Browsing by Subject "Enhanced oil recovery--Simulation methods"
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Item Development of methodology for optimization and design of chemical flooding(2008-08) Ghorbani, Davood, 1967-; Sepehrnoori, Kamy, 1951-; Delshad, MojdehChemical flooding is one of the most difficult enhanced oil recovery methods and was considered a high-risk process in the past. Some reasons are low and uncertain oil price, high chemical prices, lack of confidence in performance of the chemical flooding process, long project life, and reservoir and process uncertainties. However, with significant improvement in simulation and optimization tools and high oil price, chemical flooding is feasible in terms of economical and carefully implemented design. Optimization of chemical floods requires complex integration of reservoir, chemical, economics properties and also drilling and production strategies. Many of these variables are uncertain parameters and many simulations are required to capture the effect of the uncertain and decision variables. These simulations could become very expensive and may not be feasible to consider all of the required simulation models. The goal of this research is the development of a methodology for optimization and design of chemical flooding of candidate oil reservoirs. We performed a comprehensive sensitivity study of reservoir and fluid properties that have significant influence on the oil production during the chemical flooding by performing a series of reservoir simulation runs. For performing the reservoir simulation runs, this study used the UT_IRSP platform and the multiphase, multicomponent, chemical flooding simulator called UTCHEM. During the study, UT_IRSP and UTCHEM have been modified by adding new modules, functions and variables. For example, a deviated well module was implemented in UTCHEM to study deviated wells. Deviated well module allows the users to introduce deviated wells in reservoir and import the well locations similar to Eclipse or CMG simulators. A time-dependent well schedule module was implemented in the UT_IRSP framework. This enhancement allows the well placement optimization studies to find the best time to add new wells, and change the status of the well for example from a producer to an injector in order to have an optimum development plan. An advanced post processing module was added to UT_IRSP in order to design, screen, and optimize complex cases for chemical enhanced oil recovery processes such as investigating the well patterns, well spacing, and type of the well (horizontal vs. vertical wells). An experimental design and response surface methodology with integrated economic model were utilized in this study to obtain the optimum design under uncertainties and have an optimal combination of the decision variables. This methodology is based on applying multi-regression analysis and ANOVA (analysis of variance) between the objective function (i.e. dependent variable, which is net present value (NPV) in chemical flooding) and other uncertain and process variables (independent variables). The economic analysis model used the discounted cash flow method to calculate net present value at the economic life of process, internal rate of return, and growth rate of return for each simulation case. Also the optimizer, OptQuest, is launched with a goal of maximizing the mean NPV. The range and the risk associated with the optimum design was studied using Monte Carlo simulation of objective function of the response variable and other independent variables. This methodology was applied for complex chemical flood cases such as well placement, change of status of wells as a function of time or well pattern and well spacing to investigate the best well scenario from recovery and economics point of view.Item Mechanistic modeling, design, and optimization of alkaline/surfactant/polymer flooding(2008-12) Mohammadi, Hourshad, 1977-; Pope, Gary A.; Delshad, MojdehAlkaline/surfactant/polymer (ASP) flooding is of increasing interest and importance because of high oil prices and the need to increase oil production. The benefits of combining alkali with surfactant are well established. The alkali has very important benefits such as lowering interfacial tension and reducing adsorption of anionic surfactants that decrease costs and make ASP a very attractive enhanced oil recovery method provided the consumption is not too large and the alkali can be propagated at the same rate as a synthetic surfactant and polymer. However, the process is complex so it is important that new candidates for ASP be selected taking into account the numerous chemical reactions that occur in the reservoir. The reaction of acid and alkali to generate soap and its subsequent effect on phase behavior is the most crucial for crude oils containing naphthenic acids. Using numerical models, the process can be designed and optimized to ensure the proper propagation of alkali and effective soap and surfactant concentrations to promote low interfacial tension and a favorable salinity gradient. The first step in this investigation was to determine what geochemical reactions have the most impact on ASP flooding under different reservoir conditions and to quantify the consumption of alkali by different mechanisms. We describe the ASP module of UTCHEM simulator with particular attention to phase behavior and the effect of soap on optimum salinity and solubilization ratio. Several phase behavior measurements for a variety of surfactant formulations and crude oils were successfully modeled. The phase behavior results for sodium carbonate, blends of surfactants with an acidic crude oil followed the conventional Winsor phase transition with significant three-phase regions even at low surfactant concentrations. The solubilization data at different oil concentrations were successfully modeled using Hand's rule. Optimum salinity and solubilization ratio were correlated with soap mole fractions using mixing rules. New ASP corefloods were successfully modeled taking into account the aqueous reactions, alkali/rock interactions, and the phase behavior of soap and surfactant. These corefloods were performed in different sandstone cores with several chemical formulations, crude oils with a wide range of acid numbers, brine with a wide range of salinities, and a wide range of temperatures. 2D and 3D sector model ASP simulations were performed based on field data and design parameters obtained from coreflood history matches. The phenomena modeled included aqueous phase chemical reactions of the alkaline agent and consequent consumption of alkali, the in-situ generation of surfactant by reaction with the acid in the crude, surfactant/soap phase behavior, reduction of surfactant adsorption at high pH, cation exchange with clay, and the effect of co-solvent on phase behavior. Sensitivity simulations on chemical design parameters such as mass of surfactant and uncertain reservoir parameters such as kv/kh ratio were performed to provide insight as the importance of each of these variables in chemical oil recovery. Simulations with different permeability realizations provided the range for chemical oil recoveries. This study showed that it is very important to model both surface active components and their effect on phase behavior when doing mechanistic ASP simulations. The reactions between the alkali and the minerals in the formation depend very much on which alkali is used, the minerals in the formation, and the temperature. This research helped us increase our understanding on the process of ASP flooding. In general, these mechanistic simulations gave insights into the propagation of alkali, soap, and surfactant in the core and aid in future coreflood and field scale ASP designs.Item Reservoir simulation studies for coupled CO₂ sequestration and enhanced oil recovery(2008-05) Ghomian, Yousef, 1974-; Pope, Gary A.; Sepehrnoori, Kamy, 1951-Compositional reservoir simulation studies were performed to investigate the effect of uncertain reservoir parameters, flood design variables, and economic factors on coupled CO₂ sequestration and EOR projects. Typical sandstone and carbonate reservoir properties were used to build generic reservoir models. A large number of simulations were needed to quantify the impact of all these factors and their corresponding uncertainties taking into account various combinations of the factors. The design of experiment method along with response surface methodology and Monte-Carlo simulations were utilized to maximize the information gained from each uncertainty analysis. The two objective functions were project profit in the form of $/bbl of oil produced and sequestered amount of CO₂ in the reservoir. The optimized values for all objective functions predicted by design of experiment and the response surface method were found to be close to the values obtained by the simulation study, but with only a small fraction of the computational time. After the statistical analysis of the simulation results, the most to least influential factors for maximizing both profit and amount of stored CO₂ are the produced gas oil ratio constraint, production and injection well types, and well spacing. For WAG injection scenarios, the Dykstra-Parsons coefficient and combinations of WAG ratio and slug size are important parameters. Also for a CO₂ flood, no significant reduction of profit occurred when only the storage of CO₂ was maximized. In terms of the economic parameters, it was demonstrated that the oil price dominates the CO₂ EOR and storage. This study showed that sandstone reservoirs have higher probability of need for CO₂i ncentives. In addition, higher CO₂ credit is needed for WAG injection scenarios than continuous CO₂ injection. As the second part of this study, scaling groups for miscible CO₂ flooding in a three-dimensional oil reservoir were derived using inspectional analysis with special emphasis on the equations related to phase behavior. Some of these scaling groups were used to develop a new MMP correlation. This correlation was compared with published correlations using a wide range of reservoir fluids and found to give more accurate predictions of the MMP.