Uncertainty Analysis of Capacity Estimates and Leakage

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Uncertainty Analysis of Capacity Estimates and Leakage

Transcript Of Uncertainty Analysis of Capacity Estimates and Leakage

Uncertainty Analysis of Capacity Estimates and Leakage Potential for Geologic Storage of Carbon Dioxide in Saline Aquifers
by
Yamama Raza
S.B., Engineering Science, Smith College, 2006
Submitted to the Engineering Systems Division in Partial Fulfillment of the Requirements for the Degree of
Master of Science in Technology and Policy
at the
Massachusetts Institute of Technology
June 2009
©2009 Massachusetts Institute of Technology. All rights reserved.
Signature of Author………………………………………………………………………………………………………. Technology and Policy Program, Engineering Systems Division Thursday, May 14th, 2009
Certified by………………………………………………………………………………………………………………. Mort D. Webster
Assistant Professor, Engineering Systems Division Thesis Supervisor
Certified by………………………………………………………………………………………………………………. Howard Herzog
Principal Researcher, MIT Energy Initiative Thesis Supervisor
Accepted by……………………………………………………………………………………………………………… Dava J. Newman
Professor of Aeronautics and Astronautics and Engineering Systems Director, Technology and Policy Program

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Uncertainty Analysis of Capacity Estimates and Leakage Potential for Geologic Storage of Carbon Dioxide in Saline Aquifers
by Yamama Raza
Submitted to the Engineering Systems Division on May 14th, 2009 in Partial Fulfillment of the Requirements for
the Degree of Master of Science in Technology and Policy
Abstract
The need to address climate change has gained political momentum, and Carbon Capture and Storage (CCS) is a technology that is seen as being feasible for the mitigation of carbon dioxide emissions. However, there is considerable uncertainty that is present in our understanding of the behavior of CO2 that is injected into the sub-surface.
In this work, uncertainty analysis is performed using Monte Carlo simulations for capacity estimates and leakage potential for a saline aquifer. Six geologic parameters are treated as uncertain: porosity, irreducible water saturation, the endpoint relative permeability of CO2, residual gas saturation, viscosity of water, and viscosity of the brine.
The results of the simulations for capacity indicate that there is a large uncertainty in capacity estimates, and that evaluating the model at using the mean values of the individual parameters does not give the same result as the mean of the distribution of capacity estimates. Sensitivity analysis shows that the two parameters that contribute the most to the uncertainty in estimates are the residual gas saturation and the endpoint relative permeability of CO2.
The results for the leakage simulation suggest that while there is a non-zero probability of leakage, the cumulative amount of CO2 that leaks is on the order of fractions of a percent of the total injected volume, suggesting that essentially all the CO2 is trapped. Additionally, the time when leakage begins is on the order of magnitude of thousands of years, indicating that CCS has the potential to be a safe carbon mitigation option.
Any development of regulation of geologic storage and relevant policies should take uncertainty into consideration. Better understanding of the uncertainty in the science of geologic storage can influence the areas of further research, and improve the accuracy of models that are being used. Incorporating uncertainty analysis into regulatory
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requirements for site characterization will provide better oversight and management of injection activities. With the proper management and monitoring of sites, the establishment of proper liability regimes, accounting rules and compensation mechanisms for leakage, geologic storage can be a safe and effective carbon mitigation tool to combat climate change.
Thesis Supervisors: Mort D. Webster Assistant Professor, Engineering Systems Division Howard J. Herzog Principal Researcher, MIT Energy Initiative
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Acknowledgements
At the completion of my degree here at MIT, there are a number of people I would like to express my appreciation to for making these two years a valuable learning experience. First of all I would like to thank my research supervisors, Mort Webster and Howard Herzog for their support and guidance through out the course of this project. I would like to acknowledge the William F. McClelland Fund, and the Richard de Neufville Technology and Policy Tuition Fellow Scholarship, for their funding for my degree here at MIT, as well as the Carbon Sequestration Initiative for supporting this project. I would like to thank Ruben Juanes from the department of Civil and Environmental Engineering, and his students Christopher MacMinn and Michael Szulczewski for their help with their models that are used in this work, and more importantly, for being readily available to troubleshoot and explain the finer details whenever I’ve needed it. A big thank you to all my lab mates- Ashleigh Hildebrand, Gary Shu, Michael Hamilton, Ellie Ereira, Sarah Bashadi and Manya Ranjan, for their help and support and of course, their good company in the office. Additionally, I would like to thank Mary Gallagher for all her support for everything you could ever need in the office. I would also like to thank Sydney Miller and the rest of the TPP staff that has also helped me tremendously in different ways throughout my two years here at MIT. Finally, a thank you that can never truly be big enough is in order to my ever supportive family- My extremely supportive parents who’ve never stopped me from chasing my dreams, even when they’ve lost track of what they are, and my siblings Farheen and Sarwar; particularly my brother Sarwar whose constant presence, support, advice and un-ending patience with his spoilt little sister has gone a long, long way. It makes me extremely happy and I feel blessed to know that all of you are proud of me and my achievements, and I hope to be able to continue to live up to your expectations as I finally leave school and step into the real world.
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Table of Contents
Abstract _____________________________________________________________ 3 Acknowledgements ____________________________________________________ 5 Table of Contents______________________________________________________ 7 Table of figures _______________________________________________________ 8 List of tables _________________________________________________________ 9 List of Acronyms and Symbols __________________________________________ 10 Chapter 1: Introduction and Background __________________________________ 11
1.1 The Climate Crisis and the need for quick action _______________________ 11 1.2 Geologic Storage of Carbon Dioxide _________________________________ 13 1.3 Capacity Estimation methods for Saline Aquifers _______________________ 15 1.4 Regulation of Geologic Storage in the United States_____________________ 17 1.5 Objective of this work ____________________________________________ 20 Chapter 2: Models and Methods _________________________________________ 21 2.1 Models used ____________________________________________________ 21 2.2 Uncertainty Analysis _____________________________________________ 26 2.3 Parameters for uncertainty analysis __________________________________ 27 2.4 Methods: Determining the Distributions of Uncertain Parameters __________ 28 2.5 Performing the Monte Carlo analysis_________________________________ 34 Chapter 3: Results ____________________________________________________ 37 3.1 Results of Capacity Simulations ____________________________________ 37 3.2 Results of Leakage Simulations _____________________________________ 43 Chapter 4: Implications of Uncertainty in Geologic Storage ___________________ 48 4.1 Implications of uncertainty on the science of geologic storage _____________ 49 4.2 Implications for the regulation of geologic storage ______________________ 51 4.3 Implications of uncertainty on the feasibility of geologic storage as a carbon mitigation option ___________________________________________________ 55 Chapter 5: Conclusions and Future work __________________________________ 58 5.1 Conclusions ____________________________________________________ 58 5.2 Future Work ____________________________________________________ 60 References __________________________________________________________ 61
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Table of figures
Figure 1.1 Geologic trapping mechanisms __________________________________ 14 Figure 2.1 Schematic of the basin ________________________________________ 22 Figure 2.2 The two stages in the migration of the plume________________________ 24 Figure 2.3 Schematic of relative permeability curves for water and CO2 ___________ 27 Figure 2.4 PDF of K*rg, _________________________________________________ 30 Figure 2.5 PDF of porosity_______________________________________________ 31 Figure 2.6 PDF of Sgr __________________________________________________ 31 Figure 2.7 PDF of Sw __________________________________________________ 32 Figure 2.8 Schematic of reservoir depth. ____________________________________ 33 Figure 3.1 PDF of capacity.______________________________________________ 38 Figure 3.2 PDF of storage capacity for the cases with varying correlations_________ 39 Figure 3.3 Sensitivity Analysis for one parameter variable at a time. _____________ 41 Figure 3.4, Sensitivity analysis for one parameter constant at a time. ______________ 41 Figure 3.5 Leak/no leak at different distances away from the injection well ________ 43 Figure 3.6 Fraction of samples for which there is leakage at different lengths. ______ 44 Figure 3.7 Input distribution for fracture distance from injection well. ____________ 45 Figure 3.8 Distribution of lengths at which leakage occurs ._____________________ 45 Figure 3.9 Distributions of total amount leaked ______________________________ 46 Figure 3.10 Distributions of start year of leakage ____________________________ 47
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List of tables
Table 2.1: Data used to fit probability distribution functions ___________________ 29 Table 2.2: Descriptive Statistics for input distributions of uncertain parameters_____ 32 Table 3.1 Statistics for the distribution of the capacity estimate simulations with
varying correlations____________________________________________39 Table 3.2 Statistics for leakage simulation__________________________________ 47
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List of Acronyms and Symbols
AOR_______________________________________________________Area of Review CCS_____________________________________________ Carbon Capture and Storage CO2______________________________________________________ Carbon Dioxide DOE _________________________________________________Department of Energy EPA ________________________________________Environmental Protection Agency GHG______________________________________________________Greenhouse Gas Gt CO2__________________________________________________Gigatonnes of CO2 IPCC_______________________________Intergovernmental Panel on Climate Change K*rg______________________________________Endpoint relative permeability of CO2 MMV________________________________Monitoring, Measurement and Verification PDF_____________________________________________Probability Density Function Sgr___________________________________________________residual gas saturation Swc_________________________________________________connate water saturation SDWA_____________________________________________ Safe Drinking Water Act UIC___________________________________________Underground Injection Control
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StorageUncertaintyLeakageCapacity EstimatesTechnology