were negligible. Red crosses for pure CO2 and green circles for CO2 + SO2 .
Figure 15.13 Predominance diagram of vanadium species at experimental conditions. The differences in the diagram from considering the SO2 traces were negligible. Red crosses for pure CO2 and green circles for CO2 + SO2 .
Figure 15.14 Predominance diagram of lead species at experimental conditions. The differences in the diagram from considering the SO2 traces were negligible. Red crosses for pure CO2 and green circles for CO2 + SO2 .
Chapter 16
Figure 16.1 Schematic representation of the CO2 separation process with alcanolamine (a – HiCAPTTM ) and Demixing amine (b – DMXTM ) based solvent.
Figure 16.2 MEA Triangle.
Figure 16.3 (a) temperature profile of the calorimeter; (b) thermograms obtained at different pressures for pure MEA. The thermograms are shifted one from the other for better visualization.
Figure 16.4 Vapor pressure of MEA versus temperature. ●: our results; ■: Touhara et al. [14]: *: Nath et al. [15] ○: Dow Chemical [16];___: Antoine equation from Kim et al. [17].
Figure 16.5 (a) temperature profile of the calorimeter; (b) thermograms obtained at different compositions for {MEA-water} mixtures, at atmospheric pressure. The thermograms are shifted one from the other for better visualization.
Figure 16.6 liquid-vapor equilibrium curves obtained for the binary mixture water + MEA at atmospheric pressure. ▲: data obtained by DSC; ρρ: from Cai et al. [23]. Red and blue line are model predictions using the method described above.
Figure 16.7 Overall experimental set-up for preparation of solutions containing known quantities of dissolved gas.
Figure 16.8 1 H and 13 C NMR spectra obtained at 25°C for MEA + Water + CO2 mixtures.
Figure 16.9 speciation in MEA + Water + CO2 mixtures, versus loading charge. Points: NMR results; line: model prediction.
Chapter 17
Figure 17.1 Gibbs energy versus extent of reaction. Simulation results have been fitted to a cubic equation (with standard deviation of 0.71 kJ/mol), as an aid to the eye.
Chapter 18
Figure 18.1 4a × 2b × 1c supercell model of illite.
Figure 18.2 Models of fluid molecules and illite.
Figure 18.3 Velocity autocorrelation function of CO2 .
Figure 18.4 Variation trend of CO2 self diffusion coefficient at different molar ratios.
Figure 18.5 Variation trend of CO2 self diffusion coefficient at different formation depths.
Figure 18.6 Density distribution of CO2 at formation depth of 3 km.
Figure 18.7 Density distribution of CO2 at mole ratio of 3.
Figure 18.8 RDF between CO2 and O in the pore wall at formation depth of 3 km.
Figure 18.9 RDF between CO2 and O in the pore wall at mole ratio of 3.
Chapter 20
Figure 20.1 Process layout of the Ryan-Holmes process (blue arrows denote cooling energy streams; red arrows denote heat energy streams; green arrows denote mechanical energy streams).
Figure 20.2 Process layout of the dual pressure low-temperature distillation process (blue arrows denote cool energy streams; red arrows denote heat energy streams; green arrows denote mechanical energy streams).
Figure 20.3 Process layout of the MDEA scrubbing process (blue arrows denote cool energy streams; red arrows denote heat energy streams; green arrows denote mechanical energy streams).
Figure 20.4 Distribution of the energy consumptions by quality for the Ryan-Holmes process (RH), the dual pressure low-temperature process (DPLT), and the MDEA scrubbing process (MDEA).
Figure 20.5 Distribution of the energy consumptions per process section for the Ryan-Holmes process (RH), the dual pressure low-temperature process (DPLT), and the MDEA scrubbing process (MDEA).
Chapter 21
Figure 21.1 Experimental apparatus for CO2 absorption by solvent.
Figure 21.2 Solubility of CO2 in aqueous solution of MEA (30 wt %) at 298.15 K. ♦, this work; ○, Ref. (1).
Figure 21.3 Solubility of CO2 in aqueous solution of MEA (30% wt) at 313.15 K. ♦, this work; ○, Ref 1; ▲, Ref 2; ×, Ref 3.
Figure 21.4 Solubility of CO2 in aqueous solution of MEA (30 wt %) at 333.15 K. ♦, this work; *, Ref 1; ▲, Ref 2; ×, Ref. 3.
Figure 21.5 Solubility of CO2 in the solution DES (1 ChCl: 2 EG) + MEA (30 wt% of DES) at three different temperatures: ◊, 298.15; □, 313.15; ○, 333.15 K.
Figure 21.6 Solubility of CO2 at 313 K in the solution DES (1 ChCl: 2 EG): □, from ref. (4) and DES + MEA (30 wt% of DES): ×, from the present study.
Figure 21.7 Comparison of CO2 solubility at 313.15 K, in MEA 30 wt% + DES (1 ChCl: 2 EG): ♦, this work, with those in MEA 30 wt% aqueous solutions: ×, Ref. (1); □, Ref.(2); Δ, Ref. (3).
Figure 21.8 Comparison of the CO2 solubility at 333.15 K, in MEA 30 wt% + DES (1 ChCl: 2 EG): ♦, this work, with those in MEA 30 wt% aqueous solutions: ×, Ref. (1); □, Ref.(2); Δ, Ref. (3).
Chapter 22
Figure 22.1 Typical CO2 CPU. Double-stages, auto-refrigerated flash separation configuration.
Figure 22.2 Single stage separation by liquefaction
Figure 22.3 Schematics of stripping column.
Figure 22.4 Two graphical representations of the equilibrium compositions on each plate of the column (with a fixed R=0.3), relative to two different thermodynamic models: solid lines represent results for the classical optimized PR while the dotted lines represent results for the PR equation of state with the EoS/ mixing rule. The blue line is the operating line (which is the same for the two considered cases); black lines are the equilibrium curves defined by the two models; broken red lines connect the points, resulting from the iterative process briefly described above, from the equilibrium to the operating line. These broken lines start from the point (xO2 , yO2 ) that characterizes the liquid and vapor phase composition of the feed (marked either with the symbol “◊” or with “○” to distinguish between the two models) and end to the plate that guarantees the achievement of xO2 lower than 100 ppm.
Figure 22.5 High pressure compression unit of the CPU.
Figure 22.6 Phase envelopes of mixtures which compositions are reported in Table 22.15 (figure (a): ID-3; figure (b): ID-8). Three phase envelopes are reported in each figure, each one relative to the application of a different model: (– –) PR + EoS/ mixing rule; (- · -) PR with kij = 0; (- -) PR with optimal kij .
List of Tables
Chapter 1
Table 3.1 Number of large-scale CCS projects by lifecycle stage, industry and technology used, data from Global CCS Institute database [13], own calculations.
Table 3.2 Number of small-scale projects (pilot and demonstrators) by sector, at different stage of development. F means Full chain; C, project focus on capture; S: project focus on storage. Data from Global CCS Institute database [13], own calculations.
Chapter 2
Table 5.1 Density of gas components at 500 bara and 100 °C simulated using volume corrected SRK equation of state.
Table 5.2 Simulated tie-line MMP’s and percent vaporizing drive for four injections gases at 121 °C.
Table 5.3 Key data for produced fluids from the CO2 slim tube simulation at 121 °C and 210 bara.
Table A1 Reservoir fluid of Negahban et al. [11] characterized for the volume corrected PR equation of state.
Table A2 Non-zero binary interaction coefficients for use with the fluid composition in Table A1
Table A3 Key property data of the reservoir fluids considered in this work.
Table A4 Oil B reservoir fluid of Lindeloff et al. [16] characterized for the volume corrected SRK equation of state.
Table A5 Non-zero binary interaction parameters for the EoS model for Oil B in Table A4
Table A6 Oil A reservoir fluid of Lindeloff et al. [16] characterized for the volume corrected SRK equation of state
Table A7 Non-zero binary interaction parameters for the EoS model for Oil A in Table A6
Chapter 6
Table 6.1 The mineral compositions of target rock sample.
Chapter 7
Table 7.1 Informations for hydrocarbon components in experiments.
Table 7.2 hexane-CO2 system for example.
Table 7.3 Experimental results for hexane-CO2 system with different molar fraction in 50 °C.
Table 7.4 Swelling factors and hydrocarbon properties at 50 °C and 30 MPa.
Chapter 9
Table 9.1 Literature experimental data for CO2 -H2 O-CaCl2 system.
Table 9.2 Experimental data of CO2 solubility in a 1 mol/kgw CaCl2 solution at 323.15, 373.15 and 423.15 K.
Chapter 11
Table 11.1 State of the art concerning existing VLE data of each binary system. ND: No Data NIST, CD: Confidential Data CTP, CR: Chemical Reaction, Cryo: Cryogenic measurement, DWA: data widely available, NEW: new set of data determined in the context of the Joint Industrial project between Heriot Watt University and CTP MinesParisTech.
Chapter 13
Table 13.1 Composition of the mixture used in this work.
Chapter 14
Table 14.1 The more fraction of natural gas with different CO2 content (mol %).
Table 14.2 Formation water composition.
Table 14.3 CPA parameters for CO and water involved in this study (Obtained from literature).
Table 14.4 The AAD of phase equilibria calculation for XCO2 and YH2O .
Table 14.5 CPA parameters for hydrocarbon components considered in this work.
Table 14.6 The AAD% between experimental and calculated data for gases in water-rich phase.
Table 14.7 The AAD% between experimental and calculated data for water in gas-rich phase.
Chapter 15
Table 15.1 Metal composition of sandstone (mol L–1 ).
Table 15.2 Brine composition (mol L–1 ).
Chapter 16
Table 16.1 MEA Triangle: list of the amines with transferable models and FF.
Chapter 17
Table 17.1 Case 1 – Convergence for initial state corresponding to ξ = 0.060.
Table 17.2 Case 2 – Convergence for initial state corresponding to ξ = 0.995.
Chapter 20
Table 20.1 Values of the parameters used in the net equivalent CH4 analysis.
Table 20.2 Amount of CH4 equivalent to the cooling and heating duties required in the Ryan-Holmes process shown in Figure 20.1.
Table 20.3 Amount of CH4 equivalent to the powers required (by pumps) or provided (by the expander) in the Ryan-Holmes process shown in Figure 20.1.
Table 20.4 Amount of CH4 equivalent to the cooling and heating duties required in the dual pressure low-temperature distillation process shown in Figure 20.2.
Table 20.5 Amount of CH4 equivalent to the powers required (by the pump) or provided (by the expander) in the dual pressure low-temperature distillation process shown in Figure 20.2.
Table 20.6 Amount of CH4 equivalent to the cooling and heating duties required in the MDEA scrubbing process shown in Figure 20.3.
Table 20.7 Amount of CH4 equivalent to the powers required (by compressors) or provided (by the expander) in the MDEA scrubbing process shown in Figure 20.3.
Table 20.8 Percentages of the total produced methane required to supply energy to the different investigated processes for LNG production.
Chapter 22
Table 22.1 Characteristics of CO2 flows captured by post – combustion technologies.
Table 22.2 Characteristics of CO2 flows captured by oxy-fuel combustion technologies.
Table 22.3 Characteristics of CO2 flows (after a preliminary dehydration) captured by pre-combustion technologies. All data collected from [21].
Table 22.4 Compositional specifications of the CO2 capture flow.
Table 22.5 Pure components properties applied in the model. All properties have been collected from DIPPR database.
Table 22.6 PR-kij -values optimized in [9].
Table 22.7 -(Aij , Aji )-optimal values published in [10]. For the joint uncertainty of binary parameters, see [10].
Table 22.8 Compositional characteristics of capture streams analyzed in this section. Compositions of nitrogen and argon here presented have been calculated considering the total dehydrated compositions (zN2 + zAr ) reported in Table 22.1 – Table 22.3 and then divided into two equal quantities. For this reason, their compositions are similar. (*) The ID number has been reported to understand, through Table 22.1, Table 22.2 and Table 22.3, what are the capture technologies that may produce these streams.
Table 22.9 Thermodynamic properties and compositional characteristics of calculated flows.
Table 22.10 Summary of significant calculated quantities.
Table 22.11 Percentage variations of each result, R, reported in Table 22.10 and calculated with PR – kij = 0 and PR – kij = opt models, with respect to the ones obtained with
Table 22.12 Number of plates of the stripping column determined by the different applied models.
Table 22.13 Assumptions of calculations of the compression station.
Table 22.14 Relative deviations between compressors consumptions calculated with different models: PR – 78 + kij = 0 vs.PR + EoS / and PR – 78 + kij = opt vs.PR + EoS / .
Table 22.15 Quality of typical captured and purified streams. (*) These ID numbers refer to the flows reported in Table 22.1 and Table 22.2
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Advances in Solar Cell Materials and Storage
Series Editors: Nurdan Demirci Sankir and Mehmet Sankir
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Cutting-Edge Technology for Carbon Capture, Utilization, and Storage
Karine Ballerat-Busserolles
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Library of Congress Cataloging-in-Publication Data
ISBN 978-1-119-36348-4
With the ratification of the Paris Agreement, we are now committing ourselves to achieving a temperature target of below 2°C, which represents a significant mitigation challenge. Going below 1.5 °C increases immensely this mitigation challenge. CCS has been identified as a key mitigation technology option and the IPCC 5th Assessment report showed that the least cost mitigation portfolio needs to include CCS. Unfortunately CCS has not been deployed as quickly as expected: the current global CO2 capture and storage capacity is only 40 million tons per year, which is a tiny fraction of the 36 billion tons per year of CO2 emitted around the globe. Nevertheless, important demonstration projects are emerging such as Boundary Dam & Quest projects in Canada and Petranova project in Texas. In Norway, three projects have also been preselected for a demonstrator to be launched in 2022.
The application of CCS to industrial sectors other than power (e.g., steel, cement, refining) is expected to deliver half of the global emissions reduction from CCS by 2050. In the near future, these industrial applications will open up, especially in Europe; there will be new opportunities and avenues for CCS that can accelerate its deployment. For these process industries, no possible alternatives for CO2 mitigation exist that could be new energies for fossil fuels.
In North America, Enhanced Oil Recovery (EOR) is the main application considered as it allows CO2 valorization. EOR contributes also to GHG mitigation as 40 to 50 % of the injected CO2 remains stored. At the end of the oil production, it is also possible to continue CO2 injection to store it in the depleted reservoirs. CO2 -EOR has been used for over 40 years, particularly in West Texas and New Mexico.
In Europe and China CO2 EOR will also be considered but it has to be deployed, and storage in deep saline aquifers might also play an important role when a CCS business model exists, which needs to have legislation more operative, a real incentive to finance the first CCS demonstrators, and finally a CO2 price higher than 50 €/t and not at 5 €/t as today.
CO2 Utilization may also be considered for specific applications but it will not play an important role.
A lot of research efforts have still to be made to develop the affordable technologies allowing generalization of CO2 capture facilities throughout the world. Amine processes have been used since 1920 in order to decarbonize natural gas but progress has to be made in reducing CO2 capture cost, which represents 85% of the CCS final cost.
This book contains the papers presented during the CETCCUS conference which was hosted by ICCF in Clermont-Ferrand from 25th to 27th September 2017. This conference was dedicated to CO2 Capture Utilization and Storage technologies.
We hope that it will enable as many people as possible to have a better understanding of the mechanisms involved as well as the technological and economic challenges still to be taken up to deploy CCUS technologies around the globe.
Paul Broutin
CO2 Capture Manager
IFP Energies nouvelles
Solaize, France
A conference with the name Cutting Edge Technology for Carbon Capture, Utilization, and Storage (CETCCUS) was held in Clermont-Ferrand, France, in September 2017. The conference attract both academic, industry, and government representatives to discuss the latest technology related to carbon capture, utilization, and storage (CCUS).
Presenters came from France, Spain, Switzerland, Italy, Denmark, the United Kingdom, Canada and China with co-authors from several other countries, showing the worldwide interest in this topic. This book is a collection of the papers presented at the conference.
The tone for the meeting was set by our keynote speaker M. Paul Broutin and his comments are briefly summarized in the preface to this volume.
Many excellent papers were presented that included new relevant experimental data, models for the data, molecular simulations, new processes for removing carbon dioxide from gas streams, and discussion of enhanced oil recovery (EOR), which is still the main method for utilization of CO2 . This book is a collection of the papers from the conference. We believe these papers shows the quality of the research in this field.
We were pleased to have had several students present at the conference. And we would like to note Ms. Marie Poulain (Chapter 9) who was awarded the ProSim Prize for Best Student Paper.
Finally, we would like to thank our sponsors: Axelera, Gas Liquids Engineering. ProSim, Swagelok, Club CO2 , Société française de physique, Société Chimique de France, The National Center for Scientific Research, Université Clermont Auvergne, Clermont-Ferrand Chemistry Institute, Auvergne Rhône Alpes Region, and The City of Clermont-Ferrand.
K.B., J.J.C., & Y.W.
September 2017
Part I CARBON CAPTURE AND STORAGE