Development of Adaptive Implicit Chemical and Compositional Reservoir Simulators PDF Download
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Author: Bruno Ramon Batista Fernandes
Publisher:
ISBN:
Category :
Languages : en
Pages : 0
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Book Description
Reservoir simulators are important tools used in the oil industry for evaluating field opportunity, reservoir management, and reserve estimation. Such tools are based on complex physics and mathematics that require fast solution in order to provide better production scenarios and history matching. In this work, algorithms for solving the partial differential equations arising in modeling compositional miscible gas flooding and chemical EOR processes are presented. Herein, the algorithms presented are based on time discretization schemes known as IMPEC (Implicit Pressure explicit compositions), fully implicit and a combination of these two approaches known as adaptive implicit (AIM). The main goal of this work is to improve the performance of the simulations. For compositional miscible gas flooding, the following approaches are implemented: Natural variables, extensive global variables, and a novel intensive global variable fully implicit approach, an AIM from the literature, and a new AIM. The implementation considers Cartesian grids and fractured reservoirs using the embedded discrete fracture method. Additionally, all implementation considers up to four phases, which is novel for the adaptive implicit methods. For the chemical EOR the following formulations are developed: FI approaches (global variable, natural variable, and mixed variable) and a global variable adaptive implicit. All important features for polymer and surfactant flooding are considered. New models proposed in this work and in the literature to relative permeability, capillary desaturation curves, and critical micelle concentration are implemented to demonstrate the importance of handling the phase transition in order for the FI/AIM be successful in simulating real applications. In order to help the development of the aforementioned formulation an automatic differentiation tool was developed to reduce the timeframe for implementation. All the above formulations are implemented to Cartesian grids, but the global variables for chemical EOR is also implemented for corner point grids that can handle hanging nodes. We also develop a framework that can easily include any type of grid (Cartesian, corner point, unstructured) that is still under development. All the aforementioned formulations are included in two in-house simulators from The University of Texas at Austin named UTCOMPRS and UTCHEMRS. The results for both simulators are compared to the original IMPEC approaches of these simulators and to results of several commercial simulators. From the results, we can clearly observe that the new formulations proposed in this work not only are robust and improve the computational performance of the aforementioned simulators, but also have computational performance similar to the commercial simulators largely used in the oil industry
Author: Bruno Ramon Batista Fernandes
Publisher:
ISBN:
Category :
Languages : en
Pages : 0
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Book Description
Reservoir simulators are important tools used in the oil industry for evaluating field opportunity, reservoir management, and reserve estimation. Such tools are based on complex physics and mathematics that require fast solution in order to provide better production scenarios and history matching. In this work, algorithms for solving the partial differential equations arising in modeling compositional miscible gas flooding and chemical EOR processes are presented. Herein, the algorithms presented are based on time discretization schemes known as IMPEC (Implicit Pressure explicit compositions), fully implicit and a combination of these two approaches known as adaptive implicit (AIM). The main goal of this work is to improve the performance of the simulations. For compositional miscible gas flooding, the following approaches are implemented: Natural variables, extensive global variables, and a novel intensive global variable fully implicit approach, an AIM from the literature, and a new AIM. The implementation considers Cartesian grids and fractured reservoirs using the embedded discrete fracture method. Additionally, all implementation considers up to four phases, which is novel for the adaptive implicit methods. For the chemical EOR the following formulations are developed: FI approaches (global variable, natural variable, and mixed variable) and a global variable adaptive implicit. All important features for polymer and surfactant flooding are considered. New models proposed in this work and in the literature to relative permeability, capillary desaturation curves, and critical micelle concentration are implemented to demonstrate the importance of handling the phase transition in order for the FI/AIM be successful in simulating real applications. In order to help the development of the aforementioned formulation an automatic differentiation tool was developed to reduce the timeframe for implementation. All the above formulations are implemented to Cartesian grids, but the global variables for chemical EOR is also implemented for corner point grids that can handle hanging nodes. We also develop a framework that can easily include any type of grid (Cartesian, corner point, unstructured) that is still under development. All the aforementioned formulations are included in two in-house simulators from The University of Texas at Austin named UTCOMPRS and UTCHEMRS. The results for both simulators are compared to the original IMPEC approaches of these simulators and to results of several commercial simulators. From the results, we can clearly observe that the new formulations proposed in this work not only are robust and improve the computational performance of the aforementioned simulators, but also have computational performance similar to the commercial simulators largely used in the oil industry
Author: Wenjun Li (doctor of engineering.)
Publisher:
ISBN:
Category :
Languages : en
Pages : 420
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Book Description
Three compositional reservoir simulators have been developed in the Department of Petroleum and Geosystems Engineering at The University of Texas at Austin (UT-Austin): UTCOMP (miscible gas flooding simulator), UTCHEM (chemical flooding simulator), and GPAS (General Purpose Adaptive Simulator). UTCOMP and UTCHEM simulators have been used by various oil companies for solving a variety of field problems. The efficiency and accuracy of each simulator becomes critically important when they are used to solve field problems. In this study, two well-developed solver packages, SAMG and HYPRE, along with existing solvers were compared. Our numerical results showed that SAMG can be an excellent solver for the usage in the three simulators for solving problems with a high accuracy requirement and long simulation times, and BoomerAMG in HYPRE package can also be a good solver for application in the UTCHEM simulator. In order to investigate the flexibility and the efficiency of a partitioned coupling method, the second part of this thesis presents a new implementation using a partition method for a thermal module in an equation-of-state (EOS) compositional simulator, the General Purpose Adaptive Simulator (GPAS) developed at The University of Texas at Austin. The finite difference method (FDM) was used for the solution of governing partial differential equations. Specifically, the new coupled implementation was based on the Schur complement method. For the partition method, two suitable acceleration techniques were constructed. One technique was the optimized choice of preconditioner for the Schur complement; the other was the optimized selection of tolerances for the two solution steps. To validate the implementation, we present simulation examples of hot water injection in an oil reservoir. The numerical comparison between the new implementation and the traditional, fully implicit method showed that the partition method is not only more flexible, but also faster than the classical, fully implicit method for the same test problems without sacrificing accuracy. In conclusion, the new implementation of the partition method is a more flexible and more efficient method for coupling a new module into an existing simulator than the classical, fully implicit method. The third part of this thesis presents another type of coupling method, iterative coupling methods, which has been implemented into GPAS with thermal module, FICM (Fully, Iterative Coupling Method) and GICM (General, Iterative Coupling Method), LICM (Loose, Iterative Coupling Method). The results show that LICM is divergent, and GICM and FICM can work normally. GICM is the fastest among the compared methods, and FICM has a similar efficiency as CFIM (Classic Fully Implicit Method). Although GICM is the fastest method, GICM is less accurate than FICM for in the test cases carried out in this study.
Author: Nariman Fathi Najafabadi
Publisher:
ISBN:
Category :
Languages : en
Pages : 0
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Book Description
As easy target reservoirs are depleted around the world, the need for intelligent enhanced oil recovery (EOR) methods increases. The first part of this work is focused on modeling aspects of novel chemical EOR methods for naturally fractured reservoirs (NFR) involving wettability modification towards more water wet conditions. The wettability of preferentially oil wet carbonates can be modified to more water wet conditions using alkali and/or surfactant solutions. This helps the oil production by increasing the rate of spontaneous imbibition of water from fractures into the matrix. This novel method cannot be successfully implemented in the field unless all of the mechanisms involved in this process are fully understood. A wettability alteration model is developed and implemented in the chemical flooding simulator, UTCHEM. A combination of laboratory experimental results and modeling is then used to understand the mechanisms involved in this process and their relative importance. The second part of this work is focused on modeling surfactant/polymer floods using a fully implicit scheme. A fully implicit chemical flooding module with comprehensive oil/brine/surfactant phase behavior is developed and implemented in general purpose adaptive simulator, GPAS. GPAS is a fully implicit, parallel EOS compositional reservoir simulator developed at The University of Texas at Austin. The developed chemical flooding module is then validated against UTCHEM.
Author: Farhad Tarahhom
Publisher:
ISBN:
Category :
Languages : en
Pages : 508
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Book Description
A large percentage of oil and gas reservoirs in the most productive regions such as the Middle East, South America, and Southeast Asia are naturally fractured reservoirs (NFR). The major difference between conventional reservoirs and naturally fractured reservoirs is the discontinuity in media in fractured reservoir due to tectonic activities. These discontinuities cause remarkable difficulties in describing the petrophysical structures and the flow of fluids in the fractured reservoirs. Predicting fluid flow behavior in naturally fractured reservoirs is a challenging area in petroleum engineering. Two classes of models used to describe flow and transport phenomena in fracture reservoirs are discrete and continuum (i.e. dual porosity) models. The discrete model is appealing from a modeling point of view, but the huge computational demand and burden of porting the fractures into the computational grid are its shortcomings. The affect of natural fractures on the permeability anisotropy can be determined by considering distribution and orientation of fractures. Representative fracture permeability, which is a crucial step in the reservoir simulation study, must be calculated based on fracture characteristics. The diagonal representation of permeability, which is customarily used in a dual porosity model, is valid only for the cases where fractures are parallel to one of the principal axes. This assumption cannot adequately describe flow characteristics where there is variation in fracture spacing, length, and orientation. To overcome this shortcoming, the principle of the full permeability tensor in the discrete fracture network can be incorporated into the dual porosity model. Hence, the dual porosity model can retain the real fracture system characteristics. This study was designed to develop a novel approach to integrate dual porosity model and full permeability tensor representation in fractures. A fully implicit, parallel, compositional chemical dual porosity simulator for modeling naturally fractured reservoirs has been developed. The model is capable of simulating large-scale chemical flooding processes. Accurate representation of the fluid exchange between the matrix and fracture and precise representation of the fracture system as an equivalent porous media are the key parameters in utilizing of dual porosity models. The matrix blocks are discretized into both rectangular rings and vertical layers to offer a better resolution of transient flow. The developed model was successfully verified against a chemical flooding simulator called UTCHEM. Results show excellent agreements for a variety of flooding processes. The developed dual porosity model has further been improved by implementing a full permeability tensor representation of fractures. The full permeability feature in the fracture system of a dual porosity model adequately captures the system directionality and heterogeneity. At the same time, the powerful dual porosity concept is inherited. The implementation has been verified by studying water and chemical flooding in cylindrical and spherical reservoirs. It has also been verified against ECLIPSE and FracMan commercial simulators. This study leads to a conclusion that the full permeability tensor representation is essential to accurately simulate fluid flow in heterogeneous and anisotropic fracture systems.
Author: Knut-Andreas Lie
Publisher: Cambridge University Press
ISBN: 1108492436
Category : Business & Economics
Languages : en
Pages : 677
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Book Description
Presents numerical methods for reservoir simulation, with efficient implementation and examples using widely-used online open-source code, for researchers, professionals and advanced students. This title is also available as Open Access on Cambridge Core.
Author: Masoud Behzadinasab
Publisher:
ISBN:
Category :
Languages : en
Pages : 256
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Book Description
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.
Author: Stanislav Ursegov
Publisher: Springer Nature
ISBN: 3030674746
Category : Science
Languages : en
Pages : 91
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Book Description
This book presents unique features of the adaptive modeling approach based on new machine learning algorithms for petroleum exploration, development, and production. The adaptive approach helps simulation engineers and geoscientists to create adequate geological and hydrodynamic models. This approach is proven to be a real alternative to traditional techniques, such as deterministic modeling. Currently, machine-learning algorithms grow in popularity because they provide consistency, predictiveness, and convenience. The primary purpose of this book is to describe the theoretical state of the adaptive approach and show some examples of its implementation in simulation and forecasting different reservoir processes.
Author: Feng Pan (Ph. D.)
Publisher:
ISBN:
Category :
Languages : en
Pages : 652
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Book Description
For a stress-sensitive or stress-dependent reservoir, the interactions between its seepage field and in situ stress field are complex and affect hydrocarbon recovery. A coupled geomechanics and fluid-flow model can capture these relations between the fluid and solid, thereby presenting more precise history matchings and predictions for better well planning and reservoir management decisions. A traditional reservoir simulator cannot adequately or fully represent the ongoing coupled fluid-solid interactions during the production because of using the simplified update-formulation for porosity and the static absolute permeability during simulations. Many researchers have studied multiphase fluid-flow models coupled with geomechanics models during the past fifteen years. The purpose of this research is to develop a coupled geomechanics and compositional model and apply it to problems in the oil recovery processes. An equation of state compositional simulator called the General Purpose Adaptive Simulator (GPAS) is developed at The University of Texas at Austin and uses finite difference / finite control volume methods for the solution of its governing partial differential equations (PDEs). GPAS was coupled with a geomechanics model developed in this research, which uses a finite element method for discretization of the associated PDEs. Both the iteratively coupled solution procedure and the fully coupled solution procedure were implemented to couple the geomechanics and reservoir simulation modules in this work. Parallelization, testing, and verification for the coupled model were performed on parallel clusters of high-performance workstations. MPI was used for the data exchange in the iteratively coupled procedure. Different constitutive models were coded into GPAS to describe complicated behaviors of linear or nonlinear deformation in the geomechanics model. In addition, the geomechanics module was coupled with the dual porosity model in GPAS to simulate naturally fractured reservoirs. The developed coupled reservoir and geomechanics simulator was verified using analytical solutions. Various reservoir simulation case studies were carried out using the coupled geomechanics and GPAS modules.
Author: Feng Pan
Publisher:
ISBN:
Category :
Languages : en
Pages : 652
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Book Description
For a stress-sensitive or stress-dependent reservoir, the interactions between its seepage field and in situ stress field are complex and affect hydrocarbon recovery. A coupled geomechanics and fluid-flow model can capture these relations between the fluid and solid, thereby presenting more precise history matchings and predictions for better well planning and reservoir management decisions. A traditional reservoir simulator cannot adequately or fully represent the ongoing coupled fluid-solid interactions during the production because of using the simplified update-formulation for porosity and the static absolute permeability during simulations. Many researchers have studied multiphase fluid-flow models coupled with geomechanics models during the past fifteen years. The purpose of this research is to develop a coupled geomechanics and compositional model and apply it to problems in the oil recovery processes. An equation of state compositional simulator called the General Purpose Adaptive Simulator (GPAS) is developed at The University of Texas at Austin and uses finite difference / finite control volume methods for the solution of its governing partial differential equations (PDEs). GPAS was coupled with a geomechanics model developed in this research, which uses a finite element method for discretization of the associated PDEs. Both the iteratively coupled solution procedure and the fully coupled solution procedure were implemented to couple the geomechanics and reservoir simulation modules in this work. Parallelization, testing, and verification for the coupled model were performed on parallel clusters of high-performance workstations. MPI was used for the data exchange in the iteratively coupled procedure. Different constitutive models were coded into GPAS to describe complicated behaviors of linear or nonlinear deformation in the geomechanics model. In addition, the geomechanics module was coupled with the dual porosity model in GPAS to simulate naturally fractured reservoirs. The developed coupled reservoir and geomechanics simulator was verified using analytical solutions. Various reservoir simulation case studies were carried out using the coupled geomechanics and GPAS modules.
Author: Rami Mustafa Younis
Publisher: Stanford University
ISBN:
Category :
Languages : en
Pages : 206
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Book Description
As conventional hydrocarbon resources dwindle, and environmentally-driven markets start to form and mature, investments are expected to shift into the development of novel emerging subsurface process technologies. While these processes are characterized by a high commercial potential, they are also typically associated with high technical risk. The time-to-market along comparable development pipelines, such as for Enhanced Oil Recovery (EOR) methods in the Oil and Gas sector, is on the order of tens of years. It is anticipated that in the near future, there will be much value in developing simulation tools that can shorten time-to-market cycles, making investment shifts more attractive. There are two forces however that may debilitate us from delivering simulation as a scientific discovery tool. The first force is the growing nonlinearity of the problem base. The second force is the flip-side of a double edged sword; a rapidly evolving computer architecture scene. The first part of this work concerns the formulation and linearization of nonlinear simultaneous equations; the archetypal inflexible component of all large scale simulators. The proposed solution is an algorithmic framework and library of data-types called the Automatically Differentiable Expression Templates Library (ADETL). The ADETL provides generic representations of variables and discretized expressions on a simulation grid, and the data-types provide algorithms employed behind the scenes to automatically compute the sparse analytical Jacobian. Using the library, large-scale simulators can be developed rapidly by simply writing the residual equations, and without any hand differentiation, hand crafted performance tuning loops, or any other low-level constructs. A key challenge that is addressed is in enabling this level of abstraction and programming ease while making it easy to develop code that runs fast. Faster than any of several existing automatic differentiation packages, faster than any purely Object Oriented implementation, and at least in the order of the execution speed of code delivered by a development team with hand-optimized residuals, analytical derivatives, and Jacobian assembly routines. A second challenge is in providing a generic multi-layered software framework that incorporates plug-in low-level constructs tuned to emerging architectures. The inception of the ADETL spurred an effort to develop the new generation AD-GPRS simulator, which we use to demonstrate the powers of the ADETL. We conclude with a thought towards a future where simulators can write themselves. The second part of this work develops nonlinear methods that can exploit the nature of the underlying physics to deal with the current and upcoming challenges in physical nonlinearity. The Fully Implicit Method offers unconditional stability of the discrete approximations. This stability comes at the expense of transferring the inherent physical stiffness onto the coupled nonlinear residual equations that are solved at each timestep. Current reservoir simulators apply safe-guarded variants of Newton's method that can neither guarantee convergence, nor provide estimates of the relation between convergence rate and timestep size. In practice, timestep chops become necessary, and they are guided heuristically. With growing complexity, convergence difficulties can lead to substantial losses in computational effort and prohibitively small timesteps. We establish an alternate class of nonlinear iteration that converges and that associates a timestep to each iteration. Moreover, the linear solution process within each iteration is performed locally. Several challenging examples are presented, and the results demonstrate the robustness and computational efficiency of the proposed class of methods. We conclude with thoughts to unify timestepping and iterative nonlinear methods.
