bluuebunny/crossref_metadata_2025_split huggingface dataset:
Adaptive Local-Global VCMP Methods for Coarse-Scale Reservoir Modeling
Authors: Chen T. , Gerritsen M. G. , Durlofsky L. J. , Lambers J. V. 
Published: February 2009

Abstract
Upscaling is often applied to generate practical simulation models from highly detailed geocellular descriptions. In this paper we develop and evaluate a new upscaling procedure – a variable compact multipoint adaptive local-global technique (VCMP-ALG) – that is able to capture, accurately and efficiently, both full-tensor and global flow effects in the coarse model. The method successfully combines the positive attributes of its two underlying component procedures: the variable compact multipoint (VCMP) flux scheme, which provides coarse-scale transmissibilities that are appropriate for use in problems characterized by strong full-tensor permeabilities, and adaptive local-global (ALG) upscaling, which accounts for the effects of large-scale flow in the upscaling computations without solving any global fine-scale flow problems. The performance of the local-global VCMP upscaling technique is evaluated for multiple realizations of oriented variogram-based models and synthetic deltaic systems. Extensive numerical results for 2D cases demonstrate that the VCMP-ALG approach provides better overall accuracy than either of the underlying methods – an extended local VCMP technique and an adaptive local-global procedure based on two-point flux approximations – applied individually. The extension of the VCMP-ALG method to irregular quadrilateral grids is also accomplished. Finally, we present results for two-phase oil-water flows, for which the models based on the VCMP-ALG method again provide the best overall accuracy.
General Nonlinear Solution Strategies for Multiphase Multicomponent EoS Based Simulation
Authors: Voskov D. V. , Younis R. M. , Tchelepi H. A. 
Published: February 2009

Abstract
We present a novel reservoir flow simulation framework built on top of an Automatic Differentiation with Expression Templates Library (ADETL). Given discrete algebraic expressions of the governing conservation equations, associated constraint relations, and equations of state, the ADETL library generates efficient computer code for the corresponding Jacobian matrix. The framework allows for complete flexibility in the specification of the independent variables, which leads to unified simulator for different formulations and solution strategies. We study the behavior of several widely used nonlinear formulations and solution strategies for general-purpose compositional simulation. The numerical behaviors using different variable sets, including the so called natural- and mass-type variables, are investigated. We also report on tie-line based parameterization strategies for compositional modeling. The focus is on the fully implicit method (FIM), where the full Jacobian (primary and secondary algebraic equations in terms of both the primary and secondary variables) is constructed. Schur-complement reduction of the full Jacobian is used to assemble the (reduced) Jacobian for the primary equations as a function of the primary unknowns only. The numerical challenges associated with the nonlinear hydrodynamic and thermo-dynamic interactions associated with compositional displacement processes are the focus of this investigation. These include phase appearance and disappearance, crossing into and out of the critical region, wide pressure variations in space and time. The behavior of the Newton iterations as a function of timestep size is analyzed for different variable sets, alignment of equations (including linear and nonlinear constraints), and nonlinear updating strategies. Comparisons are performed for several challenging multi-phase multi-component problems of practical interest.
Detailed Near-Well Darcy-Forchheimer Flow Modeling and Upscaling on Unstructured 3D Grids
Authors: Karimi-Fard M. , Durlofsky L. J. 
Published: February 2009

Abstract
Computing well performance accurately is very important for reservoir management and optimization. Standard large-scale reservoir simulators, however, are not able to resolve detailed near-well physics such as the interaction between the local pressure gradient, reservoir heterogeneity, and well completion. This is because these effects occur on scales that are very small compared to typical simulation grid blocks. In this work, we describe a modeling procedure for representing the well and near-well region that is able to resolve flow down to the scale of the completion and perforations. Our computations involve single-phase flow simulations on unstructured 3D tetrahedral grids. The Darcy-Forchheimer equation is solved in order to include non-Darcy effects, which can be important in the near-well region where fluid velocities are high. The new modeling capability is applied to quantify the impact of completion type – open hole or perforated cased hole – on well productivity. Next, in order to capture these detailed effects in large-scale simulation models, a new upscaling procedure is developed and applied. The approach can be categorized as a local-global upscaling method which uses global coarse-scale simulations to provide key parameters for the local upscaling computations. An example for a case with significant non-Darcy effects demonstrates the high degree of accuracy achievable using this technique.
A Novel Approach to Integrate Dual Porosity Model and Full Permeability Tensor Representation in Fractures
Authors: Tarahhom Farhad , Sepehrnoori Kamy , Marcondes Francisco 
Published: February 2009

Abstract
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 in porting the fractures into the computational grid are its shortcomings. On the other hand, 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.
Expelling oil from matrix blocks into fractures based on water imbibition leaves behind significant amounts of oil in the matrix blocks in the form of residual oil. Chemical flooding is an excellent means to expel more oil from the matrix into fractures. A fully implicit parallel, compositional chemical dual porosity model in conjunction with full permeability tensor for the fracture system has been developed. The model is capable of simulating large-scale chemical flooding processes. 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 the UTCHEM simulator. Results show excellent agreements for a variety of flooding processes. Full permeability tensor results were also verified with a discrete fracture simulator.
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.
Development of a Three Phase, Fully Implicit, Parallel Chemical Flood Simulator
Authors: Najafabadi N. Fathi , Han C. , Delshad M. , Sepehrnoori K. 
Published: February 2009

Abstract
Field-scale applications of chemical flooding become more attractive with higher oil prices. Several pilot and commercial scale chemical floods are currently in operation or design. Economic feasibility of such projects relies on how cost-effectively the remaining oil volume is recovered. Robust design and optimization are essential for technical success and profitability. The main objective in chemical flooding design is to keep the surfactant in Type III near the optimum salinity. Salinity gradient design is a robust design since it can compensate for heterogeneity and reservoir uncertainties and guarantees the surfactant in Type III for a longer time compared to other designs. A comprehensive surfactant phase behavior model is required to take into account the salinity gradient design with all possible phase transitions.
The development discussed in this paper enables accurate modeling and optimization of chemical flooding designs for realistic field-scale projects where a salinity gradient exists naturally or is imposed by design. The parallel processing capability combined with the fully implicit scheme allows high-resolution full field scale chemical flooding simulations. Comprehensive surfactant phase behavior as a function of water salinity has been implemented into a fully implicit and parallel equation of state (EOS) compositional simulator, GPAS. The fully implicit simulation results are validated against an IMPES chemical flooding simulator.
Accurate simulation of chemical processes requires fine grid resolution which adds a large computational overhead for modeling field-scale projects. Our enhanced simulator will allow for high resolution, field-scale design and optimization of chemical flooding projects. This is the first fully implicit, chemical-EOS compositional simulator with a comprehensive surfactant phase behavior that can take into account the effect of salinity and the resulting two or three phase flow with efficient parallel scalability.
A New Solution Procedure for a Fully Coupled Geomechanics and Compositional Reservoir Simulator
Authors: Pan Feng , Sepehrnoori Kamy , Chin L. Y. 
Published: February 2009

Abstract
Traditional reservoir simulators cannot capture the complicated interactions between fluid production and reservoir rock deformation during hydrocarbon recovery. In particular, in a recovery process when both phase behavior and deformation of reservoir rock play critical roles, a coupled geomechanics and compositional reservoir model can rigorously capture the above physical relations between solid and fluids and thereby perform more precise history matchings and predictions for better well planning and reservoir management decisions.
This paper considers a fully coupled geomechanics and compositional modeling process. A novel solution procedure for the associated fully coupled Jacobian system is presented using the Schur complement technique. The proposed approach has the following features: (1) it has similar convergence properties as the fully implicit method, (2) combined with Krylov subspace iterative solvers, it can deal with symmetric and unsymmetric problems, and (3) it can be easily parallelized to solve large-scale reservoir simulation problems.
In this work, a parallel, fully implicit, equation of state compositional reservoir simulator was fully coupled with a geomechanics FEM module. For each Newton iteration, an original two by two block Jacobian system is converted to a Schur complement system, and then the associated Schur complement system is solved using a BiCGstab(l) iterative method; subsequently all the unknowns for the reservoir simulator and the geomechanics module are obtained at the same time. The above partition solution procedure is equivalent to a block Gaussian elimination; hence its convergence is similar to a fully implicit coupled procedure.
The proposed approach is implemented to solve two- and three-dimensional compositional reservoir simulation case studies considering geomechanics effects. We also compare the results between the fully coupled and the iteratively coupled approaches. It is shown that this approach presents a viable alternative in solution methods for solving general coupled physical problems.
Stochastic History Matching of a Deepwater Turbidite Reservoir
Authors: Alpak Faruk O. , van Kats Florian , Hohl Detlef 
Published: February 2009

Abstract
A novel stochastic framework is described that facilities automatic history matching and uncertainty quantification workflows. The underlying algorithm of the framework combines Design of Experiments (DoE) and Markov Chain Monte Carlo (MCMC) inference techniques. A generic singular-value decomposition technique creates a Response Surface Model (RSM) from a DoE-based selection of simulations. Ensuing RSM serves as a rapid proxy to full-physics reservoir simulation. The data integration and uncertainty quantification framework extends current working practice by sampling Bayes' posterior parameter probability distribution with a rigorous MCMC method using the Metropolis-Hastings algorithm. This improves uncertainty estimates in the history-matching mode, and provides a unified platform for scenario management and analysis in the forecast uncertainty quantification mode.
The stochastic framework is tested for robustness and efficiency on a real field case. A history matching study is carried out for a complex deepwater turbidite reservoir involving multiple geologic realizations. Within the context of the study, the stochastic framework delivered (a) a complete description of the high-impact model parameters dominating the quality of the match, (b) multiple models honoring the historical production data, (c) reduced uncertainty ranges for the history-matching parameters, and (d) a quantitative measure of reliability for different measurement types. The outcome of the multi-realization history matching study reveals a better reservoir connectivity and an increased net-sand volume compared to the maximum a-posteriori (MAP) prediction attained by a commercial assisted history-matching software. A well-by-well analysis of the most probable model reveals that the match is comparable or superior to the ones delivered by the commercial tool. The field test outcome demonstrates the reliability, expediency, rigor, and computational efficiency of our stochastic history-matching and recovery forecasting framework.
Estimation of Depths of Fluid Contacts by History Matching Using Iterative Ensemble Kalman Smoothers
Authors: Wang Yudou , Li Gaoming , Reynolds A. C. 
Published: February 2009

Abstract
With the ensemble Kalman filter (EnKF) or smoother (EnKS), it is easy to adjust a wide variety of model parameters by assimilation of dynamic data. We focus on the case where reallizations and estimates of the depths of the initial fluid contacts as well as gridblock rock property fields are generated by matching production data with the EnKS. The objective is to account for uncertainty in the depths of the contacts and provide improved estimates of the depths by conditioning reservoir models to production data. The efficiency of EnKF and EnKS arises because data are assimilated sequentially in time and so "history matching data" requires only one forward run of the reservoir simulator for each ensemble member. For EnKS and EnKF to yield reliable characterizations of the uncertainty in model parameters and future performance predictions, the updated reservoir simulation variables, e.g., saturations and pressures, must be statistically consistent with the realizations of these variables that would be obtained by rerunning the simulator from time zero using the updated model parameters. This statistical consistency can only be established under assumptions of Gaussianity and linearity that do not normally hold. Here, we explore the use of iterative EnKS methods that are statistically consistent to improve the performance of EnKS.
Use of Reduced-Order Modeling Procedures for Production Optimization
Authors: Cardoso M. A. , Durlofsky L. J. 
Published: February 2009

Abstract
The determination of optimal well settings is very demanding computationally, as the simulation model must be run many times during the course of the optimization. For this reason, reduced-order modeling procedures, which are a family of techniques that enable high efficient simulations, are very useful for optimizing problems. In this paper we describe a recently developed reduced-order modeling technique which has been used in other application areas, we describe a recently developed reduced-order modeling technique which has been used in other application areas, the trajectory piecewise linear (TPWL) procedure, and incorporate it in optimization computations. The TPWL methodology represents solutions encountered during the optimization runs in terms of Taylor series expansions around previously simulated states. This requires a small number of preprocessing simulations using the full (high-fidelity) model, during which pressure and saturation states and Jacobian matrices are saved. These states and matrices are then projected into a low-dimensional space using proper orthogonal decomposition. Simulations in this reduced space can be performed very efficiently; in this work we observe runtime speedups of a factor 450.
We assess the TPWL representation for simulations of waterflood in a heterogeneous 3D model containing over 20,000 grid blocks and six wells. The high degree of accuracy of the TPWL model is first demonstrated for several testing simulations in which producer will settings differ from those used in the preprocessing runs. The TPWL representations are then used in several optimizations involving the determination of optimal bottomhole pressures in four producers at six different times (24 control variables). Both gradient-based and generalized pattern search optimization algorithms are considered. Results for optimized net present value using TPWL are shown to be in consistently close agreement with those computed using high-fidelity simulations. Most significantly, when the optimal well settings obtained using TPWL are applied in high-fidelity models, the resulting net present values are within 0.8% of the values determined using the high-fidelity simulations. Our overall conclusion is that the TPWL representation is very well suited for use in production optimization problems.
A New Method for Thermodynamic Equilibrium Computation of Systems With an Arbitrary Number of Phases
Authors: Fraces Gasmi Cédric , Voskov Denis V. , Tchelepi Hamdi A. 
Published: February 2009

Abstract
Reservoir recovery processes involve complex mass and heat transfer between the injected fluid and the resident rock-fluid system. Thermal-compositional reservoir simulators can be used to plan such displacement processes, in which the phase behavior is computed with an Equation of State (EoS). These thermodynamic-equilibrium computations include phase-stability tests and flash calculations, and can consume a significant fraction of the total simulation time, especially for highly detailed reservoir models and a large number of components. Here, we propose a general Compositional Space Parameterization (CSP) method for complex mixtures, especially those where more than two fluid phases can coexist in parts of the parameter space. For a given pressure (P), temperature (T) and overall composition, a unique tie-simplex (tie-line for two phases, tie-triangle for three phases, etc.) can be defined. For a particular composition at P and T, the tie-simplex provides the necessary phase equilibrium information (i.e., phase state and phase compositions). For compositional flow simulation, a set of tie-simplexes can be calculated in a preprocessing step, or adaptively constructed during the simulation. The tie-simplex representation can be used to replace standard phase-equilibrium calculations completely, or it can be used as an initial guess for standard EoS calculations. Challenging examples with two and three phases are presented to validate this tie-simplex CSP approach. Standard EoS methods, which are widely used in industrial compositional simulators, are compared with CSP-based simulations for problems with large numbers of components and complex two- and three-phase behaviors spanning wide ranges of pressure and temperature. The numerical experiments indicate that our multi-dimensional tie-simplex representation combined with linear pressure and temperature interpolation in tie-simplex space, which is implemented as an adaptive tabulation strategy, leads to highly robust and efficient computations of the phase behavior associated with compositional flow simulation.
Optimization of Residual Gas and Solubility Trapping for CO2 Storage in Saline Aquifers
Authors: Nghiem Long , Yang Chaodong , Shrivastava Vijay , Kohse Bruce , Hassam Mohamed , Chen Dingjun , Card Colin 
Published: February 2009

Abstract
The two most important trapping mechanisms for CO2 storage in saline aquifers, namely residual gas trapping and solubility trapping, are examined. It is shown that a water injector located above the CO2 injector can be used to enhance both residual gas trapping and solubility trapping. Using simulation, the optimal location and operating conditions for the water injector are determined for both a low-permeability aquifer and a high-permeability aquifer. The analysis is performed using the concept of Pareto optimal solutions for multiple-objective optimization. It is shown that for a low-permeability aquifer, the use of a water injector can significantly increase the amount of residual gas trapping, which results in a substantial increase in the total trapped amount. For a high-permeability aquifer, the use of a water injector above the CO2 injector does not increase CO2 trapping.
Stability, Accuracy and Efficiency of Sequential Methods for Coupled Flow and Geomechanics
Authors: Kim J. , Tchelepi H. A. , Juanes R. 
Published: February 2009

Abstract
We perform detailed stability and convergence analyses of iteratively coupled solution methods for coupled fluid flow and reservoir geomechanics. We analyse four different operator-split strategies: two schemes in which the mechanical problem is solved first (drained and undrained splits), and two schemes where the flow problem is solved first (fixed-strain and fixed-stress splits). We use the Van Neumann method to obtain sharp stability criteria. The drained and fixed-strain splits, which are commonly used, are only conditionally stable. Their stability limits are independent of time step size and depend only on the strength of the coupling between flow and mechanics. This implies that problems with strong coupling cannot be solved by the drained or fixed-strain split methods. Moreover, oscillations in the solution by the drained and fixed-strain split methods can occur even when the stability limit is honored. For problems where the deformation may be plastic in nature, the drained and fixed-strain sequential schemes suffer from severe stability problems when the system enters the plastic regime. However, the undrained and fixed-stress splitting methods are unconditionally stable regardless of the coupling strength, and they do not suffer from oscillations. We also show that the drained and fixed-strain split methods with a fixed number of iterations are inconsistent. That is, they converge to the wrong solution as the time step size goes to zero. On the other hand, the fully coupled, undrained, and fixed-stress methods are consistent even in the case of a single iteration per time step. While both the undrained and fixed-stress schemes are stable, the fixed-stress method is more accurate for a given number of iterations than the undrained method. As a result, we strongly recommend the fixed-stress split. These results have immediate and widespread applicability in the design of reservoir flow simulators that account for geomechanics.