Introduction To Modeling Simulation And Optimization Of Co2 Sequestration In Various Types Of Reservoirs
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Introduction To Modeling Simulation And Optimization Of Co2 Sequestration In Various Types Of Reservoirs
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Author : Ramesh Agarwal
language : en
Publisher: Elsevier
Release Date : 2024-11-23
Introduction To Modeling Simulation And Optimization Of Co2 Sequestration In Various Types Of Reservoirs written by Ramesh Agarwal and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-11-23 with Technology & Engineering categories.
Carbon capture and sequestration has become an essential technology for addressing the mitigation of global warming and adverse climate change due to increasing CO2 emissions from fossil fuel combustion worldwide. However, the scientific/engineering community still lacks thorough and practical knowledge about various types of reservoirs capable of effective long-term CO2 sequestration. Introduction to Modeling, Simulation, and Optimization of CO2 Sequestration in Various Types of Reservoirs pulls together the relevant basic scientific knowledge and applications to help reservoir engineering practitioners learn and utilize the potential of CO2 sequestration in saline, oil, gas, shale, basalt, and geothermal reservoirs. After presenting the fundamental properties of various reservoirs, the authors describe each type of reservoir and explain basic parameters, benchmark cases, experimental data, optimization strategies for CO2 sequestration, prospects, and outlook. Rounding out the text with a glossary and consideration of future developments, this book delivers the necessary tools for engineers to better understand carbon sequestration and advance the energy transition. - Introduces the physical characteristics of saline, oil, gas, shale, basalt, and geothermal reservoirs - Describes the physics and chemistry of CO2 sequestration in different types of reservoirs and their modeling - Applies numerical simulation and optimization methodology to various reservoirs with real-world examples - Reviews machine learning applications to carbon capture and sequestration
Principles Of Petroleum Geoscience
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Author : Ashok Vaidya
language : en
Publisher: Educohack Press
Release Date : 2025-02-20
Principles Of Petroleum Geoscience written by Ashok Vaidya and has been published by Educohack Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-02-20 with Science categories.
"Principles of Petroleum Geoscience" offers a comprehensive exploration of essential concepts and methodologies in the field. Authored by experts, we bridge geology, geophysics, engineering, and environmental science, providing an interdisciplinary perspective. Our topics span sedimentary basin analysis, reservoir characterization, seismic interpretation, and well logging, along with the latest advancements in research and technology. We present real-world examples and case studies to illustrate practical applications in petroleum exploration and production, helping readers grasp complex ideas through practical insights. With up-to-date content, this resource is invaluable for students, researchers, and professionals in petroleum geoscience, equipping them to meet modern challenges in hydrocarbon exploration and development.
New Techniques For Reduced Order Modeling In Reservoir Simulation
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Author : Zhaoyang Jin
language : en
Publisher:
Release Date : 2019
New Techniques For Reduced Order Modeling In Reservoir Simulation written by Zhaoyang Jin and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019 with categories.
Reservoir simulation is widely applied for the management of oil and gas production and CO2 storage operations. It can be computationally expensive, however, particularly when the flow physics is complicated and many simulation runs must be performed. This has motivated the development of reduced-order modeling (ROM) procedures, where the goal is to achieve high degrees of computational speedup along with reasonable solution accuracy. In this work we develop and apply two types of ROM methods -- one based on proper orthogonal decomposition (POD) and piecewise linearization, and one based on deep learning. We first develop a POD-based ROM, referred to as POD-TPWL, to simulate coupled flow-geomechanics problems. In POD-TPWL, proper orthogonal decomposition, which enables the representation of solution unknowns in a low-dimensional subspace, is combined with trajectory piecewise linearization (TPWL), where solutions with new sets of well controls are represented via linearization around previously simulated (training) solutions. The over-determined system of equations is projected into the low-dimensional subspace using a least-squares Petrov-Galerkin procedure. The states and derivative matrices required by POD-TPWL, generated by an extended version of Stanford's Automatic-Differentiation-based General Purpose Research Simulator, are provided in an offline (pre-processing or training) step. Offline computational requirements correspond to the equivalent of 5-8 full-order simulations, depending on the number of training runs used. Runtime (online) speedups of O(100) or more are achieved for new POD-TPWL test-case simulations. The POD-TPWL model is tested extensively for a 2D coupled problem involving oil-water flow and geomechanics. It is shown that POD-TPWL provides predictions of reasonable accuracy, relative to full-order simulations, for well-rate quantities, global pressure and saturation fields, global maximum and minimum principal stress fields, and the Mohr-Coulomb rock failure criterion, for the cases considered. A systematic study of POD-TPWL error is conducted using various training procedures for different levels of perturbation between test and training cases. The use of randomness in the well bottom-hole pressure profiles used in training is shown to be beneficial in terms of POD-TPWL solution accuracy. The procedure is also successfully applied to a prototype 3D example case. We next apply the POD-TPWL reduced-order modeling framework to simulate and optimize the injection stage of CO2 storage operations. The use of multiple derivatives, meaning that the linearizations are performed around different training solutions at different time steps, is described and assessed. Two example cases are presented, and the ability of the POD-TPWL model to accurately capture bottom-hole pressure, when time-varying CO2 injection rates are prescribed, is demonstrated. It is also shown that, for these examples, the reduced-order models can provide accurate estimates of CO2 molar fraction at particular locations in the domain. The POD-TPWL model is then incorporated into a mesh adaptive direct search optimization framework where the objective is to minimize the amount of CO2 reaching a target layer at the end of the injection period. The POD-TPWL model is shown to be well suited for this purpose and to provide optimization results that are comparable to those obtained using full-order simulations. POD-TPWL preprocessing computations entail a (serial) time equivalent of about 6.7 full-order simulations, though the resulting runtime speedups, relative to full-order simulation, are about 100--150 for the cases considered. Finally, we develop a new deep-learning-based ROM for reservoir simulation. The reduced-order model is based on an existing embed-to-control (E2C) framework and includes an auto-encoder, which projects the system to a low-dimensional subspace, and a linear transition model, which approximates the evolution of the system states in low dimension. In addition to the loss function for data mismatch considered in the original E2C framework, we introduce a physics-based loss function that penalizes predictions that are inconsistent with the governing flow equations. The loss function is also modified to emphasize accuracy in key well quantities of interest (e.g., fluid production rates). The E2C ROM is shown to have interesting parallels with POD-TPWL. The new ROM is applied to oil-water flow in a 2D heterogeneous reservoir. A total of 300 high-fidelity training simulations are performed in the offline stage, and the network training requires 10-12~minutes on a Tesla V100 GPU node. Online (runtime) computations achieve speedups of O(1000) relative to full-order simulations. Extensive test case results, with well controls varied over large ranges, are presented. Accurate ROM predictions are achieved for global saturation and pressure fields at particular times, and for injection and production well responses as a function of time. Error is shown to increase when 100 or 200 (rather than 300) training runs are used to construct the E2C ROM.
Data Driven Analytics For The Geological Storage Of Co2
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Author : Shahab Mohaghegh
language : en
Publisher: CRC Press
Release Date : 2018-05-20
Data Driven Analytics For The Geological Storage Of Co2 written by Shahab Mohaghegh and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-05-20 with Science categories.
Data-driven analytics is enjoying unprecedented popularity among oil and gas professionals. Many reservoir engineering problems associated with geological storage of CO2 require the development of numerical reservoir simulation models. This book is the first to examine the contribution of artificial intelligence and machine learning in data-driven analytics of fluid flow in porous environments, including saline aquifers and depleted gas and oil reservoirs. Drawing from actual case studies, this book demonstrates how smart proxy models can be developed for complex numerical reservoir simulation models. Smart proxy incorporates pattern recognition capabilities of artificial intelligence and machine learning to build smart models that learn the intricacies of physical, mechanical and chemical interactions using precise numerical simulations. This ground breaking technology makes it possible and practical to use high fidelity, complex numerical reservoir simulation models in the design, analysis and optimization of carbon storage in geological formations projects.
Numerical Simulation And Optimization Of Co2 Sequestration In Saline Aquifers
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Author : Zheming Zhang
language : en
Publisher:
Release Date : 2013
Numerical Simulation And Optimization Of Co2 Sequestration In Saline Aquifers written by Zheming Zhang and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013 with Electronic dissertations categories.
With heightened concerns on CO2 emissions from pulverized-coal power plants, there has been major emphasis in recent years on the development of safe and economical Geological Carbon Sequestration (GCS) technology. Although among one of the most promising technologies to address the problem of anthropogenic global-warming due to CO2 emissions, the detailed mechanisms of GCS are not well-understood. As a result, there remain many uncertainties in determining the sequestration capacity of the formation/reservoir and the safety of sequestered CO2 due to leakage. These uncertainties arise due to lack of information about the detailed interior geometry of the formation and the heterogeneity in its geological properties such as permeability and porosity which influence the sequestration capacity and plume migration. Furthermore, the sequestration efficiency is highly dependent on the injection strategy which includes injection rate, injection pressure, type of injection well employed and its orientation etc. The goal of GCS is to maximize the sequestration capacity and minimize the plume migration by optimizing the GCS operation before proceeding with its large scale deployment. In this dissertation, numerical simulations of GCS are conducted using the DOE multi-phase flow solver TOUGH2 (Transport of Unsaturated Groundwater and Heat). A multi-objective optimization code based on genetic algorithm is developed to optimize the GCS operation for a given geological formation. Most of the studies are conducted for sequestration in a saline formation (aquifer). First, large scale GCS studies are conducted for three identified saline formations for which some experimental data and computations performed by other investigators are available, namely the Mt. Simon formation in Illinois basin, Frio formation in southwest Texas, and the Utsira formation off the coast of Norway. These simulation studies have provided important insights as to the key sources of uncertainties that can influence the accuracy in simulations. For optimization of GCS practice, a genetic algorithm (GA) based optimizer has been developed and combined with TOUGH2. Designated as GA-TOUGH2, this combined solver/optimizer has been validated by performing optimization studies on a number of model problems and comparing the results with brute force optimization which requires large number of simulations. Using GA-TOUGH2, an innovative reservoir engineering technique known as water-alternating-gas (WAG) injection is investigated in the context of GCS; GA-TOUGH2 is applied to determine the optimal WAG operation for enhanced CO2 sequestration capacity. GA-TOUGH2 is also used to perform optimization designs of time-dependent injection rate for optimal injection pressure management, and optimization designs of well distribution for minimum well interference. Results obtained from these optimization designs suggest that over 20% reduction of in situ CO2 footprint, greatly enhanced CO2 dissolution, and significantly improved well injectivity can be achieved by employing GA-TOUGH2. GA-TOUGH2 has also been employed to determine the optimal well placement in a multi-well injection operation. GA-TOUGH2 appears to hold great promise in studying a host of other optimization problems related to GCS.
Reservoir Model Design
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Author : Philip Ringrose
language : en
Publisher: Springer Nature
Release Date : 2021-06-09
Reservoir Model Design written by Philip Ringrose and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-06-09 with Science categories.
This book gives practical advice and ready to use tips on the design and construction of subsurface reservoir models. The design elements cover rock architecture, petrophysical property modelling, multi-scale data integration, upscaling and uncertainty analysis. Philip Ringrose and Mark Bentley share their experience, gained from over a hundred reservoir modelling studies in 25 countries covering clastic, carbonate and fractured reservoir types, and for a range of fluid systems – oil, gas and CO2, production and injection, and effects of different mobility ratios. The intimate relationship between geology and fluid flow is explored throughout, showing how the impact of fluid type, displacement mechanism and the subtleties of single- and multi-phase flow combine to influence reservoir model design. The second edition updates the existing sections and adds sections on the following topics: · A new chapter on modelling for CO2 storage · A new chapter on modelling workflows · An extended chapter on fractured reservoir modelling · An extended chapter on multi-scale modelling · An extended chapter on the quantification of uncertainty · A revised section on the future of modelling based on recently published papers by the authors The main audience for this book is the community of applied geoscientists and engineers involved in understanding fluid flow in the subsurface: whether for the extraction of oil or gas or the injection of CO2 or the subsurface storage of energy in general. We will always need to understand how fluids move in the subsurface and we will always require skills to model these quantitatively. The second edition of this reference book therefore aims to highlight the modelling skills developed for the current energy industry which will also be required for the energy transition of the future. The book is aimed at technical-professional practitioners in the energy industry and is also suitable for a range of Master’s level courses in reservoir characterisation, modelling and engineering. • Provides practical advice and guidelines for users of 3D reservoir modelling packages • Gives advice on reservoir model design for the growing world-wide activity in subsurface reservoir modelling • Covers rock modelling, property modelling, upscaling, fluid flow and uncertainty handling • Encompasses clastic, carbonate and fractured reservoirs • Applies to multi-fluid cases and applications: hydrocarbons and CO2, production and storage; rewritten for use in the Energy Transition.
Geological Storage Of Co2
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Author : Jan Martin Nordbotten
language : en
Publisher: Wiley
Release Date : 2011-10-24
Geological Storage Of Co2 written by Jan Martin Nordbotten and has been published by Wiley this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-10-24 with Technology & Engineering categories.
Despite the large research effort in both public and commercial companies, no textbook has yet been written on this subject. This book aims to provide an overview to the topic of Carbon Capture and Storage (CSS), while at the same time focusing on the dominant processes and the mathematical and numerical methods that need to be employed in order to analyze the relevant systems. The book clearly states the carbon problem and the role of CCS and carbon storage. Thereafter, it provides an introduction to single phase and multi-phase flow in porous media, including some of the most common mathematical analysis and an overview of numerical methods for the equations. A considerable part of the book discusses the appropriate scales of modeling, and how to formulate consistent governing equations at these scales. The book also illustrates real world data sets and how the ideas in the book can be exploited through combinations of analytical and numerical approaches.
Numerical Simulation And Optimization Of Carbon Dioxide Utilization For Enhanced Oil Recovery From Depleted Reservoirs
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Author : Razi Safi
language : en
Publisher:
Release Date : 2015
Numerical Simulation And Optimization Of Carbon Dioxide Utilization For Enhanced Oil Recovery From Depleted Reservoirs written by Razi Safi and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015 with Electronic dissertations categories.
Due to concerns about rising CO2 emissions from fossil fuel power plants, there has been a strong emphasis on the development of a safe and economical method for Carbon Capture Utilization and Storage (CCUS). One area of current interest in CO2 utilization is the Enhanced Oil Recovery (EOR) from depleted reservoirs. In an Enhanced Oil Recovery system, a depleted or depleting oil reservoir is re-energized by injecting high-pressure CO2 to increase the recovery factor of the oil from the reservoir. An additional benefit beyond oil recovery is that the reservoir could also serve as a long-term storage vessel for the injected CO2. Although this technology is old, its application to depleted reservoirs is relatively recent because of its dual benefit of oil recovery and CO2 storage thereby making some contributions to the mitigation of anthropogenic CO2 emissions. Since EOR from depleted reservoirs using CO2 injection has been considered by the industry only recently, there are uncertainties in deployment that are not well understood, e.g. the efficiency of the EOR system over time, the safety of the sequestered CO2 due to possible leakage from the reservoir. Furthermore, it is well known that the efficiency of the oil extraction is highly dependent on the CO2 injection rate and the injection pressure. Before large scale deployment of this technology can occur, it is important to understand the mechanisms that can maximize the oil extraction efficiency as well as the CO2 sequestration capacity by optimizing the CO2 injection parameters, namely, the injection rate and the injection pressure. In this thesis, numerical simulations of subsurface flow in an EOR system is conducted using the DOE funded multiphase flow solver COZView/COZSim developed by Nitec, LLC. A previously developed multi-objective optimization code based on a genetic algorithm developed in the CFD laboratory of the Mechanical Engineering department of Washington University in St. Louis is modified for the use the COZView/COZSim software for optimization applications to EOR. In this study, two reservoirs are modeled. The first is based on a benchmark reservoir described in the COZSim tutorial; the second is a reservoir in the Permian Basin in Texas for which extensive data is available. In addition to pure CO2 injection, a Water Alternating Gas (WAG) injection scheme is also investigated for the same two reservoirs. Optimizations for EOR Constant Gas Injection (CGI) and WAG injection schemes are conducted with a genetic algorithm (GA) based optimizer combined with the simulation software COZSim. Validation of the obtained multi-objective optimizer was achieved by comparing its results with the results obtained from the built-in optimization function within the COZView graphic user interface. Using our GA based optimizer, optimal constant-mass and pressure-limited injection profiles are determined for EOR. In addition, the use of recycled gas is also investigated. Optimization of the EOR problem results in an increased recovery factor with a more efficient utilization of injected CO2. The results of this study should help in paving the way for future optimization studies of other systems such as Enhanced Gas Recovery (EGR) and Enhanced Geothermal Systems (EGS) that are currently being investigated and considered for CCUS.
Numerical Simulation And Optimization Of Carbon Dioxide Utilization And Storage In Enhanced Gas Recovery And Enhanced Geothermal Systems
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Author : James H. Biagi
language : en
Publisher:
Release Date : 2014
Numerical Simulation And Optimization Of Carbon Dioxide Utilization And Storage In Enhanced Gas Recovery And Enhanced Geothermal Systems written by James H. Biagi and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014 with Electronic dissertations categories.
With rising concerns surrounding CO2 emissions from fossil fuel power plants, there has been a strong emphasis on the development of safe and economical Carbon Capture Utilization and Storage (CCUS) technology. Two methods that show the most promise are Enhanced Gas Recovery (EGR) and Enhanced Geothermal Systems (EGS). In Enhanced Gas Recovery a depleted or depleting natural gas reservoir is re-energized with high pressure CO2 to increase the recovery factor of the gas. As an additional benefit following the extraction of natural gas, the reservoir would serve as a long-term storage vessel for the captured carbon. CO2 based Enhanced Geothermal Systems seek to increase the heat extracted from a given geothermal reservoir by using CO2 as a working fluid. Carbon sequestration is accomplished as a result of fluid losses throughout the life of the geothermal system. Although these technologies are encouraging approaches to help in the mitigation of anthropogenic CO2 emissions, the detailed mechanisms involved are not fully understood. There remain uncertainties in the efficiency of the systems over time, and the safety of the sequestered CO2 due to leakage. In addition, the efficiency of both natural gas extraction in EGR and heat extraction in EGS are highly dependent on the injection rate and injection pressure. Before large scale deployment of these technologies, it is important to maximize the extraction efficiency and sequestration capacity by optimizing the injection parameters. In this thesis, numerical simulations of subsurface flow in EGR and EGS are conducted using the DOE multiphase flow solver TOUGH2 (Transport of Unsaturated Groundwater and Heat). A previously developed multi-objective optimization code based on a genetic algorithm is modified for applications to EGR and EGS. For EGR study, a model problem based on a benchmark-study that compares various mathematical and numerical models for CO2 storage is considered. For EGS study a model problem based on previous studies (with parameters corresponding to the European EGS site at Soultz) is considered. The simulation results compare well with the computations of other investigators and give insight into the parameters that can influence the simulation accuracy. Optimizations for EGR and EGS problems are carried out with a genetic algorithm (GA) based optimizer combined with TOUGH2, designated as GA-TOUGH2. Validation of the optimizer was achieved by comparison of GA based optimization studies with the brute-force run of large number of simulations. Using GA-TOUGH2, optimal time-independent and time-dependent injection profiles were determined for both EGR and EGS. Optimization of EGR problem resulted in a larger natural gas production rate, a shorter total operation time, and an injection pressure well below the fracture pressure. Optimization of EGS problem resulted in a precise management of the production temperature profile, heat extraction for the entire well life, and more efficient utilization of CO2. The results of these studies will hopefully pave the way for future GA-TOUGH2 based optimization studies to improve the modeling of CCUS projects.
Petrophysical Modeling And Simulation Study Of Geological Co2 Sequestration
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Author : Xianhui Kong
language : en
Publisher:
Release Date : 2014
Petrophysical Modeling And Simulation Study Of Geological Co2 Sequestration written by Xianhui Kong and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014 with categories.
Global warming and greenhouse gas (GHG) emissions have recently become the significant focus of engineering research. The geological sequestration of greenhouse gases such as carbon dioxide (CO2) is one approach that has been proposed to reduce the greenhouse gas emissions and slow down global warming. Geological sequestration involves the injection of produced CO2 into subsurface formations and trapping the gas through many geological mechanisms, such as structural trapping, capillary trapping, dissolution, and mineralization. While some progress in our understanding of fluid flow in porous media has been made, many petrophysical phenomena, such as multi-phase flow, capillarity, geochemical reactions, geomechanical effect, etc., that occur during geological CO2 sequestration remain inadequately studied and pose a challenge for continued study. It is critical to continue to research on these important issues. Numerical simulators are essential tools to develop a better understanding of the geologic characteristics of brine reservoirs and to build support for future CO2 storage projects. Modeling CO2 injection requires the implementation of multiphase flow model and an Equation of State (EOS) module to compute the dissolution of CO2 in brine and vice versa. In this study, we used the Integrated Parallel Accurate Reservoir Simulator (IPARS) developed at the Center for Subsurface Modeling at The University of Texas at Austin to model the injection process and storage of CO2 in saline aquifers. We developed and implemented new petrophysical models in IPARS, and applied these models to study the process of CO2 sequestration. The research presented in this dissertation is divided into three parts. The first part of the dissertation discusses petrophysical and computational models for the mechanical, geological, petrophysical phenomena occurring during CO2 injection and sequestration. The effectiveness of CO2 storage in saline aquifers is governed by the interplay of capillary, viscous, and buoyancy forces. Recent experimental data reveals the impact of pressure, temperature, and salinity on interfacial tension (IFT) between CO2 and brine. The dependence of CO2-brine relative permeability and capillary pressure on IFT is also clearly evident in published experimental results. Improved understanding of the mechanisms that control the migration and trapping of CO2 in the subsurface is crucial to design future storage projects for long-term, safe containment. We have developed numerical models for CO2 trapping and migration in aquifers, including a compositional flow model, a relative permeability model, a capillary model, an interfacial tension model, and others. The heterogeneities in porosity and permeability are also coupled to the petrophysical models. We have developed and implemented a general relative permeability model that combines the effects of pressure gradient, buoyancy, and capillary pressure in a compositional and parallel simulator. The significance of IFT variations on CO2 migration and trapping is assessed. The variation of residual saturation is modeled based on interfacial tension and trapping number, and a hysteretic trapping model is also presented. The second part of this dissertation is a model validation and sensitivity study using coreflood simulation data derived from laboratory study. The motivation of this study is to gain confidence in the results of the numerical simulator by validating the models and the numerical accuracies using laboratory and field pilot scale results. Published steady state, core-scale CO2/brine displacement results were selected as a reference basis for our numerical study. High-resolution compositional simulations of brine displacement with supercritical CO2 are presented using IPARS. A three-dimensional (3D) numerical model of the Berea sandstone core was constructed using heterogeneous permeability and porosity distributions based on geostatistical data. The measured capillary pressure curve was scaled using the Leverett J-function to include local heterogeneity in the sub-core scale. Simulation results indicate that accurate representation of capillary pressure at sub-core scales is critical. Water drying and the shift in relative permeability had a significant impact on the final CO2 distribution along the core. This study provided insights into the role of heterogeneity in the final CO2 distribution, where a slight variation in porosity gives rise to a large variation in the CO2 saturation distribution. The third part of this study is a simulation study using IPARS for Cranfield pilot CO2 sequestration field test, conducted by the Bureau of Economic Geology (BEG) at The University of Texas at Austin. In this CO2 sequestration project, a total of approximately 2.5 million tons supercritical CO2 was injected into a deep saline aquifer about ~10000 ft deep over 2 years, beginning December 1st 2009. In this chapter, we use the simulation capabilities of IPARS to numerically model the CO2 injection process in Cranfield. We conducted a corresponding history-matching study and got good agreement with field observation. Extensive sensitivity studies were also conducted for CO2 trapping, fluid phase behavior, relative permeability, wettability, gravity and buoyancy, and capillary effects on sequestration. Simulation results are consistent with the observed CO2 breakthrough time at the first observation well. Numerical results are also consistent with bottomhole injection flowing pressure for the first 350 days before the rate increase. The abnormal pressure response with rate increase on day 350 indicates possible geomechanical issues, which can be represented in simulation using an induced fracture near the injection well. The recorded injection well bottomhole pressure data were successfully matched after modeling the fracture in the simulation model. Results also illustrate the importance of using accurate trapping models to predict CO2 immobilization behavior. The impact of CO2/brine relative permeability curves and trapping model on bottom-hole injection pressure is also demonstrated.