[PDF] Numerical Simulation And Optimization Of Carbon Dioxide Utilization For Enhanced Oil Recovery From Depleted Reservoirs eBook

Author : Razi Safi
Publisher :
Page : 80 pages
File Size : 29,32 MB
Release : 2015
Category : Electronic dissertations
ISBN :

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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.

Author : James H. Biagi
Publisher :
Page : 75 pages
File Size : 14,27 MB
Release : 2014
Category : Electronic dissertations
ISBN :

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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.

Author : Berihun Mamo Negash
Publisher : Springer
Page : 122 pages
File Size : 50,60 MB
Release : 2018-03-15
Category : Technology & Engineering
ISBN : 9811084505

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This book presents articles from the International Conference on Improved Oil Recovery, CIOR 2017, held in Bandung, Indonesia. Highlighting novel technologies in the area of Improved Oil Recovery, it discusses a range of topics, including enhanced oil recovery, hydraulic fracturing, production optimization, petrophysics and formation evaluation.

Author : A.G. Koestler
Publisher : Elsevier
Page : 277 pages
File Size : 48,19 MB
Release : 2002-04-29
Category : Science
ISBN : 0080534279

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This volume contains 17 selected papers reflecting the flavour of the Norwegian Petroleum Society conference on hydrocarbon seals quantification and showing the recent significant advances in the understanding and application of hydrocarbon seal methodologies. Three broad categories are covered in this book: methodologies addressing cap-rock integrity, methodologies relating to fault seal and case studies both from the hydrocarbon basins of Northwestern Europe and in the form of outcrop examples. With the North Sea, Norwegian Sea and Atlantic Margin moving along their respective basin maturity and development curves, exploration is being forced deeper into high pressure/high temperature terrains, while exploitation and development requires greater precision and realism in reservoir simulations to maximise drilling strategies to prolong field life. In all instances the need for predictive tools and methodologies that address the integrity and behaviour of top and lateral (fault) seals to hydrocarbon traps, both in the static and dynamic state, have been identified as key risk factors and this is reflected in this volume.

Author : Shahab Mohaghegh
Publisher : CRC Press
Page : 282 pages
File Size : 16,26 MB
Release : 2018-05-20
Category : Science
ISBN : 1315280809

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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.

Author : Prashant Sopanrao Jadhawar
Publisher :
Page : 524 pages
File Size : 46,3 MB
Release : 2010
Category : Enhanced oil recovery
ISBN :

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Increasing demand of the oil and gas have given rise to surge in drilling and exploration activities to recover oil from other unexplored oil-bearing formations (such as offshore) as well as in the efforts to improve and/or modify the existing methods of the enhanced oil recovery to recover the residual oil left-behind by the applied EOR method. Nearly one-third volume of the original oil in place (OOIP) is left-behind by the current EOR technologies. Estimated 2 trillion barrels of this volume is lucrative to cater the energy needs of the respective countries. Gas injection EOR method is a major contending process in exploitation of this resource, and its application is on the rise since last decade. Continuous gas injection (CGI) and water-alternating gas (WAG) injection are the most notable and commonly field-implemented horizontal displacement type gas injection EOR processes. The limitations of CGI are the severe gravity segregation and poor sweep efficiencies. Although the reservoir sweep efficiencies are improved with the WAG, review of 59 field projects suggest that they yield only maximum of 10% incremental oil recoveries due to the detrimental effects of increased water saturation to diminish gas injectivity, reducing oil mobility, decreased oil relative permeability and oil bypassing due to gravity segregation. Conversely, vertical downward oil-displacement gas driven gravity drainage EOR methods uses the gravity forces to its advantage for enhancing the oil recovery. Gravity drainage EOR methods have been applied to dipping and reef type reservoirs in the field projects and reported to yield high incremental oil recoveries. In this study, the CO2-assisted gravity drainage EOR method is investigated in the non-dipping reservoir through the 3D reservoir simulations and scaling and the sensitivity analysis. Both the compositional and pseudomiscible black-oil numerical reservoir simulations are conducted in the 50 and 35 °API gravity oil-reservoirs respectively. Main objectives of this research are to (i) develop a better production strategy for the oil recovery optimization (ii) investigate the options to optimize oil recovery in the CO2-assisted gravity drainage EOR process (numerical simulation studies) (iii) to develop a set of scaled models sufficient to completely scale the CO2-assisted gravity drainage EOR process through the scaling and sensitivity studies. Original contributions of this research are (i) First comprehensive demonstration of the CO2-assisted gravity drainage EOR method application in 50 °API gravity oil-reservoir, (ii) Development and verification of a new hypothesis of the horizontal gas floodfront in the top-down CO2-assisted gravity drainage EOR process, (iii) Development of a general process selection map for the preliminary choice between the immiscible and miscible process, (iv) Grid size effect studies: Changes in both the x and y grid-dimensions has no impact on the CO2-assisted gravity drainage oil recovery, (v) Grid thickness effect studies: Thin layers, even in the upper layers, facilitates the optimum CO2-assisted gravity drainage oil recovery (vi) Heterogeneity in permeability effect: Presence of heterogeneity in permeability (kv / kv = 0.001) improves the CO2-assisted gravity drainage oil recovery performance (95.5% incremental oil recovery) thereby reducing the number of pore volumes and the operational time. It has been found that recovery further improves when the molecular diffusion effects are taken into account, (vii) Heterogeneity in porosity: Porosity values increasing downwards, such as in the overturned faults, promotes the CO2-assisted gravity drainage mechanism to yield better oil recovery performance, (viii) Clear identification of the overall mechanisms and the supporting micro-mechanisms through the parametric analysis of the reservoir simulation results, (ix) Development of a new correlation (combination number, NJadhawar and Sarma) that encompasses the traditional process affecting multiphase operational parameters in the form of the dimensionless groups. It is further validated using the field projects including the data from the Oseberg field, Norway. Excellent logarithmic correlation match is obtained between the new combination number, NJadhawar and Sarma, and the oil recoveries from both the immiscible and miscible reservoir simulations as well as the field projects. New combination number, NJadhawar and Sarma, is a useful tool to predict CO2-assisted gravity drainage oil recoveries, and (x) Development of a set of the additional scaled models sufficient to completely scale the CO2-assisted gravity drainage EOR process are proposed and validated.

Author : Zhiqiang Gu
Publisher :
Page : pages
File Size : 12,73 MB
Release : 2009
Category : Carbon dioxide
ISBN :

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17 p. report presents the results of compositional simulations of CO2 floods of the Monument Butte Northeast unit and the Glen Bench field. This simulation study is a preliminary investigation of the CO2 enhanced oil recovery (EOR) potential. This study attempts to 1) eliminate the post waterflood incremental oil recovery for the two fields using CO2 injection and water-alternating-gas injection, 2) determine CO2 utilization factors and 3) determine the sequestration potential of EOR for the fields.

Author : Andrew Leach
Publisher :
Page : 31 pages
File Size : 27,74 MB
Release : 2014
Category :
ISBN :

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In this paper, we present what is to our knowledge the first theoretical economic analysis of CO2- enhanced oil recovery (EOR). This technique, which has been used successfully in a number of oil plays (notably in West Texas, Wyoming, and Saskatchewan), entails injection of CO2 into mature oil fields in a manner that reduces the oil's viscosity, thereby enhancing the rate of extraction. As part of this process, significant quantities of CO2 remain sequestered in the reservoir. If CO2 emissions are regulated, oil producers using EOR should therefore be able to earn sequestration credits in addition to oil revenues. We develop a theoretical framework that analyzes the dynamic co-optimization of oil extraction and CO2 sequestration, through the producer's choice at each point in time of an optimal CO2 fraction in the injection stream (the control variable). We find that the optimal fraction is likely to decline monotonically over time, and reach zero before the optimal termination time. Numerical simulations, based on an ongoing EOR project in Wyoming, confirm this result. They show also that cumulative sequestration is positively related to the oil price, and is in fact much more responsive to oil-price increases than to increases in the carbon tax. Only at very high taxes does a tradeoff between oil output and sequestration arise.