# 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 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 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 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 Diffuse Source Transmissibility Upscaling(2014-10-03) Nunna, Krishna ChaitanyaShow more Static high resolution three dimensional geological models are routinely constructed to provide an integrated description of a reservoir which includes seismic, well log and core data, and which characterize the reservoir heterogeneity at multiple scales. These models also represent the structure and stratigraphy of the reservoir within the design of the modeling grid, which may include faults, fault blocks, pinch-outs, layering and cross bedding. Numerical simulation of these high resolution static models remains a challenge even with the rapid growth of computational resources since both geological and flow simulation models have increased in size. 50 million cell geologic models are routine, while simulation models are typically one or two orders of magnitude coarser. Also, multiple simulations should be performed to optimize among various recovery or well placement scenarios for subsurface uncertainty assessment which is not possible to carry out on fine scale models. Hence, upscaling of the geologic models for flow simulation remains part of the subsurface workflows. The industry also faces new reservoir engineering challenges. Unconventional reservoirs (tight gas / shale oil / shale gas) have low permeabilities ranging from micro to nano Darcy. The time for pressure transients are no longer measured in hours or days, but instead are measured in decades or longer for unconventional systems. The separation between transient testing and steady state reservoir management is no longer applicable. Historically, our upscaling algorithms have relied upon steady state concepts of flow, which are no longer applicable to unconventional reservoirs. In the current study, a novel diffuse source transmissibility upscaling approach is described. It applies pressure transient concepts to the calculation of the effective transmissibility between coarse cell pairs. Unlike the usual steady state upscaling algorithms, it is a completely local calculation and is not dependent upon knowledge of, or assumptions about, global reservoir flow patterns. The concept of diffusive time of flight is utilized to calculate the drainage volume at the inter-cell face and remove the fine cells disconnected from the drainage volume. The approach is validated at field scale using an onshore US tight gas reservoir model and is shown to reduce simulation run times by up to two orders of magnitude without significance loss of accuracy in performance prediction.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 Evaluation of a statistical infill candidate selection technique(Texas A&M University, 2004-09-30) Guan, LinhuaShow more Quantifying the drilling or recompletion potential in producing gas basins is often a challenging problem, because of large variability in rock quality, well spacing, and well completion practices, and the large number of wells involved. Complete integrated reservoir studies to determine infill potential are often too time-consuming and costly for many producing gas basins. In this work we evaluate the accuracy of a statistical moving-window technique that has been used in tight-gas formations to assess infill and recompletion potential. The primary advantages of the technique are its speed and its reliance upon well location and production data only. We used the statistical method to analyze simulated low-permeability, 100-well production data sets, then compared the moving-window infill-well predictions to those from reservoir simulation. Results indicate that moving-window infill predictions for individual wells can be off by more than 50%; however, the technique accurately predicts the combined infill-production estimate from a group of infill candidates, often to within 10%. We found that the accuracy of predicted infill performance decreases as heterogeneity increases and increases as the number of wells in the project increases. The cases evaluated in this study included real-world well spacing and production rates and a significant amount of depletion at the infill locations. Because of its speed, accuracy and reliance upon readily available data, the moving window technique can be a useful screening tool for large infill development projects.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 Heterogeneous Reservoir Characterization Utilizing Efficient Geology Preserving Reservoir Parameterization through Higher Order Singular Value Decomposition (HOSVD)(2015-01-21) Afra, SardarShow more Petroleum reservoir parameter inference is a challenging problem to many of the reservoir simulation work flows, especially when it comes to real reservoirs with high degree of complexity and non-linearity, and high dimensionality. In fact, the process of estimating a large number of unknowns in an inverse problem lead to a very costly computational effort. Moreover, it is very important to perform geologically consistent reservoir parameter adjustments as data is being assimilated in the history matching process, i.e., the process of adjusting the parameters of reservoir system in order to match the output of the reservoir model with the previous reservoir production data. As a matter of fact, it is of great interest to approximate reservoir petrophysical properties like permeability and porosity while reparameterizing these parameters through reduced-order models. As we will show, petroleum reservoir models are commonly described by in general complex, nonlinear, and large-scale, i.e., large number of states and unknown parameters. Thus, having a practical approach to reduce the number of reservoir parameters in order to reconstruct the reservoir model with a lower dimensionality is of high interest. Furthermore, de-correlating system parameters in all history matching and reservoir characterization problems keeping the geological description intact is paramount to control the ill-posedness of the system. In the first part of the present work, we will introduce the advantages of a novel parameterization method by means of higher order singular value decomposition analysis (HOSVD). We will show that HOSVD outperforms classical parameterization techniques with respect to computational and implementation cost. It also, provides more reliable and accurate predictions in the petroleum reservoir history matching problem due to its capability to preserve geological features of the reservoir parameter like permeability. The promising power of HOSVD is investigated through several synthetic and real petroleum reservoir benchmarks and all results are compared to that of classic SVD. In addition to the parameterization problem, we also addressed the ability of HOSVD in producing accurate production data comparing to those of original reservoir system. To generate the results of the present work, we employ a commercial reservoir simulator known as ECLIPSE. In the second part of the work, we will address the inverse modeling, i.e., the reservoir history matching problem. We employed the ensemble Kalman filter (EnKF) which is an ensemble-based characterization approach to solve the inverse problem. We also, integrate our new parameterization technique into the EnKF algorithm to study the suitability of HOSVD based parameterization for reducing the dimensionality of parameter space and for estimating geologically consistence permeability distributions. The results of the present work illustrates the characteristics of the proposed parameterization method by several numerical examples in the second part including synthetic and real reservoir benchmarks. Moreover, the HOSVD advantages are discussed by comparing its performance to the classic SVD (PCA) parameterization approach. In the first part of the present work, we will introduce the advantages of a novel parameterization method by means of higher order singular value decomposition analysis (HOSVD). We will show that HOSVD outperforms classical parameterization techniques with respect to computational and implementation cost. It also, provides more reliable and accurate predictions in the petroleum reservoir history matching problem due to its capability to preserve geological features of the reservoir parameter like permeability. The promising power of HOSVD is investigated through several synthetic and real petroleum reservoir benchmarks and all results are compared to that of classic SVD. In addition to the parameterization problem, we also addressed the ability of HOSVD in producing accurate production data comparing to those of original reservoir system. To generate the results of the present work, we employ a commercial reservoir simulator known as ECLIPSE. In the second part of the work, we will address the inverse modeling, i.e., the reservoir history matching problem. We employed the ensemble Kalman filter (EnKF) which is an ensemble-based characterization approach to solve the inverse problem. We also, integrate our new parameterization technique into the EnKF algorithm to study the suitability of HOSVD based parameterization for reducing the dimensionality of parameter space and for estimating geologically consistence permeability distributions. The results of the present work illustrate the characteristics of the proposed parameterization method by several numerical examples in the second part including synthetic and real reservoir benchmarks. Moreover, the HOSVD advantages are discussed by comparing its performance to the classic SVD (PCA) parameterization approach.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 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 Item Modeling and simulation of polymer flooding including the effects of fracturing(2015-12) Li, Zhitao; Delshad, Mojdeh; Wheeler, Mary F.; Pope, Gary A.; Sepehrnoori, Kamy; Huh, ChunShow more Chemical enhanced oil recovery (EOR) technology has attracted increasing interest in recent years with declining oil production from conventional oil reserves. Water flooding of heterogeneous reservoirs with viscous oil leaves considerable amount of remaining oil even at high producing water cuts. Polymer flooding is a mature EOR technology for augmenting recovery of moderately viscous oil. Water soluble polymers are used to reduce water mobility and improve sweep efficiency. For very viscous oil, polymer flooding is a potential non-thermal approach for minimizing viscous fingering and improving both displacement sweep efficiency and volumetric sweep efficiency. Polymer manufacturing techniques has been significantly advanced since 1980’s, which provides improved polymer quality and keeps polymer price relatively low. Compared with unconventional oil recovery techniques such as hydraulic fracturing, well planned and optimized polymer flooding can be profitable even at pessimistic oil price. It is thus crucial to have a reservoir simulator that is able to accurately model polymer properties and simulate polymer flooding in complex reservoir systems. Polymer rheological behavior is dependent on polymer molecular structure, concentration, Darcy velocity, brine salinity, hardness, permeability, porosity, etc. We improved polymer rheology modeling for heterogeneous reservoirs where permeability varies for orders of magnitude. For an injection well, a large portion of pressure drop is lost near wellbore where apparent polymer viscosity as a function of Darcy velocity varies drastically. Conventional analytical well models fail to capture the non-Newtonian effect of apparent polymer viscosity and make injectivity predictions widely deviated from true solutions especially for coarse-grid simulations. We developed a semi-analytical polymer injectivity model and implemented it into UTCHEM. This model is able to handle both shear-thinning and shear-thickening polymer rheology. It successfully avoids the grid effect and matches fine-grid simulation results and analytical solutions. Another challenge is to model polymer injectivity under fracturing conditions. To maintain an economic polymer injection rate, wellbore pressure may exceed the fracture initiation pressure. We developed a framework to couple a fracture model with UTCHEM. This coupled simulator is able to model fracture propagation during polymer injection. Finally several simulation studies were conducted to show the impacts of polymer rheological behavior, loss of polymer into aquifer, near wellbore effect and fracture propagation.Show more Item Modeling of gas flooding in high pressure reservoir using a compositional reservoir simulator(2016-12) Du, Yujing; Sepehrnoori, Kamy, 1951-; Mohanty, Kishore KumarShow more In this thesis, three phase relative permeability model and miscible fingering model were implemented into a compositional simulator. Two dimensional homogeneous reservoir simulations were performed using four different gases, and the performance and reservoir properties were compared after different gas flooding. The results show that CH4 injection, 96% CH4 + 4% C2 injection, and CO2 injection have high oil recovery of about 95%, while N2 injection leads to less than 60% oil recovery. N2 breakthrough the fastest and CO2 breakthrough the slowest. The reason is that N2 has the lowest viscosity while CO2 has the highest viscosity. In each of the four cases, recovery rate increases with time, possibly because the viscosity decreases as more gas dissolves in oil hence the overall viscosity decrease with time. Gas injecting from the top tends to have earlier breakthrough because the gravity assists the gas drainage process, but the ultimate recoveries are the same. The effect of flooding direction, swept orientation and well spacing on oil recovery were investigated. Swept orientation has the most significant effect on the oil recovery compared since swept orientation determines the areal swept efficiency. Diagonal sweeping has much higher areal swept efficiency than vertical sweeping since it sweeps larger area. Well spacing has more significant effect on oil recovery when the swept is vertical than diagonal, and larger well spacing leads to lower recovery since smaller area can be swept. Large well spacing also postpones the breakthrough time, especially for diagonal sweeping cases. Comparing the result of N2 flooding with and without fingering model, it can be seen that near miscible viscous fingering tends to lead to low recovery and earlier breakthrough.Show more Item Modeling of point bar geology using a grid transformation scheme and geostatistics(2015-12) Li, Henry; Sepehrnoori, Kamy, 1951-; Srinivasan, SanjayShow more Point bars, the convex inner banks of meandering rivers, exhibit distinct heterogeneities. Modeling these heterogeneities is essential because of the presence of mud/silt layers in point bars impede the flow of fluids in processes strongly controlled by buoyancy or gravity such as the steam chamber rise during Steam-Assisted Gravity Drainage (SAGD). This thesis details the modeling of point bars using geological trends and well data to supplement geostatistical simulation. The modeling processes in this thesis capture the internal geometry of the accretion layers as well as geological trends. Curvilinear grids are constructed between major erosional surfaces where a grid transformation scheme is used to transform the curvilinear coordinates into orthogonal coordinates for geostatistical simulation. The grid transformation allows flexibility in performing statistical simulation in rectangular coordinate while honoring the curvilinear geometry of the point bar. An entire point bar model contains a series of accreting curviplanar grids. Geological modeling is done independently for each grid. The geology captures key trends that make up the heterogeneities in the model. The point bar model created is based on a modern point bar in the Brazos River. Data from thirty-three wells are used in creating the reservoir model. Several distinct trends are observed. There is an upward decrease in sediment size in the point bar. An overall fining downstream trend is observed in the vertical slices of the point bar. Heterolithic bedding is observed where frequent layers of silt extend from the top to near the base analogous to outcrops. Mud and silt dominate the upward regions of the point bar while conglomerate and cobble are mainly present at the base. The flow simulation model investigated the effect of mud drapes and fining heterogeneities on the development of steam chamber in SAGD recovery. The mud drapes impeded the steam chamber rise. The steam chambers were initially divided into pockets based on the flow barriers present. After 1 years of production, the steam chamber reaches the top of the reservoir but continued to be separated by the mud/silt barriers. Comparing to the homogeneous case, the point bar model exhibited lower oil recovery.Show more Item Modeling of temperature effect on low salinity waterflooding(2016-05) Fu, Wensi; Sepehrnoori, Kamy, 1951-Show more Recent studies have shown that additional oil can be achieved by modifying the composition and/or salinity of the injection water. Low salinity waterflooding gains popularity due to its low cost, availability of water, and high displacement efficiency of light to medium gravity oil. Various mechanisms behind low salinity waterflooding have been proposed. However, the dominant underlying mechanism is still under debate due to the complex nature of the interaction between crude oil/brine/rock (COBR). Temperature has been reported to play a significant role in the process of low salinity waterflooding, particularly in carbonates. Temperature may affect geochemical reactions between rock surface, crude oil, and water and consequently alter the rock wettability. Investigating the temperature effect not only helps identify optimum condition to achieve additional oil recovery but also contributes to understanding the mechanisms behind low salinity waterflooding. In order to investigate the temperature effect on low salinity waterflooding, we implemented an energy module in the UTCOMP-IPhreeqc simulator. Hereafter, we refer to the improved simulator as “non-isothermal UTCOMP-IPhreeqc.” UTCOMP-IPhreeqc is capable of modeling non-isothermal, multi-dimensional, and multi-phase transport process with geochemical calculations between water, minerals, gases, ion exchangers, kinetics, and surface complexes. Non-isothermal UTCOMP-IPhreeqc was then applied to study the temperature effect on low salinity coreflood experiments of sandstone and carbonate rocks based on the laboratory work of Kozaki (2012) and Chandrasekhar (2013), respectively. Our simulation results revealed that for the sandstone case, changing the temperature from 30 to 120 ºC has insignificant effect on the oil recovery. We believe the reason is due to the fact that for this specific case the total ionic strength and the viscosity ratio (water viscosity over oil viscosity) did not change with increasing temperature. Noteworthy, double-layer expansion is assumed to be the underlying mechanism for low salinity waterflooding in sandstones in non-isothermal UTCOMP-IPhreeqc. On the other hand, the total ionic strength is the main controlling parameter for the double-layer expansion. For the carbonate case, with increasing temperature from 120 to 150 ºC, oil recovery increased for both formation brine and low salinity water injection. The reason: while the viscosity ratio remained constant, calcite dissolution increases as the temperature increases. The calcite dissolution is assumed to be the underlying mechanism for low salinity water in carbonates in non-isothermal UTCOMP-IPhreeqc. Hence, as more calcite dissolves the wettability of the rock changes towards more water-wet. As a result, oil recovery improves.Show more Item On some problems in the simulation of flow and transport through porous media(2009-08) Thomas, Sunil George; Wheeler, Mary F. (Mary Fanett)Show more The dynamic solution of multiphase flow through porous media is of special interest to several fields of science and engineering, such as petroleum, geology and geophysics, bio-medical, civil and environmental, chemical engineering and many other disciplines. A natural application is the modeling of the flow of two immiscible fluids (phases) in a reservoir. Others, that are broadly based and considered in this work include the hydrodynamic dispersion (as in reactive transport) of a solute or tracer chemical through a fluid phase. Reservoir properties like permeability and porosity greatly influence the flow of these phases. Often, these vary across several orders of magnitude and can be discontinuous functions. Furthermore, they are generally not known to a desired level of accuracy or detail and special inverse problems need to be solved in order to obtain their estimates. Based on the physics dominating a given sub-region of the porous medium, numerical solutions to such flow problems may require different discretization schemes or different governing equations in adjacent regions. The need to couple solutions to such schemes gives rise to challenging domain decomposition problems. Finally, on an application level, present day environment concerns have resulted in a widespread increase in CO₂capture and storage experiments across the globe. This presents a huge modeling challenge for the future. This research work is divided into sections that aim to study various inter-connected problems that are of significance in sub-surface porous media applications. The first section studies an application of mortar (as well as nonmortar, i.e., enhanced velocity) mixed finite element methods (MMFEM and EV-MFEM) to problems in porous media flow. The mortar spaces are first used to develop a multiscale approach for parabolic problems in porous media applications. The implementation of the mortar mixed method is presented for two-phase immiscible flow and some a priori error estimates are then derived for the case of slightly compressible single-phase Darcy flow. Following this, the problem of modeling flow coupled to reactive transport is studied. Applications of such problems include modeling bio-remediation of oil spills and other subsurface hazardous wastes, angiogenesis in the transition of tumors from a dormant to a malignant state, contaminant transport in groundwater flow and acid injection around well bores to increase the permeability of the surrounding rock. Several numerical results are presented that demonstrate the efficiency of the method when compared to traditional approaches. The section following this examines (non-mortar) enhanced velocity finite element methods for solving multiphase flow coupled to species transport on non-matching multiblock grids. The results from this section indicate that this is the recommended method of choice for such problems. Next, a mortar finite element method is formulated and implemented that extends the scope of the classical mortar mixed finite element method developed by Arbogast et al [12] for elliptic problems and Girault et al [62] for coupling different numerical discretization schemes. Some significant areas of application include the coupling of pore-scale network models with the classical continuum models for steady single-phase Darcy flow as well as the coupling of different numerical methods such as discontinuous Galerkin and mixed finite element methods in different sub-domains for the case of single phase flow [21, 109]. These hold promise for applications where a high level of detail and accuracy is desired in one part of the domain (often associated with very small length scales as in pore-scale network models) and a much lower level of detail at other parts of the domain (at much larger length scales). Examples include modeling of the flow around well bores or through faulted reservoirs. The next section presents a parallel stochastic approximation method [68, 76] applied to inverse modeling and gives several promising results that address the problem of uncertainty associated with the parameters governing multiphase flow partial differential equations. For example, medium properties such as absolute permeability and porosity greatly influence the flow behavior, but are rarely known to even a reasonable level of accuracy and are very often upscaled to large areas or volumes based on seismic measurements at discrete points. The results in this section show that by using a few measurements of the primary unknowns in multiphase flow such as fluid pressures and concentrations as well as well-log data, one can define an objective function of the medium properties to be determined, which is then minimized to determine the properties using (as in this case) a stochastic analog of Newton’s method. The last section is devoted to a significant and current application area. It presents a parallel and efficient iteratively coupled implicit pressure, explicit concentration formulation (IMPEC) [52–54] for non-isothermal compositional flow problems. The goal is to perform predictive modeling simulations for CO₂sequestration experiments. While the sections presented in this work cover a broad range of topics they are actually tied to each other and serve to achieve the unifying, ultimate goal of developing a complete and robust reservoir simulator. The major results of this work, particularly in the application of MMFEM and EV-MFEM to multiphysics couplings of multiphase flow and transport as well as in the modeling of EOS non-isothermal compositional flow applied to CO₂sequestration, suggest that multiblock/multimodel methods applied in a robust parallel computational framework is invaluable when attempting to solve problems as described in Chapter 7. As an example, one may consider a closed loop control system for managing oil production or CO₂sequestration experiments in huge formations (the “instrumented oil field”). Most of the computationally costly activity occurs around a few wells. Thus one has to be able to seamlessly connect the above components while running many forward simulations on parallel clusters in a multiblock and multimodel setting where most domains employ an isothermal single-phase flow model except a few around well bores that employ, say, a non-isothermal compositional model. Simultaneously, cheap and efficient stochastic methods as in Chapter 8, may be used to generate history matches of well and/or sensor-measured solution data, to arrive at better estimates of the medium properties on the fly. This is obviously beyond the scope of the current work but represents the over-arching goal of this research.Show more