CFD modelling of CO2 gas dispersion in shallow sea water

120 Table 4.2: Results of Sauter mean CO2 bubble diameter with different release rates..... 127 Table 4.5: Results of predicted levels of seawater pCO2 with different release rates.....

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PHAM HOANG HUY PHUOC LOI

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15 MAY 2020

UNIVERSITI TEKNOLOGI PETRONAS CFD MODELLING OF CO2 GAS DISPERSION IN SHALLOW SEAWATER

by PHAM HOANG HUY PHUOC LOI

The undersigned certify that they have read, and recommend to the Postgraduate Studies

Programme for acceptance this thesis for the fulfillment of the requirements for the degree

Assoc Prof Dr Risza Rusli

Assoc Prof Dr Lau Kok Keong

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Assoc Prof Ir Dr Abd Halim Shah

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Chemical Engineering Department Universiti Teknologi PETRONAS

18/05/2020

CFD MODELLING OF CO2 GAS DISPERSION IN SHALLOW SEAWATER

by

PHAM HOANG HUY PHUOC LOI

A Thesis Submitted to the Postgraduate Studies Programme

as a Requirement for the Degree of

DOCTOR OF PHILOSOPHY CHEMICAL ENGINEERING DEPARTMENT UNIVERSITI TEKNOLOGI PETRONAS BANDAR SERI ISKANDAR,

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PHAM HOANG HUY PHUOC LOI

220/8, 14-9 Street, Ward 5, Vinh Long Province, Vietnam Assoc Prof Dr Risza Rusli

15 MAY 2020

15 MAY 2020

DEDICATION

This thesis is dedicated to my family, main supervisor and friends who always support me within these few years

ACKNOWLEDGEMENTS

Thanks to God for giving me patience despite the tears and sweat

The helpful and knowledgeable supervisor, Assoc Prof Dr Risza Rusli who continuously educating me since my master and now PhD

The Universiti Teknologi PETRONAS and Centre of Advanced Process Safety that are very supportive giving me the chance to pursue my dream

I would like to thank my beloved family, especially my mother who always stands

by me with her non-stop loving me This thesis is dedicated to her I would like to show my appreciation to Prof Faisal Khan and Dr Abdul Mutalib Embong whose supports contribute to the success of my research

My million thanks also go to the good friends; Madam Azlin, Madam Hezlina, Dr Athar, Dr Diana, Dr Marhdati, Afiq Laziz, Esan, Haslinda, Aizat, Faizal Bindin, Faiz, Faiqa, Amira, Ah Hoi, Du Ngoc Uy Lan, Nguyen Tai Hong and Beh Per Phong

My deep appreciation to my sisters here; Vo Thanh Nguyet, Phan Thi Cam Ha, Nguyen Thi Tuyet Hong, Nguyen Thi Thuy Hang and Nguyen Thi Oanh Last but not least, to those in beloved land; To Anh Nga, Tran Thi Nhu Hang, Nguyen Huynh Hac,

To Anh Loan, Nguyen Thi Nhu Ngoc, Pham Thi Kim Lan, Le Thi Huong, Dang Minh Chau Van, Ho Phan Duy Quang, Vo Thi Tra Giang, Simon Trung, Tran Anh Linh, Vo Van Thanh, Phan Minh Nha, Pham Kim Ngan, Pham Kim Ngoc, Pham Huynh Thien Khanh, Pham Ngoc Truc Dao and Pham Ngoc Quoc Bao I love you guys

Thank you once again

ABSTRACT

An accidental CO2 release from shallow reservoir presents a significant effect on the marine ecosystem Therefore, it is very crucial to establish the source term and dispersion models to assess the environmental impacts of the CO2 release from the shallow subsea storage to prevent major accidents Thus, this research aimed to establish a source term model which was enhanced by applying a volume of fluid (VOF) model in FLUENT ® to include the hydrostatic pressure to predict the initial size and shape of the CO2 bubble Besides, a dispersion model was established to include the reaction and the actual current velocity to predict the changes in the pCO2

and pH levels In order to achieve thence, a computational fluid dynamic FLUENT ® code comprising Eulerian-Eulerian approach, realizable k-e turbulent model and species transport equation was integrated with the population balance model (PBM) in the numerical simulation The effects of release rate, release size, and current velocity on the release of the CO2 bubble in the seawater were also discussed

(CFD)-in this study The enhanced source term model predicted the (CFD)-initial bubble size was (CFD)-in

a range of 10-14 mm, which is similar to the result of the previous numerical analysis

A comparison of the bubble shape predicted from the enhanced source term model and observed from the published experimental data showed a reasonable agreement The enhanced dispersion model predicted the highest pCO2 and the lowest pH were at

1591 μatm and 5.7 pH, respectively The relative differences between the simulation results and the published experimental data were 6 % for the pCO2 and 2 % for the

pH This finding revealed that good agreement was observed between the simulation results with the chemical reaction and the published experimental data The initial bubble size increased with the increments of the release rate and the release size The study confirmed the earlier finding that high release rate in low tide (and low current) condition has the most severe impact

ABSTRAK

Pembebasan CO2 secara tidak sengaja dari takungan cetek memberi kesan yang penting kepada ekosistem marin Oleh itu, penghasilan model penyebaran dan sumber terma untuk menilai kesan pembebasan CO2 dari takungan cetek bawah laut kepada persekitaran adalah sangat penting bagi mencegah kemalangan besar Maka, penyelidikan ini bertujuan untuk menghasilkan model terma sumber yang dipertingkatkan dengan menggunakan model isipadu bendalir (VOF) dalam FLUENT® dan melibatkan tekanan hidrostatik bagi meramal saiz awal dan bentuk gelembung CO2 Selain itu, model penyebaran yang dihasilkan menggunakan tindak balas dan arus halaju sebenar untuk meramal perubahan pCO2 dan paras pH Untuk mencapai tujuan tersebut, kod dinamik bendalir komputasi (CFD)-FLUENT ® yang terdiri daripada pendekatan Eulerina-Eulerian, model pergolakan k-e dan persamaan pengangkutan spesies disatukan dengan model keseimbangan populasi (PBM) dalam simulasi numerik Kesan kadar pembebasan, saiz yang dibebaskan dan halaju semasa gelembung CO2 dikeluarkan dalam air laut juga dibincangkan dalam penyelidikan ini Model terma sumber yang dipertingkatkan telah meramalkan saiz awal gelembung berada dalam anggaran 10-14 mm, iaitu sama dengan keputusan analisis numerik sebelum ini Perbandingan bentuk gelembung yang diramalkan dari model terma sumber yang dipertingkatkan dan pemerhatian dari data eksperimen yang diterbitkan menunjukkan persetujuan yang wajar Model penyebaran yang dipertingkatkan telah meramalkan pCO2 paling tinggi dan pH terendah berada pada 1591 μatm dan 5.7 pH Perbezaan relatif antara keputusan simulasi dan data eksperimen yang diterbitkan ialah 6% untuk pCO2 dan 2% untuk pH Penemuan ini menunjukkan persetujuan yang baik antara hasil simulasi dengan reaksi kimia dan data eksperimen yang diterbitkan Saiz awal gelembung meningkat dengan kenaikan kadar dan saiz pembebasan Penyelidikan ini mengesahkan penemuan terdahulu bahawa kadar pembebasan yang tinggi dalam keadaan pasang surut (dan arus rendah) memberi kesan yang paling teruk

In compliance with the terms of the Copyright Act 1987 and the IP Policy of the university, the copyright of this thesis has been reassigned by the author to the legal entity of the university,

Institute of Technology PETRONAS Sdn Bhd

Due acknowledgement shall always be made of the use of any material contained

in, or derived from, this thesis

© PHAM HOANG HUY PHUOC LOI, 2020 Institute of Technology PETRONAS Sdn Bhd All rights reserved

TABLE OF CONTENT

ABSTRACT vii

ABSTRAK viii

LIST OF FIGURES xiv

LIST OF TABLES xix

NOMENCLATURE xxii

CHAPTER 1 INTRODUCTION 1

1.1 Background 1

1.1.1 Carbon Capture and Storage 1

1.1.2 Consequence Analysis in Quantitative Risk Assessment Procedure 4

1.1.2.1 Consequence Analysis 5

1.2 Problem Statement 9

1.3 Research Objectives 10

1.4 Scope of Study 11

1.5 Research Contributions 12

1.6 Outline of Thesis 12

1.7 Chapter Summary 14

CHAPTER 2 LITERATURE REVIEW 16

2.1 Chapter Overview 16

2.2 Carbon Dioxide Emission and Implementation of Carbon Capture and Storage 17

2.3 Carbon Capture and Storage 18

2.3.1 CO2 Capture 21

2.3.2 CO2 Transport 23

2.3.3 CO2 Storage 24

2.4 Potential Risk in CCS System 27

2.4.1 Risk in CO2 Pipeline 27

2.4.2 Risk in Offshore CO2 Storage 28

2.5 Hazards Related to Carbon Dioxide and Impurities from CCS 29

2.5.1 Toxicity of Carbon Dioxide in Air 29

2.5.2 Toxicity of Hydrogen Sulphide in Air 31

2.5.3 Toxicity of Carbon Monoxide in Air 32

2.5.4 Toxicity of Nitrogen Dioxides in Air 33

2.5.5 Toxicity of Sulphur Dioxides in Air 33

2.5.6 Hazards of Carbon Dioxide in Seawater 33

2.6 Consequence Analysis for Releases of Toxic CO2 Gas 36

2.6.1 Source Term Model 36

2.6.1.1 Source Term Model for Subsea CO2 Release 37

2.6.2 Dispersion Model 39

2.6.2.1 Dispersion Model for Subsea CO2 Release 39

2.6.3 Effect Model 46

2.6.3.1 Probit Model 46

2.6.3.2 Probability of Fatality 46

2.7 Consequence Analysis of Release and Dispersion of CO2 to the Marine Water from Subsea CO2 Storage 47

2.7.1 Physicochemical Behaviour of CO2 Release from Subsea CO2 Storage 47

2.7.2 Experimental Work to Study Release and Dispersion of CO2 to the Marine Water 48

2.7.2.1 Experimental Work to Study the Release and Dispersion of CO2 Droplet 48

2.7.2.2 QICS Experiment to Study the Release and Dispersion of CO2 Bubble 50

2.7.3 Modelling of Formation of Initial CO2 Bubble in Shallow Seawater 53 2.7.4 Modelling of Dispersion of CO2 Bubble in Shallow Seawater 53

2.8 Modelling of Bubbly Flow in Pure Water Using CFD 58

2.9 Model Validation 62

2.10 Solution Method 62

2.10.1 QUICK Scheme 63

2.10.2 Phase Coupled SIMPLE Scheme 63

2.11 Chapter Summary 64

CHAPTER 3 METHODOLOGY 67

3.1 Chapter Overview 67

3.2 Methodology to Apply and Enhance the Underwater Source Term Model of CO2 Bubble Formation in Shallow Seawater 69

3.2.1 Step 1: Apply and Enhance the Underwater Source Term Model 69

3.2.1.1 Application of the Standard Underwater Source Term Model 69 3.2.1.2 Enhance of the Standard Underwater Source Term Model 70

3.2.2 Step 2: Model Validation Study for the Underwater Source Term Model 71

3.2.2.1 Selection of Release Scenario 71

3.2.2.2 Simulation Set-up 72

3.2.3 Step 3: Investigate Effect of Different Parameters on the Formation of Initial CO2 Bubble 74

3.3 Methodology to Apply and Enhance the Underwater Dispersion Model of Released CO2 Bubble in Shallow Seawater 74

3.3.1 Step 1: Apply and Enhance the Underwater Dispersion Model 74

3.3.1.1 Application of the Standard Underwater Dispersion Model 74

3.3.1.2 Enhance of the Standard Dispersion Model 89

3.3.2 Step 2: Model Validation Study for the Underwater Dispersion Model 90

3.3.2.1 Selection of Release Scenario 90

3.3.2.2 Simulation Set-up 90

3.3.3 Step 3: Investigate Effect of Different Parameters on the Dispersion of CO2 Bubble 97

3.4 Chapter Summary 98

CHAPTER 4 RESULTS AND DISCUSSIONS 100

4.1 Chapter Overview 100

4.2 Simulation Results of Formation of Initial CO2 Bubble in Shallow Seawater101 4.2.1 Mesh Independency Study for the Formation of Initial CO2 Bubble 101 4.2.2 Prediction of Hydrostatic Pressure 103

4.2.3 Model Validation Study for the Formation of Initial CO2 Bubble 104

4.2.4 Effects of Different Parameters on the Formation of Initial CO2

Bubble 105

4.2.4.1 Effect of Release Velocity on the Formation of Initial CO2 Bubble 105

4.2.4.2 Effect of Release Size on the Formation of Initial CO2 Bubble 106

4.2.4.3 Velocity Vectors of Formed CO2 Bubble 108

4.3 Simulation Results of Dispersion of CO2 Bubble in Shallow Seawater 109

4.3.1 Mesh Independency Study for the Dispersion of CO2 Bubble 109

4.3.2 Prediction of Reaction 109

4.3.3 Prediction of Actual Current Velocity 113

4.3.4 Model Validation Study for the Dispersion of CO2 Bubble 114

4.3.4.1 Calculation of Initial Condition of Seawater 114

4.3.4.2 Prediction of Changes in pCO2 and pH Levels 115

4.3.5 Effect of Different Parameters on the Dispersion of CO2 Bubble 120

4.3.5.1 Effect of Release Rate on the Dispersion of CO2 Bubble 122

4.3.5.2 Effect of Seawater Current on the Dispersion of CO2 Bubble137 4.3.5.3 Effect of Release Size on the Dispersion of CO2 Bubble 150

4.4 Chapter Summary 163

CHAPTER 5 CONCLUSIONS AND FUTURE WORKS 165

5.1 Conclusions 165

5.2 Further Future Works 167

References……… 168

APPENDIX A USER DEFINED FUNCTION OF REACTION RATE 186

APPENDIX B USER DEFINED FUNCTION OF ACTUAL CURRENT VELOCITY 189

List of Publications……….191

LIST OF FIGURES

Figure 1.1: Large-scale projects related to the CCS technology in the world [4] 2 Figure 1.2: Procedure of quantitative risk assessment [51] 5 Figure 2.1: Observation of an increase of CO2 concentration in the atmosphere from

1960 to 2019 [92] 17 Figure 2.2: Three main processes of CCS technology in the power plant [3] 21 Figure 2.3: CO2 capturing procedures [94] 22 Figure 2.4: Site options use for storing the captured CO2 [3]: (1) saline formations; (2) coal-bed methane; (3) EOR; (4) depleted oil and gas reservoirs 25 Figure 2.5: Gas exchange process in the lungs [9] 30 Figure 2.6: Standard method for consequence analysis of a toxic gas accident [51] 37 Figure 2.7: Sketch of CO2 plume and CO2 dissolution process at the release area [88] 48 Figure 2.8: Experimental setup from the QICS project [88]: a) photo of CO2 bubble plumes were observed by video camera; b) sketch of the observation system 51 Figure 3.1: Method used in the numerical modelling of the formation and dispersion

of CO2 gas in shallow seawater 68 Figure 3.2: A surface mesh of the computational domain with 304,000 cells and boundary conditions 73 Figure 3.3: Geometry and mesh used in the simulation of the CO2 dispersion: a) geometry of low tide; b) mesh surface of low tide with the element size of 0.2 m ´ 0.2

m 92 Figure 4.1: Mesh independency was studied with three different meshes on bubble distance measured from the release hole 102 Figure 4.2: Mesh independency was studied with three different meshes on bubble rising velocity 102 Figure 4.3: Simulation results of the initial CO2 bubble size 103

Figure 4.4: Comparison of CO2 bubble shapes: a) the released CO2 bubble shapes were predicted from the present underwater source term model, b) the released CO2

bubble shapes were observed from the QICS experiment 104 Figure 4.5: Predictions of CO2 bubble formation at different release velocities: a) 0.2 m/s; b) 0.30 m/s; c) 0.40 m/s 105 Figure 4.6: Predictions of CO2 bubble formation at different release sizes: a) 4 mm; b)

6 mm; c) 8 mm 107 Figure 4.7: Contours of CO2 bubble velocity vectors in seawater column 108 Figure 4.8: Predictions of pCO2 at 3 cm from seabed above the point of the release with and without the chemical reaction 110 Figure 4.9: Predictions of pCO2 at 5 cm from seabed above the point of the release with and without the chemical reaction 111 Figure 4.10: Predictions of pH at 3 cm from the seabed above the point of the release with and without the chemical reactions 112 Figure 4.11: Predictions of pH at 5 cm from the seabed above the point of the release with and without the chemical reactions 112 Figure 4.12: Contour of actual current velocity without CO2 gas 113 Figure 4.13: Contour of current velocity with the released CO2 gas 114 Figure 4.14: Predictions of pCO2 at 5 cm from the seabed above the release hole with different release rates in low 117 Figure 4.15: Predictions of pCO2 at 5 cm from the seabed above the release hole with different release rates in high tide 117 Figure 4.16: Predictions of pH at 3 cm from the seabed above the release hole with different release rates in low tide 118 Figure 4.17: Predictions of pH at 3 cm from the seabed above the release hole with different release rates in high tide 119 Figure 4.18: Contours of the mean bubble diameter with the release rate of 2.66 ´ 10-5

kg/s 123 Figure 4.19: Contours of the mean bubble diameter with the release rate of 1.97 ´ 10-4

kg/s 123 Figure 4.20: Contours of the mean bubble diameter with the release rate of 3.68 ´ 10-4

kg/s 124

Figure 4.21: Number density of CO2 bubble with the release rate of 2.66 ´ 10-5 kg/s at

60 s after the beginning of the release 125

Figure 4.22: Number density of CO2 bubble with the release rate of 1.97 ´ 10-4 kg/s at 60 s after the beginning of the release 125

Figure 4.23: Number density of CO2 bubble with the release rate of 3.68 ´ 10-4 kg/s at 60 s after the beginning of the release 126

Figure 4.24: Contours of pCO2 with the release rate of 2.66 ´10-5 kg/s 128

Figure 4.25: Contours of pCO2 with the release rate of 1.97 ´ 10-4 kg/s 128

Figure 4.26: Contours of pCO2 with the release rate of 3.68 ´10-4 kg/s 129

Figure 4.27: Contours of pH with the release rate of 2.66 ´ 10-5 kg/s 130

Figure 4.28: Contours of pH with the release rate of 1.97 ´ 10-4 kg/s 130

Figure 4.29: Contours of pH with the release rate of 3.68 ´ 10-4 kg/s 131

Figure 4.30: Prediction of pCO2 at different monitoring points with the release rate of 2.66 ´ 10-5 kg/s 134

Figure 4.31: Prediction of pCO2 at different monitoring points with the release rate of 1.97 ´ 10-4 kg/s 134

Figure 4.32: Prediction of pCO2 at different monitoring points with the release rate of 3.68 ´ 10-4 kg/s 135

Figure 4.33: Prediction of pH at different monitoring points with the release rate of 2.66 ´ 10-5 kg/s 135

Figure 4.34: Prediction of pH at different monitoring points with the release rate of 1.97 ´ 10-4 kg/s 136

Figure 4.35: Prediction of pH at different monitoring points with the release rate of 3.68 ´ 10-4 kg/s 136

Figure 4.36: Contours of the mean bubble diameter with the maximum surface current velocity of 0.03 m/s 138

Figure 4.37: Contours of the mean bubble diameter at the maximum surface current velocity of 0.07 m/s 139

Figure 4.38: Number density of CO2 bubble with the maximum surface current velocity of 0.03 m/s at 60 s after the beginning of the release 140

Figure 4.39: Number density of CO2 bubble with the maximum surface current

velocity of 0.07 m/s at 60 s after the beginning of the release 140

Figure 4.40: Contours of pCO2 with the maximum surface current velocity of 0.03 m/s 143

Figure 4.41: Contours of pCO2 with the maximum surface current velocity of 0.07 m/s 143

Figure 4.42: Contours of pH with the maximum surface current velocity of 0.03 m/s 144

Figure 4.43: Contours of pH with the maximum surface current velocity of 0.07 m/s 145

Figure 4.44: Prediction of pCO2 at different monitoring points with the maximum surface current velocity of 0.03 m/s 148

Figure 4.45: Prediction of pCO2 at different monitoring points with the maximum surface current velocity of 0.07 m/s 148

Figure 4.46: Prediction of pH at different monitoring points with the maximum current velocity of 0.03 m/s 149

Figure 4.47: Prediction of pH at different monitoring points with the maximum surface current velocity of 0.07 m/s 149

Figure 4.48: Contours of the mean bubble diameter with the release size of 0.4 m 151

Figure 4.49: Contours of the mean bubble diameter with the release size of 0.6 m 152

Figure 4.50: Number density of CO2 bubble with the release size of 0.4 m at 60 s after the beginning of the release 153

Figure 4.51: Number density of CO2 bubble with the release size of 0.6 m at 60 s after the beginning of the release 153

Figure 4.52: Contours of pCO2 with the release size of 0.4 m 156

Figure 4.53: Contours of pCO2 with the release size of 0.6 m 156

Figure 4.54: Contours of pH with the release size of 0.4 m 157

Figure 4.55: Contours of pH with the release size of 0.6 m 157

Figure 4.56: Prediction of pCO2 at different monitoring points with the release size of 0.4 m 160

Figure 4.57: Prediction of pCO2 at different monitoring points with the release size of 0.6 m 161

Figure 4.58: Prediction of pH at different monitoring points with the release size of 0.4 m 161 Figure 4.59: Prediction of pH at different monitoring points with the release size of 0.6 m 162

LIST OF TABLES

Table 1.1: The atmospheric concentrations of CO2 and impurities that can cause

immediately dangerous to human life and health 4

Table 1.2: Previous numerical simulations for studies of release and dispersion behaviours of CO2 bubble in shallow seawater 7

Table 2.1: Large-scale CCS projects in the world [4] 18

Table 2.2: Composition of CO2 streams were captured from power plants [8] 23

Table 2.3: CO2 storage capacity worldwide in 2050 (Gt CO2) [102] 26

Table 2.4: Effects of high CO2 concentration on human [45] 30

Table 2.5: Health effects of H2S [10] 32

Table 2.6: Toxicity of carbon monoxide [46] 32

Table 2.7: Standard seawater component at a salinity of 35 g/kg, seawater pH of 8.1 pH and temperature of 25 ºC [121] 33

Table 2.8: Probit parameters and toxic load exponent 46

Table 2.9: Experiments were conducted to study the release behaviour of CO2 droplets in the deep seawater 49

Table 2.10: Experimental conditions of the QICS experiment [88] 52

Table 2.11: Modelling overview of dispersion of CO2 bubble in shallow seawater 53

Table 2.12: Summary of dispersion modelling of CO2 bubble in pure water 59

Table 3.1: Setting values of case studies of the CO2 bubble formation 72

Table 3.2: Meshes conducted for mesh independency of the CO2 bubble formation 72 Table 3.3: Values of diffusion coefficients used in the simulations 80

Table 3.4: Case studies used in model validation study of the present dispersion model 90

Table 3.5: Details of classes used in the current work 95

Table 3.6: Initial mass fraction of species in the current simulation 96

Table 3.7: Release case scenarios used in the parametric simulation of the dispersion of CO2 in shallow seawater 98

Table 4.1: Mean values of pCO2 and pH were predicted in the model validation study 120 Table 4.2: Results of Sauter mean CO2 bubble diameter with different release rates 126 Table 4.3: Results of horizontal bubble plume distance with different release rates 126 Table 4.4: Results of CO2 bubble number density at 60 s of the release with different release rates 127 Table 4.5: Results of predicted levels of seawater pCO2 with different release rates 132 Table 4.6: Results of predicted levels of seawater pH with different release rates 132 Table 4.7: Results of maximum downstream distances of seawater pCO2 and pH levels with different release rates 132 Table 4.8: Coordinator of the monitoring points with different release rates 133 Table 4.9: Results of monitoring points with different release rates 137 Table 4.10: Results of Sauter mean CO2 bubble diameter with different current

velocities 141 Table 4.11: Results of horizontal bubble plume distance with different current

velocities 141 Table 4.12: Results of CO2 bubble number density at 60 s of the release with different current velocities 142 Table 4.13: Results of predicted levels of seawater pCO2 with different current

velocities 145 Table 4.14: Results of predicted levels of seawater pH with different current

velocities 146 Table 4.15: Results of maximum downstream distances of seawater pCO2 and pH levels with different current velocities 146 Table 4.16: Coordinator of the monitoring points with different current velocity 147 Table 4.17: Results of monitoring points with different current velocities 150 Table 4.18: Results of Sauter mean CO2 bubble diameter with different release sizes 154 Table 4.19: Results of horizontal bubble plume distance with different release sizes 154

Table 4.20: Results of CO2 bubble number density at 60 s with different release sizes 155 Table 4.21: Results of predicted levels of seawater pCO2 with different release sizes 158 Table 4.22: Results of predicted levels of seawater pH with different release sizes 158 Table 4.23: Results of maximum downstream distances of seawater pCO2 and pH levels with different release sizes 159 Table 4.24: Coordinator of the monitoring points with different release sizes 159 Table 4.25: Results of monitoring points with different release sizes 163

SYMBOL

effective radius of the ion (m), parameter in Eq (2.15) (m6/mol2), the Helmholtz free energy (J), probit constant the Helmholtz free energy for the ideal gas mixture (J)

the Helmholtz free energy for the mixture (J)

the residual part of the reduced Helmholtz free energy of

component i (J) coalescence rate between bubbles of size i and j (m3/s)

coalescence rate between bubbles of size k and j (m3/s)

interfacial area (1/m), orifice area (m2) defined in Eq (3.67), parameter in Eq (2.15) (m3/mol), probit constant

, birth due to breakup and coalescence of bubbles

constant of order unity concentration (ppmv) discharge coefficient drag coefficient lift coefficient

observations of concentration (ppmv) model predictions of concentration (ppmv) roughness constant

empirical model constants taken as 1.44, 1.9 and 1.3, respectively

channel diameter (m) equivalent diameter of the bubble (m)

diameter of the sediment particles (m) Sauter mean bubble diameter (m) mass diffusion coefficient (m2/s), dispersion (kg/ms2) death due to breakup and coalescence of bubbles pipeline diameter (m)

total energy of the fluid per volume (J/m3) Eötvös number

drag force (N) fraction lift force (N)

the Fanning friction factor momentum exchange term (kg/m2s2)

FAC2 fraction of predictions within a fraction of two of the

observations

lift force (N)

gravitational acceleration (m/s2)

breakup frequency that is the fraction of bubble k of volume V

breaking per unit time (1/s) generation of turbulent kinetic energy due to mean velocity gradients

generation of turbulent kinetic energy due to buoyancy molar concentration Henry’s constant (Kmol/m3.atm)

is referred to the table of Moore

ionic strength (mol/kg) diffusion flux (kg/m2.s) rate constant of the forward reaction (2.2) (1/s) rate constant of the backward reaction (2.2) (kg/mol.s)

rate constant of the forward reaction (2.3) (l/mol.s) rate constant of the backward reaction (2.3) (l/mol.s)

Boltzmann constant = 1.3806 ´ 10-23 (J/kg)

interphase momentum exchange coefficient (kg/m3.s) first dissociation constant of carbonic acid in seawater (mol/kg seawater)

second dissociation constant of carbonic acid in seawater (mol/kg seawater)

dissociation constant of water in seawater (mol/kg seawater)

mass transfer coefficient (m/s) roughness height (m)

mass transfer rate (kg/m3.s) molecular weight (g/mol)

number density (m-3), toxic load exponent, surface normal defined in Eq (3.63)

number density of bubble sizes i, j and k, respectively

(particle/m3) NMSE normalised mean square error

pressure (Pa) pressure (Pa), probability of fatality partial pressure of CO2 (µatm)

pH value (pH)

probability that collision results in coalescence

source term mass flow rate (kg/s) drag force (N), reaction rate (mol/kg.s) Reynolds number

salinity of seawater (g/kg), source term Schmidt number

secant function

Sherwood number Strouhal number time (s), exposure time (minutes) temperature (°C)

total alkalinity (mol/kg) the fluid velocity (m/s)

velocities of bubble sizes i and j (m/s)

characteristic velocity of collision of two particles with diameters and (m/s)

velocity (m/s), specific volume of the fluid (m3/kg)

volume of each phase (m3)

volume of bubble is formed from the coalescence of bubble k and j (m3)

volume of bubble size i, i + 1, j, k respectively (m3)

contribution of fluctuating dilatation in compressible turbulence

to overall dissipation rate spatial coordinate (m) roughness length (m)

concentration of dissolved CO2 (mol/kg)

concentration of ions (mol/kg)

concentration of ions (mol/kg)

concentration of ions (mol/kg)

concentration of ions (mol/kg)

GREEKS

volume fraction of each phase

volume fraction of bubble size i

coefficient of added mass and set to be 0.5

probability density function of bubbles breaking from a bubble

of volume to a bubble of volume the reduced mixture density (kg/m3) turbulent kinetic energy dissipation rate (m2/s3) porosity (m3/m3)

scalar property such as temperature, salinity or CO2

concentration mass of CO2 transferred from the dispersed phase to the continuous phase by dissolution at the interface (kg/m3.s) curvature

turbulent kinetic energy (m2/s2) bulk viscosity of each phase (Pa.s) shear viscosity of each phase (Pa.s) relaxation time accounting for delay in the phase change transition

wake angle of cap

density (kg/m3) surface tension of the liquid phase (N/m) surface tension between CO2 and sediment (N/m)

turbulent Prandtl numbers for k and e taken as 1.0 and 1.2, respectively

surface tension between seawater and CO2 (N/m)

the inverse reduced mixture temperature (K) Reynolds stress tensor (kg/m.s2)

kinematic viscosity (m2/s) eddy viscosity (m2/s) frequency of collision (m3/s)

breakage rate (1/m3.s)

coalescence rate (m3/s)

size ratio ( ) size ratio ( ) SUBSCRIPTS

d dispersed phase

i species, bubble size, vector direction

j direction, species, bubble size, vector direction

ALOHA Areal Locations of Hazardous Atmospheres

CFPP coal fired power plant

-E-L Eulerian-Lagrangian

FLACS Flame Acceleration Simulator

FRED Fire Release Explosion Dispersion

hydrogen ion bicarbonate ion

water

GERG Groupe Européen de Recherches Gazières equation of state

hydroxide ion pCO2 partial pressure of carbon dioxide

-pH pH value

ppmv part per million volume

PHAST Process Hazard Analysis Screening Tool

PSD bubble size distribution

QICS quantifying and monitoring potential ecosystem impacts of

geological carbon storage

QUICK quadratic upstream interpolation for convective kinematics SIMPLE semi-implicit method for pressure linked equations

SW seawater, Span and Wagner equation of state

CHAPTER 1 INTRODUCTION

1.1 Background

1.1.1 Carbon Capture and Storage

Carbon capture and storage (CCS) is an alternative approach to mitigate the large volume of carbon dioxide (CO2) discharged from fossil fuel power plants and industrial processes such as oil refineries, biogas sweetening and productions of steel, iron, cement, and ammonia [1] The deployment of the CCS plants is believed can reduce CO2 emission to a minimum of 14 % by 2050 [2] The CCS technology is being applied around the world in various approaches [3] Figure 1.1 shows the global deployments of large-scale CCS [4] It can be seen from the figure 1.1 that 5 projects are still in construction, 15 projects are at the early or advanced development, and 17 projects are in operation Currently, South Korea, China, and Japan have begun to deploy the large-scale- or demonstration CCS projects, while most Southeast Asian countries have little participation in the CCS projects [5]

In Malaysia, CO2 emissions will rise up as gas reserves are depleted and more fossil fuel (i.e., coal) is used for power generation [6] Currently, PETRONAS has signed a Head of Agreement (HOA) with the TOTAL of France to study the development and production of K5, a high carbon dioxide (up to 70%) gas field offshore Sarawak [7] This is the first gas field with more than 50% CO2 content being developed in Malaysia to guarantee energy and gas supply to the nation Hence, the CO2 gas will be separated from the natural gas and stored under the seabed in a water depth of 80 meters The Ministry of Energy, Green Technology and Water (KETTHA) is now progressing with plans for CCS deployment in Malaysia, and has

set up a multi-stakeholder steering committee to consider the recommendations of the study [5] In the near future, the CCS plants will be built in Malaysia to meet the mitigation requirement of the CO2 emission

Figure 1.1: Large-scale projects related to the CCS technology in the world [4]

A CCS system consists of three main processes: (i) capturing CO2 from the large point source of emission; (ii) compressing and transporting the captured CO2; and (iii) storing the CO2 in underground formations [8] In the capture process, the discharged

CO2 gas can be captured by four various technologies such as post-combustion capture, oxyfuel capture, and pre-combustion capture, and capturing from the industrial processes [3], [9]–[11] These capture technologies produce the CO2

streams with varying components of impurities (i.e., hydrogen sulphide (H2S), carbon monoxide (CO), nitrogen dioxide (NO2), sulphur dioxide (SO2), etc.) [8]

The CO2 streams from the different capture processes are transported by pipelines

or ships to the storage sites [12]–[14] The CO2 pipelines are mostly used to transport

a large volume of captured CO2 through long distance due to its economy [10], [12], [15], [16] However, it was identified that the accidental release of CO2 via such pipeline is highly likely to happen due to equipment failure, corrosion, maintenance errors, external impacts, and operator errors [13], [17]

The captured CO2 is able to be stored at onshore and offshore [18]–[24] For instance, within Europe, the capacity of offshore CO2 storage is about 40%, and it is mainly located at the North Sea basin [25] The offshore storage method is able to achieve low-risk and cost-efficient, compared to the onshore storage sites [26]–[28] However, the CO2 from this offshore storage is likely to leak into seawater due to failure of the caprock seal, leakage through natural fault systems or failures of offshore pipeline and injection [29]–[34]

From 1990 to 2009, a total of 29 incidents related to CO2 pipelines of enhance oil recovery (EOR) projects were recorded in the USA [35]–[37] Fortunately, these 29 incidents happened without deaths or major injuries In 1979, a large amount of CO2

was released from Dieng Volcano in Indonesia and claimed 149 lives [38] The volcano eruption accident of Lake Monoun, Cameroon, in 1984 killed 37 people due

to the emission of toxic CO2 gas [39], [40] In 1986, a tragic disaster from Lake Nyos

in the northwest area of Cameroon, West Africa, killed at least 1700 people and many livestock near the lake and within 14 km radius from the area [41] In 1998, a toxic cloud was created due to the release of high-pressure CO2/H2S (approximately 82%

CO2) during the outbreak of CO2 escape in Nagylengyel, Hungary, leading to the asphyxiation of 2500 residents [42]

The mentioned accidents were not associated with the failures from the operation

of the CCS system However, the resulting accidents show further consequence studies of CO2 releases via the CO2 pipeline networks and the subsea CO2 storage are crucial The possible impacts of accidents related to the CO2 pipelines are the toxic and asphyxiant hazards of CO2 as well as the toxic hazard of impurities such as H2S,

CO, NO2 and SO2 on human and livestock in the atmospheric environment [9], [10], [43], [44] Table 1.1 summarises the effects of exposure to the atmospheric concentrations of the CO2 and the impurities which exist in the CO2 pipelines It can

be observed from the table 1.1 that the atmospheric concentrations that can cause immediately dangerous to human life and health are 40,000 ppmv for CO2 [45], 100 ppmv for H2S [10], 1200 ppmv for CO [46], 20 ppmv for NO2 [47], and 100 ppmv for

SO2 [48]

Table 1.1: The atmospheric concentrations of CO2 and impurities that can cause

immediately dangerous to human life and health

Hazardous gas Level of concentration (ppm

1.1.2 Consequence Analysis in Quantitative Risk Assessment Procedure

All major hazard processes in the industrial fields have potential risks, which are the probability of negative influences such as damage, injuries, or loss of life in the events of the accidents [51] Risk assessment is a crucial requirement in safety regulation because failure to assess the risk can lead to unsafe working environment and expose workers to major hazard accidents such as fire, explosion and toxic release Method of quantitative risk assessment (QRA) is able to analyse the risks of a process to identify whether the risks are acceptable Figure 1.2 by [51] illustrates a standard procedure for assessing the risk In this procedure, the consequence analysis and frequency analysis are considered for the risk assessment The consequence analysis examines the impact of an identified chemical accident The frequency analysis collects accidental historical data to examine the occurrence probability of an identified chemical accident

Figure 1.2: Procedure of quantitative risk assessment [51]

From the above figure 1.1, it can be indicated that many pure CCS projects are still under development Therefore, it is crucial to assess the potential risks of the CCS plants before operating the system at the industrial scale The quantitative risks in the

CO2 pipelines and the subsea CO2 storage were assessed to determine the safety issues and control measures regarding the operations of such technologies [10], [13], [17], [43], [44], [52], [53] The findings highlighted that it is important to understand the consequence of the releases of CO2 to the atmospheric and marine environment This is because the results of the consequence analysis can be used to determine the safety distance of the CO2 pipeline, and to detect and monitor the CO2 release from the subsea CO2 storage in order to prevent the major accidents

1.1.2.1 Consequence Analysis

The consequence of an identified chemical accident can be analysed using consequence models such as source term model, dispersion model, and effect model [51] The source term model estimates the rate of release, the total amount of release, and the state of release (either liquid, solid, vapour, or a combination of a specific scenario) The dispersion model shows how the released substance is transported downwind and dispersed to the environment at certain crucial concentration levels The effect model converts these incident-specific results into effects to human (injuries and death) and assets

For toxic releases, several consequence models have been developed to assess and understand the release and dispersion behaviours of the gases to the atmospheric environment, especially in air indoor and outdoor Generally, the consequence tools of the atmospheric gas release consist of: (i) integral software such as FRED, ALOHA, and PHAST; (ii) Lagrange software such as MicroSPRAY; and (iii) computational fluid dynamics (CFD) software such as FLUENT ®, OpenFOAM, ANSYS-CFX, PANACHE and FLACS [9] Most of these models were applied to model the release and dispersion of dense CO2 gas in the atmospheric conditions via the failures of the

CO2 pipelines [54], [55], [64]–[72], [56]–[63] Thus, the releases and dispersion of

CO2 via such pipelines were modelled based on various release scenarios such as venting, puncture and full-bore rupture The impacts of wind and complex terrain on the atmospheric dispersion of CO2 were investigated The small- and large-scales release experiments were also conducted to validate the developed models [73]–[79]

It was identified that the atmospheric CFD models could accurately predict the downwind concentrations of CO2, compared to the atmospheric integral models and the atmospheric Lagrange model The atmospheric CFD models are the best option when huge obstacles or major realistic terrain effects need to be addressed on the dispersion of CO2 Overall, these experimental and numerical simulation studies provided the most excellent findings for the assessment of safety distances of the certain onshore CO2 pipelines

Very few computer models were also developed to assess the consequence of the release and dispersion of gases to the marine water It was identified that the computer model is a reasonable approach to obtain expected results on this topic with low risk and cost [80] The existing computer models of the underwater gas release include integral model and CFD model [81] There is a case stated that the underwater CFD model is an alternative method for studying the dynamic behaviour of the bubble plume in the seawater, compared to the underwater integral model [82]

The previous experimental and numerical simulation studies have indicated that the release of CO2 from the shallow subsea CO2 reservoirs (seawater depth < 500 m) bring significant impacts on the animal’s life in the marine water, compared to the

CO2 release from the depth subsea CO2 reservoirs It is an indication that at the

shallow seawater condition, the release of CO2 flow will result in the bubble (gas) phase The released CO2 bubbles will rise up along the seawater column Besides, these bubbles will also be dissolved in the seawater The dissolved CO2 gas will react with water to form carbonate ion and hydrogen ion The act of dissolution and reaction of the released CO2 bubbles in the seawater will lead to the changes in the partial pressure of CO2 (pCO2) and pH of the seawater which are able to trigger the harm to the marine life

The consequence of the CO2 bubble release into the shallow seawater was analysed using the underwater integral models which were developed in the studies of [83]–[87] The developed underwater integral models mostly focused on the initial size of the CO2 bubble, the hydrodynamic of the CO2 bubble plume and the dissolution of the CO2 bubble in the seawater Table 1.2 summarised the previous modelling works for the consequence analysis of the CO2 bubble release in the seawater

Table 1.2: Previous numerical simulations for studies of release and dispersion

behaviours of CO2 bubble in shallow seawater

Year Ref

Initial

CO2

bubble size

Hydrodynamic Dissolution Reaction pCO2 pH

2013 [85],

From the above table 1.2, it was found that the initial size of the bubble has strong influence on the dissolution of the released CO2 in the seawater [87] Besides, the initial CO2 bubble size is also a key parameter which takes into account for the input condition of the underwater dispersion model [88] In the previous studies, the CO2

bubbles were modelled to release into the shallow seawater in various assumptions of initial bubble size (see Table 1.2) The initial CO2 bubble size was predicted using an underwater integral source term model [86] This source term model was developed based on a simple balance of buoyancy force and tension force

Formation of the initial bubble size depends on release depths and channel diameters (e.g., release size) [86] Effect of these factors on the initial bubble formation was investigated using the underwater integral source term model which was mentioned above [86] Thus, the initial bubble diameters were predicted to decrease with the increase of the depths It also predicted that the smaller bubble is formed with the smaller channel diameter

The shape of the released CO2 bubble affects the rising velocity [86], [88] The understanding of the CO2 bubble shape is vital to determine the hydrodynamic models

to accurately predict the rising behaviour of the released CO2 bubble in the sweater The CO2 bubble shape was assumed to be a spherical shape in the existing source term model [86]

As can be seen in the above table 1.2, the previous integral CO2 dispersion models considered only the hydrodynamic and dissolution of CO2 bubbles released in shallow seawater [83]–[87] The concentration of dissolved CO2 which was predicted from the dissolution process was used to estimate either pCO2 or pH This may lead to a limitation on the prediction of seawater pH reduction and over-prediction of the pCO2 The dissolved CO2 gas reacts with the seawater to produce ions which can cause the change in the seawater pH Besides, this process also reduces the concentration of dissolved CO2 gas

Effects of release rate, release depth, and current velocity on the dispersion of

CO2 bubbles in seawater have been numerically investigated using the developed underwater integral dispersion models as mentioned above [83]–[86] The studied parameters were changed with different values to find their effects on either the pCO2

or the seawater pH when CO2 gas releases into seawater It was predicted that the release scenario with the high release rate in the low release depth (and low current) resulted in either the highest pCO2 or the lowest seawater pH at the seafloor

H+