# Browsing by Subject "Reservoir simulation"

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Item A new reservoir scale model for fracture propagation and stress reorientation in waterflooded reservoirs(2016-12) Bhardwaj, Prateek; Sharma, Mukul M.Show more It is now well established that poro-thermo-elastic effects substantially change the magnitude and orientation of in-situ stresses. Fractures induced in injectors during water injection for waterflooding or produced water disposal have a profound impact on waterflood performance. These effects, coupled with injectivity decline due to plugging caused by injected particles, lead to permeability reduction, fracture initiation and propagation. Models are available for fracture propagation in single injection wells and single layered reservoirs that account for these effects. However, the impact of fluid injection and production on fracture growth in multiple wells and multi-layered reservoirs with competing fractures, has not been systematically modelled at a field scale. In this work, a three-dimensional, two-phase flow simulator with iteratively coupled geomechanics has been developed and applied to model the dynamic growth of injection-induced fractures. The model is based on a finite volume implementation of the cohesive zone model for arbitrary fracture propagation coupled with two-phase flow. A dynamic filtration model for permeability reduction is employed on the fracture faces to incorporate effects of internal damage and external filter cake build-up due to the injection of suspended solids and oil droplets. All physical phenomena are solved in a single framework designed for multi-well, field-scale simulation. The pressure distribution, saturation profile, thermal front, mechanical displacements and reservoir stresses are computed as fluids are injected and produced from the reservoir. Simulation results are discussed with single as well as multiple fractures propagating. Stress reorientation due to poroelastic, thermoelastic and mechanical effects is examined for the simulated cases. The orientation of the fractures is controlled primarily by the orientation of the stresses, which in turn depends on the pattern of wells and the rates of injection and production. The sweep efficiency of the waterflood is found to be impacted by the rate of growth of injection-induced fractures. Heterogeneities in multi-layered reservoirs strongly govern the expected vertical sweep and fluid distribution, which impacts the cumulative oil recovery. This is the first time a formulation of multiphase flow in the reservoir has been coupled with dynamic fracture propagation in multiple wells induced by solids plugging while including poro-thermo-elasticity at the reservoir scale. The model developed in this work can be used to simulate multiple water injection induced fractures, determine the reoriented stress state to optimize the location of infill wells and adjust injection well patterns to maximize reservoir sweep.Show more Item A new upscaling method for flow simulation of fractured systems(2018-12-06) Chen, Youguang; Sepehrnoori, Kamy, 1951-Show more Fractured reservoirs have gained continuous attention in oil and gas industry since a huge amount of reserves are stored in such reservoirs. Fractures add complexity in reservoir models and thus have potentially large effects on the reservoir simulation results. Though a lot of fine scale fracture models for reservoir simulation have been developed to capture the fracture effects, they are generally complicated and time consuming for the cases with large number of fractures and problems (for example, some inverse problems and optimization problems) where lots of forward simulations are required. Upscaling is a method to fasten the flow simulations by constructing reduced models in coarse scale to approximate the original fine scale models. It is important to construct coarse models in a proper way since the approximated models will generate errors as opposed to the fine scale models. Therefore, a new upscaling method is proposed in this work to capture the effects of fractures in fractured reservoir. First, two hypothetical flow problems are presented to provide pressure solutions for calculation of parameters in coarse models. Unsteady state method, one of these two flow problems, is firstly introduced in this work to obtain reasonable pressure solutions for reservoirs without source term. Second, we developed two partitioning methods to associate coarse grids with fine grids. Since these two partitioning approaches are suitable for different types of fracture networks, we proposed a multi-level partitioning method that is a general approach and could capture fracture effects of different fracture patterns. Third, we developed an efficient time-stepping algorithm for the unsteady state problem to reduce the computational efforts of upscaling process. The applicability of the new upsclaing methodology is verified from numerical tests of different types of reservoirs with different fracture patterns and well configurations. Errors of pressure solution, oil saturation, and production solutions are generally limited below 5% in coarse scale. Furthermore, speedup of simulation is significant in all of the presented numerical testsShow more Item A probabilistic workflow for uncertainty analysis using a proxy-based approach applied to tight reservoir simulation studies(2016-08) Wantawin, Marut; Sepehrnoori, Kamy, 1951-; Yu, WeiShow more Uncertainty associated with reservoir simulation studies should be thoroughly captured during history matching process and adequately explained during production forecasts. Lacking information and limited accuracy of measurements typically cause uncertain reservoir properties in the reservoir simulation models. Unconventional tight reservoirs, for instances, often deal with complex dynamic flow behavior and inexact dimensions of hydraulic fractures that directly affect production estimation. Non-unique history matching solutions on the basis of probabilistic logic are recognized in order to avoid underestimating prediction results. Assisted history matching techniques have been widely proposed in many literature to quantify the uncertainty. However, few applications were done in unconventional reservoirs where some distinct uncertain factors could significantly influence well performance. In this thesis, a probabilistic workflow was developed using proxy-modeling approach to encompass uncertain parameters of unconventional reservoirs and obtain reliable prediction. Proxy-models were constructed by Design of Experiments (DoE) and Response Surface Methodology (RSM). As preliminary screening tools, significant parameters were identified, thus removing those that were insignificant for the reduced dimensions. Furthermore, proxy-models were systematically built to approximate the actual simulation, then sampling algorithms, e.g. Markov Chain Monte Carlo (MCMC) method, successfully estimated probabilistic history matching solutions. An iterative procedure was also introduced to gradually improve the accuracy of proxy-models at the interested region with low history matching errors. The workflow was applied to case studies in Middle Bakken reservoir and Marcellus Shale formation. In addition to estimating misfit function for the errors, proxy-models are also regressed on the simulated quantity of the measurements at various points in time, which is shown to be very useful. This alternative method was utilized in a synthetic tight reservoir model, which analyzed the impact of complex fracture network relative to instantaneous well performance at different stages. The results in this thesis show that the proxy-based approach reasonably provides simplified approximation of actual simulation. Besides, they are very flexible and practical for demonstrating the non-unique history matching solutions and analyzing the probability distributions of complicated reservoir and fracture properties. Ultimately, the developed workflow delivers probabilistic production forecasts with efficient computational requirement.Show more Item A scenario management platform that incorporates statistic and simulation for unconventional field development(2019-05) Sun, Weitong; Sepehrnoori, Kamy, 1951-Show more Producing from shale formations has been made profitable because of technological advancements. However, the complexity and uncertainties of the unconventional reservoir make it hard to estimate the assets and maximize the value. Reservoir simulation is a powerful tool to estimate the performance of reservoir but calibrating models and optimizing the development plan can take lots of human efforts and computation time, especially when we need multiple models to stress the uncertainties. Many of methods have been developed to improve the efficiency of simulations and reduce the number of simulations needed. There are also analytical packages to help understand the results of simulations from the statistical point of view and build economic models. Thus, an efficient way to incorporate the necessary tools and methods from different sources can be helpful for the decision-making process. The designed scenario management platform can help to understand the uncertainties and to make decisions by analyzing the possible scenarios and correlated data. Connected by the data structure management system, the system is equipped with four primary modules, sampling, modeling, calculation interfaces, and visualization tools. The modules can work separately to carry out works like a predictive statistical model, lunch a batch of simulation according to the template and uncertainties, sampling improve the model or according to a distribution, access the model and presenting results. They can also be used together to do more comprehensive work like history matching and well spacing. This thesis presents a few of the technics that are implemented in this platform that can be helpful to understand the uncertainties. We also show some of the applications enabled by the modules of this system and some of the visualization ideas to diagnose the models.Show more Item An exploration of the IGA method for efficient reservoir simulation(2017-08-11) Lynd, Eric Alexander; Foster, John T., Ph. D.; Nguyen, Quoc P.Show more Novel numerical methods present exciting opportunities to improve the efficiency of reservoir simulators. Because potentially significant gains to computational speed and accuracy may be obtained, it is worthwhile explore alternative computational algorithms for both general and case-by-case application to the discretization of the equations of porous media flow, fluid-structure interaction, and/or production. In the present work, the fairly new concept of isogeometric analysis (IGA) is evaluated for its suitability to reservoir simulation via direct comparison with the industry standard finite difference (FD) method and 1st order standard finite element method (SFEM). To this end, two main studies are carried out to observe IGA’s performance with regards to geometrical modeling and ability to capture steep saturation fronts. The first study explores IGA’s ability to model complex reservoir geometries, observing L2 error convergence rates under a variety of refinement schemes. The numerical experimental setup includes an 'S' shaped line sink of varying curvature from which water is produced in a 2D homogenous domain. The accompanying study simplifies the domain to 1D, but adds in multiphase physics that traditionally introduce difficulties associated with modeling of a moving saturation front. Results overall demonstrate promise for the IGA method to be a particularly effective tool in handling geometrically difficult features while also managing typically challenging numerical phenomena.Show more Item Application of artificial neural networks for rapid flash calculations(2019-09-17) Hernandez Mejia, Jose Luis; Okuno, Ryosuke, 1974-Show more Compositional reservoir simulation is widely used as an important tool for optimization of enhanced oil recovery processes. In compositional reservoir simulation, flash calculations are performed to solve for phase properties and amounts for each grid-block and each time step by use of a cubic equation of state (EOS). EOS flash calculation is one of the most time-consuming operations during compositional reservoir simulation. There has been a critical need for more efficient EOS flash for practical compositional reservoir simulation. The central idea tested in this thesis is to use artificial neural networks (ANNs) to replace the most fundamental, but time-consuming portion of EOS flash; that is, the evaluation of fugacity coefficients. ANNs are used for efficient feedforward approximation of the EOS fugacity coefficient function with a series of weights, bias, and activation functions. A set of weights and bias is found by using an algorithm that minimizes the mean squared error between the predicted and real values. This type of approximation is called supervised learning in machine learning applications. The thermodynamic model used is the Peng – Robinson equation of state with the van der Waals mixing rules and solved by the successive substitution algorithm for flash calculations. The implementation of the ANN-based fugacity coefficient function is straightforward because it only replaces the EOS-based fugacity coefficient in conventional flash calculation algorithms. Once an ANN-based fugacity coefficient function is built based on a cubic EOS, the EOS is required only when phase densities are calculated, usually at the final convergence. That is, ANN-based flash does not use an EOS during the iterative solution. We show comparisons between the conventional EOS flash calculations and the ANN flash calculations in terms of computational efficiency. Use of ANN flash can reduce on average 89.83% of the time needed by the conventional EOS flash for the cases studied in this thesis.Show more Item Assessment of polymer injectivity during chemical enhanced oil recovery processes(2010-12) Sharma, Abhinav, 1985-; Delshad, Mojdeh; Pope, Gary A.; Huh, ChunShow more Polymers play a key role in several EOR processes such as polymer flooding, surfactant-polymer flooding and alkaline-surfactant-polymer flooding due to their critical importance of mobility control in achieving high oil recovery from these processes. Numerical simulators are used to predict the performance of all of these processes and in particular the injection rate of the chemical solutions containing polymer; since the economics is very sensitive to the injection rates. Injection rates are governed by the injection viscosity, thus, it is very important to model the polymer viscosity accurately. For the predictions to be accurate, not only the viscosity model must be accurate, but also the calculation of equivalent shear rate in each gridblock must be accurate because the non-Newtonian viscosity models depend on this shear rate. As the size of the gridblock increases, the calculation of this velocity becomes less numerically accurate, especially close to wells. This research presents improvements in polymer viscosity model. Using the improvements in shear thinning model, the laboratory polymer rheology data was better matched. For the first time, polymer viscosity was modeled for complete range of velocity using the Unified Viscosity Model for published laboratory data. New models were developed for relaxation time, time constant and high shear viscosity during that match. These models were then used to match currently available HPAM polymer's laboratory data and predict its viscosity for various concentrations for full flow velocity range. This research presents the need for injectivity correction when large grid sizes are used. Use of large grid sizes to simulate large reservoir due to computation constraints induces errors in shear rate calculations near the wellbore and underestimate polymer solution viscosity. Underestimated polymer solution viscosities lead to incorrect injectivity calculation. In some cases, depending on the well grid block size, this difference between a fine scale and a coarse simulation could be as much as 100%. This study focuses on minimizing those errors. This methodology although needs some more work, but can be used in accurate predictions of reservoir simulation studies of chemical enhanced oil recovery processes involving polymers.Show more Item A collection of case studies for verification of reservoir simulators(2012-08) Li, Xue, active 2012; Sepehrnoori, Kamy, 1951-Show more A variety of oil recovery improvement techniques has been developed and applied to the productive life of an oil reservoir. Reservoir simulators have a definitely established role in helping to identify the opportunity and select the most suitable techniques to optimum improvement in reservoir productivity. This is significantly important for those reservoirs whose operating and development costs are relatively expensive, because numerical modeling helps simulate the increased oil productivity process and evaluates the performance without undertaking trials in field. Moreover, rapid development in modeling provides engineers diverse choices. Hence the need for complete and comprehensive case studies is increasing. This study will show the different characteristics of in-house (UTCOMP and GPAS) and commercial simulators and also can validate implementation and development of models in the future. The purpose of this thesis is to present a series of case studies with analytical solutions, in addition to a series of more complicated field cases studies with no exact solution, to verify and test the functionality and efficiency of various simulators. These case studies are performed with three reservoir simulators, including UTCOMP, GPAS, and CMG. UTCOMP and GPAS were both developed at the Center for Petroleum and Geosystem Engineering at The University of Texas at Austin and CMG is a commercial reservoir simulator developed by Computer Modelling Group Ltd. These simulators are first applied to twenty case studies with exact solutions. The simulation results are compared with exact solutions to examine the mathematical formulations and ensure the correctness of program coding. Then, ten more complicated field-scale case studies are performed. These case studies vary in difficulty and complexity, often featuring heterogeneity, larger number of components and wells, and very fine gridblocks.Show more Item Comparison of models for numerical simulation of low salinity waterflood(2021-08-12) Santra, Ritabrata; Sepehrnoori, Kamy, 1951-; Delshad, MojdehShow more Accurately modeling Low Salinity Water Injection (LSWI) is essential for reliable predictions of oil recovery which affects exploration project planning and investment decisions. During LSWI, we modify the ions present in water before injection into an oil reservoir which helps maintain reservoir pressure and recover more oil from the reservoir, as compared to untreated regular water injection. Thus, understanding the primary mechanism and their effect of improved oil recovery due to wettability alteration during LSWI, and accurately modeling it, is essential to reliably predict and maximize oil recovery. However, there are several proposed models for numerical simulation of this novel method of LSWI and there exists no comparison for choosing the best model for an accurate simulation study. This study uses two simulators: (1) coupled reservoir simulator with geochemistry capabilities, UTCOMP-IPhreeqc and (2) commercial simulator, CMG’s GEM. We compare three models for numerical simulation of LSWI: (1) calcite dissolution, (2) total ionic strength, and (3) Extended Derjaguin, Landau, Verwey, and Overbeek (EDLVO). Most importantly, we also perform comparisons at both field and core scale. We describe the modeling capabilities of the two simulators and perform literature review to summarize the proposed mechanisms and the theory behind existing models. Finally, we simulate on (1) a synthetic carbonate field case, (2) a sandstone coreflood from a published literature, and (3) another sandstone coreflood, each with distinct mineralogy and petrophysical properties, to compare the three models. Results show that only the EDLVO model implemented in UTCOMP-Iphreeqc was able to accurately model the wettability alteration by estimating the change in contact angle during LSWI for all cases. While predicted recoveries from some of the models were similar, further investigation into the results uncovered the shortcomings of the other two models which resulted in incorrect calculation of the interpolating parameter. We concluded that the EDLVO model in UTCOMP-IPhreeqc works for all minerology while the other two models are scale, mineralogy, and case dependent. In future, we aim to develop a screening guide to choose model depending on the case, for simulating LSWI in commercial simulators which lack some of the mechanistic modeling capabilities of UTCOMP-IPhreeqc.Show more Item Derivative-free techniques for optimal development of conventional and unconventional reservoirs(2018-09-11) Nasir, Yusuf, M.S. in Engineering; Sepehrnoori, Kamy, 1951-Show more The cyclic nature of oil price and the incentive from an optimal field development strategy has made the need for the development and management of oil and gas field to be done in an optimal fashion in order to maximize the asset value, while satisfying the optimization constraints which can be in the form of production limits, water cut, or well spacing. The optimal development plan for an oil field is hinged on the optimal locations and production scheme of wells in the field. Computational optimization algorithms, coupled with a reservoir simulator, have become increasingly popular in determining the optimal locations of wells and the optimal controls to be imposed on them. These algorithms should be able to deal with highly non-linear objective functions, the absence of gradient information, and a limited reservoir simulation budget. In this work, we considered derivative-free and non-invasive techniques: Enhanced Success History-Based Adaptive Differential Evolution (ESHADE) strategy with linear population size reduction, which is a variant of L-SHADE (recognized as one of the state-of-the-art global stochastic optimizer for continuous variable), and a Mesh Adaptive Direct Search (MADS) local pattern search method. These two methods are hybridized to develop a hybrid framework (E-MADS) that combines the advantageous aspects of both methods in order to improve optimization efficiency. Applications of these algorithms to the joint optimization of well location and time-varying control problem, with bounds and nonlinear constraints, are presented in this work. We considered both conventional and unconventional reservoirs in this work. In unconventional reservoirs, we considered the placement and control of horizontal wells and their corresponding length, the number of fractures, and fracture spacing. ESHADE is shown to outperform traditional global optimization algorithms such as Particle Swarm Optimization (PSO) and a real-coded Genetic Algorithm (GA). The E-MADS hybrid is also shown to have a superior performance relative to the standalone ESHADE and MADS methods for the joint optimization problem. We also incorporated a proxy in the E-MADS algorithm and it was shown to improve the efficiency of the hybrid algorithm.Show more Item Development and application of a parallel chemical compositional reservoir simulator(2015-08) Behzadinasab, Masoud; Ezekoye, Ofodike A.; Sepehrnoori, Kamy, 1951-Show more Simulation of large-scale and complicated reservoirs requires a large number of gridblocks, which requires a considerable amount of memory and is computationally expensive. One solution to remedy the computational problem is to take advantage of clusters of PCs and high-performance computing (HPC) widely available nowadays. We can run large-scale simulations faster and more efficiently by using parallel processing on these systems. In this research project, we develop a parallel version of an in-house chemical flooding reservoir simulator (UTCHEM), which is the most comprehensive chemical flooding simulator. Every physical feature of the original code has been incorporated in the parallel code. The simulation results of several case studies are compared to the original code for verification and performance of the parallelization. The efficiency of the parallelization is evaluated in terms of speedup using multiple numbers of processors. Consequently, we improve the parallel efficiency to carry out the simulations by minimizing the communications among the processors by modifying the coding. The speedup results in comparison to linear speedup (considering the ideal speedup) indicate excellent efficiency. However, using large number of processors causes the simulator speedup to deviate from linear and the efficiency to decrease. The reason for the degradation is that the time devoted to communication between the processors increases with number of processors. To the best of our knowledge, the parallel version of UTCHEM (UTCHEMP) is the first parallel chemical flooding reservoir simulator that can be effective in running large-scale cases. While it is not feasible to simulate large-scale chemical flooding reservoirs with millions of gridblocks in any serial simulator due to computer memory limitations, UTCHEMP makes simulation of such cases practical. Moreover, this parallel simulator can take advantage of multiple processors to run field-scale simulations with millions of gridblocks in few hours.Show more Item Development and application of a parallel compositional reservoir simulator(2012-08) Ghasemi Doroh, Mojtaba; Sepehrnoori, Kamy, 1951-; Delshad, MojdehShow more Simulation of large-scale and complex reservoirs requires fine and detailed gridding, which involves a significant amount of memory and is computationally expensive. Nowadays, clusters of PCs and high-performance computing (HPC) centers are widely available. These systems allow parallel processing, which helps large-scale simulations run faster and more efficient. In this research project, we developed a parallel version of The University of Texas Compositional Simulator (UTCOMP). The parallel UTCOMP is capable of running on both shared and distributed memory parallel computers. This parallelization included all physical features of the original code, such as higher-order finite difference, physical dispersion, and asphaltene precipitation. The parallelization was verified for several case studies using multiple processors. The parallel simulator produces outputs required for visualizing simulation results using the S3graph visualization software. The efficiency of the parallel simulator was assessed in terms of speedup using various numbers of processors. Subsequently, we improved the coding and implementation in the simulator in order to minimize the communications between the processors to improve the parallel efficiency to carry out the simulations. To improve the efficiency of the linear solver in the simulator, we implemented three well-known high-performance parallel solver packages (SAMG, Hypre, and PETSc) in the parallel simulator. Then, the performances of the solver packages were improved in terms of the input parameters for solving large-scale reservoir simulation problems. The developed parallel simulator has expanded the capability of the original code for simulating large-scale reservoir simulation case studies. In other words, with sufficient number of processors, a field-scale simulation with a million grid cells can be performed in few hours. Several case studies are presented to show the performance of the parallel simulator.Show more Item Development of a framework for parallel reservoir simulation(2017-09-15) Barrios Molano, Hector Emilio; Sepehrnoori, Kamy, 1951-Show more Parallel reservoir simulation is a topic of special interest to reservoir engineers and reservoir simulator developers. Parallel reservoir simulators provides several advantages over non-parallel reservoir simulators, such as • Capability to run bigger models. • Capability to have simulation results faster by using several processing units at once. • Not limited to single computer memory. Memory available increases as more computers are used. All these are compelling reasons for reservoir engineers. However, for reservoir simulator developers, the creation of a parallel reservoir simulator is a more complex task than non-parallel simulators. Problems related to parallel implementation such as parallel communication, model division among processors, and the management of data distributed among processors, among others should be addressed and solved on top of the already complex task of simulator development. Hence, development time for parallel reservoir simulators is more time intensive than the traditional development on single processor computers. The objective of this work is to separate the development focus of parallel reservoir simulators in two: parallel development and reservoir simulator development. To achieve such separation, a parallel framework was developed. The framework developed in this work implements and handles the parallel complexity and provides easy to use programming interfaces to accelerate the development of new parallel reservoir simulators or the parallelization of existing ones. The University of Texas Compositional Simulator (UTCOMP) was used with the framework to create a new parallel reservoir simulator. Several cases were used to verify accuracy, to assert usability and to test parallel performance on our new parallel reservoir simulator. The parallel reservoir simulator developed in this work has all of UTCOMP's features and is able to run models with up to 102.4 million cells using up to 1024 processors.Show more Item Enhanced heavy oil recovery by hybrid thermal-chemical processes(2014-05) Taghavifar, Moslem; Pope, G. A.; Sepehrnoori, Kamy, 1951-Show more Developing hybrid processes for heavy oil recovery is a major area of interest in recent years. The need for such processes originates from the challenges of heavy oil recovery relating to fluid injectivity, reservoir heating, and oil displacement and production. These challenges are particularly profound in shaley thin oil deposits where steam injection is not feasible and other recovery methods should be employed. In this work, we aim to develop and optimize a hybrid process that involves moderate reservoir heating and chemical enhanced oil recovery (EOR). This process, in its basic form, is a three-stage scheme. The first stage is a short electrical heating, in which the reservoir temperature is raised just enough to create fluid injectivity. After electrical heating has created sufficient fluid injectivity, high-rate high-pressure hot water injection accelerates the raise in temperature of the reservoir and assists oil production. At the end of hot waterflooding the oil viscosities are low enough for an Alkali-Co-solvent-Polymer (ACP) chemical flood to be performed where oil can efficiently be mobilized and displaced at low pressure gradients. A key aspect of ultra-low IFT chemical flood, such as ACP, is the rheology of the microemulsions that form in the reservoir. Undesirable rheology impedes the displacement of the chemical slug in the reservoir and results in poor process performance or even failure. The viscosity of microemulsions can be altered by the addition of co-solvents and branched or twin-tailed co-surfactants and by an increase in temperature. To reveal the underlying mechanisms, a consistent theoretical framework was developed. Employing the membrane theory and electrostatics, the significance of charge and/or composition heterogeneity in the interface membrane and the relevance of each to the above-mentioned alteration methods was demonstrated. It was observed that branched co-surfactants (in mixed surfactant formulations) and temperature only modify the saddle-splay modulus (k ̅) and bending modulus (k) respectively, whereas co-solvent changes both moduli. The observed rheological behavior agrees with our findings. To describe the behavior of microemulsions in flow simulations, a rheological model was developed. A key feature of this model is the treatment of the microemulsion as a bi-network. This provides accuracy and consistency in the calculation of the zero-shear viscosity of a microemulsion regardless of its type and microstructure. Once model parameters are set, the model can be used at any concentration and shear rate. A link between the microemulsion rheological behavior and its microstructure was demonstrated. The bending modulus determines the magnitude of the viscous dissipations and the steady-shear behavior. The new model, additionally, includes components describing the effects of rheology alteration methods. Experimental viscosity data were used to validate the new microemulsion viscosity model. Several ACP corefloods showing the large impact of microemulsion viscosity on process performance were matched using the UTCHEM simulator with the new microemulsion rheology model added to the code. Finally, numerical simulations based on Peace River field data were performed to investigate the performance of the proposed hybrid thermal-chemical process. Key design parameters were identified to be the method of heating, duration of the heating, ACP slug size and composition, polymer drive size, and polymer concentration in the polymer drive. An optimization study was done to demonstrate the economic feasibility of the process. The optimization revealed that short electrical heating and high-rate high-pressure waterflooding are necessary to minimize the energy use and operational expenses. The optimum slug and polymer drive sizes were found to be ~0.25 PV and ~1 PV, respectively. It was shown that the well costs dominate the expenditure and the overall cost of the optimized process is in the range of 20-30 $⁄bbl of incremental oil production.Show more Item Fracture to production workflow applied to proppant permeability damage effects in unconventional reservoirs(2014-05) Naseem, Kashif; Olson, Jon E.Show more Most available data from shale production zones tends to point towards the presence of complex hydraulic fracture networks, especially in the Barnett and Marcellus formations. Representing these complex hydraulic fracture networks in reservoir simulators while incorporating the geo-mechanical parameters and fracture apertures is a challenge. In our work we developed a fracture to production simulation workflow using complex hydraulic fracture propagation model and a commercial reservoir simulator. The workflow was applied and validated using geological, stimulation and production data from the Marcellus shale. For validation, we used published data from a 5200 ft. long horizontal well drilled in the lower Marcellus. There were 14 fracturing stages with micro-seismic data and an available production history of 9 months. Complex hydraulic fractures simulations provided the fracture network geometry and aperture distributions as the output, which were up-scaled to grid block porosity and permeability values and imported into a reservoir model for production simulation and history match. The approach of using large grid blocks with conductivity adjustment to represent hydraulic fractures in a reservoir simulator which has been employed in this workflow was validated by comparing with published numerical and analytical solutions. Our results for history match were found to be in reasonable agreement with published results. The incorporation of apertures, complexity and geo-mechanics into reservoir models through this workflow reduces uncertainty in reservoir simulation of shale plays and leads to more realistic production forecasting. The workflow was utilized to study the effect of fracture conductivity damage on production. Homogenous and heterogeneous damage cases were considered. Capillary pressures, determined using empirical relationships and experimental data, were studied using the fracture to production workflow. Assuming homogenous instead of heterogeneous permeability damage in reservoir simulations was shown to have a significant impact on production forecasting, overestimating production by 70% or more over the course of two years. Capillary pressure however was less significant and ignoring capillary pressure in damaged hydraulic fractures led to only 3% difference in production in even the most damaged cases.Show more Item Hydraulic fracture optimization using hydraulic fracture and reservoir modeling in the Piceance Basin, Colorado(2012-08) Reynolds, Harris Allen; Olson, Jon E.; Laubach, SteveShow more Hydraulic fracturing is an important stimulation method for producing unconventional gas reserves. Natural fractures are present in many low-permeability gas environments and often provide important production pathways for natural gas. The production benefit from natural fractures can be immense, but it is difficult to quantify. The Mesaverde Group in the Piceance Basin in Colorado is a gas producing reservoir that has low matrix permeability but is also highly naturally fractured. Wells in the Piceance Basin are hydraulically fractured, so the production enhancements due to natural fracturing and hydraulic fracturing are difficult to decouple. In this thesis, dipole sonic logs were used to quantify geomechanical properties by combining stress equations with critically-stressed faulting theory. The properties derived from this log-based evaluation were used to numerically model hydraulic fracture treatments that had previously been pumped in the basin. The results from these hydraulic fracture models, in addition to the log-derived reservoir properties were used to develop reservoir models. Several methods for simulating the reservoir were compared and evaluated, including layer cake models, geostatistical models, and models simulating the fracture treatment using water injection. The results from the reservoir models were compared to actual production data to quantify the effect of both hydraulic fractures and natural fractures on production. This modeling also provided a framework upon which completion techniques were economically evaluated.Show more Item Influence of relative permeability curves on extent of CO₂ plume during injection into deep saline aquifers(2007-05) Park, Sang-yeop, 1980-; Bryant, Steven L.Show more A compositional reservoir simulation study of CO₂ sequestration in deep saline aquifers is presented. Numerous scenarios analyzing the different aspects of CO₂ injection, affected by formation relative permeability in heterogeneous geologic domains were performed. Two types of CO₂ injection schedules, each with six different formation relative permeability curves, were set: (1) bottom-hole pressure limited CO₂ injection; (2) constant rate CO₂ injection. Bottom-hole pressure limited injection schedule is a more realistic model for field practice. Imposing a bottom-hole pressure at the injector limited the injection rate almost instantly after injection started at an initial rate of 50 MMscf/D. However, the variation of the injection rate during the injection period was controlled by the characteristics of formation relative permeability. Bottom-hole pressure limited injection scenario provides useful insights into the total mass of CO₂ injected for each formation relative permeability set and its results are analyzed in this study. In the second injection scenario where bottom-hole pressure is not imposed, a constant CO₂ injection rate can be achieved and, ultimately, the same amount of CO₂ is injected into the aquifer regardless of formation relative permeability. Given that the same amount of CO₂ is injected, the effects of the differences between the six relative permeability sets can be summarized as follows: 1. The estimation of CO₂ invasion distance by three different analytical approaches on the basis of Buckley-Leverett fractional flow theory provided estimates close to the simulated results. Out of three approaches, the approach that couples the conventional fractional flow theory and semi-miscibility between the fluid phases provided the most accurate results to the simulated. This analytical approach reduced the error ranges of the results (in estimating CO₂ invasion distance) by up to about 50[varies with]80% compared to the others by taking into account the substantial solubility of the injected CO₂ in formation brine. 2. The lateral (horizontal) extent of the CO2 plume at the end of the injection period was analyzed by investigating the following key control factors: gas relative permeability at average CO₂ saturation, gas relative permeability at relatively high liquid saturation (Sw=0.7[varies with]1.0), and average CO₂ saturation. The collective consideration of these three factors yielded a reliable rationale behind the horizontal extent of the CO₂ plume. 3. The vertical distribution of CO₂ injected was analyzed with the concept of "reverse pressure drawdown" (RPD). RPD is the driving force that displaces the CO₂ injected. RPD is inversely proportional to the effective permeability, thus it has an inverse proportionality with relative permeability as well when the injection rate is constant. The resultant hydrostatic gradient in the wellbore and in the gridblocks containing the well was the key primary factor in vertical distribution of CO₂ because it determines variation of RPD with depth. Formation gas relative permeability influences vertical distribution, by either increasing or decreasing well node pressure depending on the characteristics of gas relative permeability. This research shows that formation relative permeability plays an important role when supercritical CO₂ enters deep saline aquifers. In determining the fate of a successful CO₂ sequestration project into aquifers, regardless of whether the storage process is focused toward greater quantities of CO₂ injection or safer CO₂ injection in a form of near-permanent trapping within a geologic domain, the impact of formation relative permeability during the sequestration process must be considered.Show more Item Integration of facies models in reservoir simulation(2010-12) Chang, Lin; Fisher, W. L. (William Lawrence), 1932-; Steel, Ronald; Torres-verdin, CarlosShow more The primary controls on subsurface reservoir heterogeneities and fluid flow characteristics are sedimentary facies architecture and petrophysical rock fabric distribution in clastic reservoirs and in carbonate reservoirs, respectively. Facies models are critical and fundamental for summarizing facies and facies architecture in data-rich areas. Facies models also assist in predicting the spatial architectural trend of sedimentary facies in other areas where subsurface information is lacking. The method for transferring geological information from different facies models into digital data and then generating associated numerical models is called facies modeling or geological modeling. Facies modeling is also vital to reservoir simulation and reservoir characterization analysis. By extensively studying and reviewing the relevant research in the published literature, this report identifies and analyzes the best and most detailed geologic data that can be used in facies modeling, and the most current geostatistical and stochastic methods applicable to facies modeling. Through intensive study of recent literature, the author (1) summarizes the basic concepts and their applications to facies and facies models, and discusses a variety of numerical modeling methods, including geostatistics and stochastic facies modeling, such as variogram-based geostatistics modeling, object-based stochastic modeling, and multiple-point geostatistics modeling; and (2) recognizes that the most effective way to characterize reservoir is to integrate data from multiple sources, such as well data, outcrop data, modern analogs, and seismic interpretation. Detailed and more accurate parameters using in facies modeling, including grain size, grain type, grain sorting, sedimentary structures, and diagenesis, are gained through this multidisciplinary analysis. The report concludes that facies and facies models are scale dependent, and that attention should be paid to scale-related issues in order to choose appropriate methods and parameters to meet facies modeling requirements.Show more Item Mimetic finite differences for porous media applications(2014-05) Al-Hinai, Omar A.; Wheeler, Mary F. (Mary Fanett)Show more We connect the Mimetic Finite Difference method (MFD) with the finite-volume two-point flux scheme (TPFA) for Voronoi meshes. The main effect is reducing the saddle-point system to a much smaller symmetric-positive definite matrix. In addition, the generalization allows MFD to seamlessly integrate with existing porous media modeling technology. The generalization also imparts the monotonicity property of the TPFA method on MFD. The connection is achieved by altering the consistency condition of the velocity bilinear operator. First-order convergence theory is presented as well as numerical results that support the claims. We demonstrate a methodology for using MFD in modeling fluid flow in fractures coupled with a reservoir. The method can be used for nonplanar fractures. We use the method to demonstrate the effects of fracture curvature on single-phase and multi-phase flows. Standard benchmarks are used to demonstrate the accuracy of the method. The approach is coupled with existing reservoir simulation technology.Show more Item Modeling and remediation of reservoir souring(2011-08) Haghshenas, Mehdi; Bryant, Steven L.; Sepehrnoori, Kamy, 1951-; Delshad, Mojdeh; Huh, Chun; Liljestrand, Howard M.Show more Reservoir souring refers to the increase in the concentration of hydrogen sulfide in production fluids during waterflooding. Besides health and safety issues, H₂S content reduces the value of the produced hydrocarbon. Nitrate injection is an effective method to prevent the formation of H₂S. Although the effectiveness of nitrate injection has been proven in laboratory and field applications and biology is well-understood, modeling aspect is still in its early stages. This work describes the modeling and simulation of biological reactions associated with reservoir souring and nitrate injection for souring remediation. The model is implemented in a general purpose adaptive reservoir simulator (GPAS). We also developed a physical dispersion model in GPAS to study the effect of dispersion on reservoir souring. The basic mechanism in the biologically mediated generation of H₂S is the reaction between sulfate and organic compounds in the presence of sulfate-reducing bacteria (SRB). Several mechanisms describe the effect of nitrate injection on reservoir souring. We developed mathematical models for biological reactions to simulate each mechanism. For every biological reaction, we solve a set of ordinary differential equations along with differential equations for the transport of chemical and biological species. Souring reactions occur in the areas of the reservoir where all of the required chemical and biological species are available. Therefore, dispersion affects the extent of reservoir souring as transport of aqueous phase components and the formation of mixing zones depends on dispersive characteristics of porous media. We successfully simulated laboratory experiments in batch reactors and sand-packed column reactors to verify our model development. The results from simulation of laboratory experiments are used to find the input parameters for field-scale simulations. We also examined the effect of dispersion on reservoir souring for different compositions of injection and formation water. Dispersion effects are significant when injection water does not contain sufficient organic compounds and reactions occur in the mixing zone between injection water and formation water. With a comprehensive biological model and robust and accurate flow simulation capabilities, GPAS can predict the onset of reservoir souring and the effectiveness of nitrate injection and facilitate the design of the process.Show more