bluuebunny/crossref_metadata_2025_split huggingface dataset:
M3E_LINSOL: A Scalable Linear Solver Package for Reservoir Simulations on Massively Parallel Computers
Authors: Ferronato M. , Paludetto Magri V. A. , Janna C. , Franceschini A. 
Published: February 2017

Abstract
A numerical package called M3E_LINSOL for the solution of large linear systems of equations arising from reservoir simulations is presented. This suite includes Krylov-based solvers combined with a set of Factorized Sparse Approximate Inverse (FSAI) preconditioners specifically designed for massively parallel architectures. The computational efficiency and scalability of these preconditioners is evaluated according to challenging real-world reservoir problems.
A New Multiscale Computational Model for Low Salinity Alkaline Waterflooding in Clay-Bearing Sandstones
Authors: Lima Sidarta A. , Murad Marcio A. , Domingues Ramon 
Published: February 2017

Abstract
We develop a new multiscale model to compute effective properties such as relative permeabilities in low salinity EOR processes in sandstones containing reactive surfaces of kaolinite clays. The approach proposed herein considers the local nanoscale description ruled by the electro-chemistry of an aqueous electrolyte solution containing Na+, Ca2+, H+ and OH- ions lying between a crude-oil droplet and clay substrate. By considering concomitant surface complexation geochemical reactions between the ionic species in the invading water and the electrically charged kaolinite surface and oilwater interface we build-up the local electric double layer problem for the electric potential based on a generalized Poisson-Boltzmann equation with nonlinear boundary conditions ruled by the geochemical reactions. By considering the local mechanical equilibrium of the electrolyte solution and solving numerically the Poisson Boltzmann problem by finite elements we compute the disjoining pressure for a wide range of brine compositions. Moreover by invoking the Frumkin/Derjaguin wetting equation, the balance between the local disjoining and capillary pressures provides highly accurate computations of the contact angle along with its dependence on pH and salinity. Such methodology allows to compute wettability alteration of the rock surface from preferential oil to water wetness. The upscaling of this result allows to compute precisely the additional dependency of relative permeability on brine composition. Computational simulations illustrate the potential of the model proposed herein in bridging the pore-scale description, ruled by the local electro-chemistry of the thin liquid film, and the constitutive law for the relative permeabilities in low salinity alkaline waterflooding.
Model Order Reduction and Control Polynomial Approximation for Well-Control Production Optimization
Authors: Sorek N. , Zalavadia H. , Gildin E. 
Published: February 2017

Abstract
The objective of this paper is to reduce the computational effort in reservoir flooding optimization problems by a combination of different optimization parametrization methods and model order reduction techniques. We compare three different parametrization methods that reduce the cardinality of the original infinite set of control-decision variables to a finite set. The three methods include a traditional piece-wise constant (PWC) approximation, a polynomial approximation by Chebyshev orthogonal polynomials and a piece-wise polynomial approximation by cubic Spline interpolation. The Proper Orthogonal Decomposition with Discrete Empirical Interpolation Method (POD-DEIM) accomplishes the reduced order modeling (ROM)..
We compare a gradient-free global stochastic search approach and a gradient-based local search approach. We used Particle Swarm Optimization (PSO) as a gradient-free algorithm and Interior-Point Optimization (IPOPT) with L-BFGS method as a gradient-based algorithm. First, we compare the performances of the three parametrization methods solved by each optimizer, using fine scale simulations for an increasing level of parametrization refinement. Then, in the second part of this paper, we combine the parametrization methods with the reduced modeling workflow. For a given level of parametrization refinement, we compare the performance of each parametrization method coupled with POD-DEIM, and solved by each optimizer. In this part, we introduce an online training procedure, where the first optimization iteration is used to construct the snapshot matrix.
The results demonstrate how refining the control approximation with more decision variables per well lead to better NPV values, but with a higher computational cost. The best NPV was achieved using the highest refining level with Chebyshev polynomial approximation. Both polynomial and piece-wise polynomial approximations served as better training sets for POD-DEIM leading to a more accurate and fast reduced model. With the strategy proposed, POD-DEIM showed the best optimization accuracy for Chebyshev polynomial with the gradient-free optimizer, thus permitting the use of the model reduction methodology for global-stochastic search methods. However, the gradient-based approach seems to consistently outperform the gradient-free approach in terms of NPV and number of iterations for the cases shown.
A New Four-Phase Flash Algorithm for Surfactant Flood Simulation
Authors: Han Choongyong , Chang Yih-Bor , Wolfsteiner Christian , Shi Xundan , Schrader Mark 
Published: February 2017

Abstract
In the recent surfactant flood simulations, there have been efforts to consider the well-known effect of oil composition on the surfactant phase behavior. In order to truly take this effect into account, hydrocarbon phase behavior needs to be coupled with the surfactant phase behavior to evaluate more accurate oil composition, especially when gaseous phase could exist in a reservoir during a simulation. Also, there is a strong need to have this coupling in a fully implicit, fully coupled (shortly, FIM) simulator in order to get all the benefits from the FIM numerical solution approach in surfactant flood simulations.
In this study, therefore, we propose a new gaseous/oleic/microemulsion/aqueous phase flash algorithm to couple the hydrocarbon phase behavior with the surfactant phase behavior in our FIM simulator using a new set of non-linear solution variables. Instead of using the phase molar fraction which is one of the conventional natural non-linear solution variables in a FIM simulator, we use various concentrations/fractions along with pressure and phase saturation as input for the four phase flash algorithm. The concentrations/fractions are the non-linear solution variables newly introduced to our FIM simulator.
With the new algorithm, we can easily consider the cation exchange on surfactant and the indirect effect of volume of surfactant adsorbed on rock in the four phase flash. We need little conversion work and don't need to locally solve equations for concentrations/fractions even if the variables are required. Also we can incorporate the original two-phase hydrocarbon flash and three-phase surfactant flash models into our four phase flash without modification. These are all the advantages over a four phase flash algorithm using the phase molar fraction as input from the non-linear solve. Moreover, as molar fraction of each component is a calculated intermediate input for the new flash algorithm, any simulator using non-linear solution variables related to component moles can easily adopt the algorithm. This actually allows us to implement the same algorithm with slight extension in one of our well and separator models which use the molar non-linear solution variables.
We have successfully tested and validated the new four phase flash algorithm using our FIM simulator with both conventional natural and mixed non-linear solution variables. Also, we show the algorithm works well with the effect of cation exchange on surfactant phase behavior. The algorithm has great extensibility to adopt any hydrocarbon and surfactant phase behavior models in our FIM simulator with the mixed non-linear solution variables if the models use their own conventional input and output variable types.
Multiscale Finite Volume Method for Discrete Fracture Modeling with Unstructured Grids
Authors: Bosma S. B. , Hajibeygi H. , Tene M. , Tchelepi H. A. 
Published: February 2017

Abstract
A multiscale method for Discrete Fracture Modeling (DFM) using unstructured grids is developed. The fine-scale discrete system is obtained by imposing tetrahedron (triangular for 2D domains) shaped grid cells, while lower-dimensional fractures are imposed at the grid interfaces. The DFM approach is then used to describe the transmissibility coefficients for all the interfaces, including those with the lower-dimensional fractures. On this fine-scale discrete system, a new algebraic multiscale formulation is developed, which first imposes two sets of coarseand dual-coarse grids. The former grid is essential for conservative multiscale formulations, while the second one is used for the calculation of local multiscale basis functions. The coarse-scale partitioning of the fracture and matrix domains is flexible and totally independent. Moreover, the multiscale basis functions are constructed for both the matrix and fracture domains. By construction, the basis functions are a partition of unity. For 2D and 3D test cases, the performance of the multiscale method is systematically assessed. It is shown that the method (with no multiscale iterations) provides accurate results, even for complex fractured systems. The presented multiscale method is a promising framework for real-field application of DFM models.
Robust Geochemical Simulation of Alkali/Surfactant/Polymer Flooding with an Equation of State
Authors: Khorsandi Saeid , Qiao Changhe , Johns Russell T. 
Published: February 2017

Abstract
Alkali-surfactant-polymer (ASP) floods can recover significant amounts of remaining oil after a water flood. Currently, commercial and academic chemical flooding simulators use Hand's model and linear interpolation rules based on a salinity scan to model micro-emulsion phase behavior. Those simple models have significant limitations when the reservoir conditions are different than experimental conditions. Recently an equation-of-state (EoS) based on HLD-NAC was developed that gives improved phase behavior predictions away from the tuned experimental data. The new EoS for SP modeling was incorporated into our in-house compositional simulator, PennSim. In this research, we expand PennSim with an updated flash calculation module that includes alkali and geochemistry. The new simulator can more accurately model ASP flooding since phase behavior changes consistently with aqueous chemistry, oil saturation, alkali concentration, salinity, pressure, and other key variables.
ASP phase behavior depends on many factors including pressure, temperature, oil EACN, and geochemistry. PennSim solves the mass conservation equations of oil acidic components, water, and aqueous solute along with phase equilibrium relations and chemical reactions using an IMPEC approach. The reactions between oleic acids, aqueous and solid species, surfactant adsorption and mineral dissolution reactions are considered. A scalable capillary desaturation curve (CDC) with permeability and porosity is used for heterogeneous field cases. An algebraic multigrid linear solver is used to speed up simulation.
The functionalities of the developed code are demonstrated with multiple injection scenarios, such as the combination of an alkali and polymer slug with and without added synthetic surfactant. Simulations are made to model 1D core floods and 2D heterogeneous reservoirs with multiple wells. The simulation results show that the main difference between the new CDC and traditional CDC curve is the size of the developed oil bank, where the traditional CDC predicts a larger oil bank in the high permeability channel.
Parallel Computation for Complex Wells Modeling in Full-Field Reservoir Simulation
Authors: Al-Shaalan T. M. , Dogru A. H. , Al-Youbi A. H. , Ismail H. 
Published: February 2017

Abstract
This paper discusses the parallel implementation of complex wells modeling in a large-scale simulation. Due to intensive computational requirements of giant reservoirs with hundreds of these complex wells, parallel implementation is essential for practical simulation studies. In this work, a distributed memory approach using message passing interface (MPI) is employed for parallelization where each processor is responsible for the computation of one or more complex wells. For inter-processor communication, a non-blocking technique is utilized to increase the parallel efficiency. Parallel implementation is not the only challenge for large-scale simulation. For instance, full-field simulation with hundreds of complex wells increases the probability of a nonconvergence solution for at least one or more complex wells during reservoir simulation. Robust algorithms are needed to guarantee convergence and improve performance. Therefore, in this paper, we propose treating complex wells as a subsurface network where it can be represented using graph theory. In addition, simulation results for a full-field with hundreds of intelligent complex wells are included. This will show the importance of well coupling with rigorous treatment of downhole controls and devices on accurately modeling large-scale and complex reservoir.
An Improved Boundary Element Method for Modeling Fluid Flow through Fractured Porous Medium
Authors: Cao Yang , Killough John E. 
Published: February 2017

Abstract
To accurately capture the flow behavior and dynamics in fractured reservoirs, a theoretically sound, and practically robust boundary element method (BEM) numerical algorithm has been developed and successfully implemented. Explicit and discrete fracture description is adopted in this approach, and the complex fracture settings and interactions can be effectively simulated. Modules characterizing the transient flow dynamics and the flow dependence on matrix heterogeneity, which are seldom studied by previous researchers through a BEM approach, have also been established and investigated.
Specifically, our model starts from two simplifications: the flow inside the fractures is treated as twodimensional, and the fractures can be equivalently seen as planar source or sink entities interacting with the matrix. In our approach, only the matrix boundaries and fractures are discretized into small elements, and each element associates with either one or two unknowns. Two sets of equations generated from the above two simplifications are used to relate these unknowns and solve the problem. And when the flow transientness and matrix heterogeneity are concerned, additional internal matrix points are selected and taken into computation, following the procedure of the dual reciprocity boundary element method (DRBEM).
Several case studies have been conducted, and result comparison indicates the validity of this approach. Finally the strength and weakness of our approach are also discussed in this paper.
A Physics-Based Data-Driven Model for History-Matching, Prediction and Characterization of Waterflooding Performance
Authors: Guo Zhenyu , Reynolds Albert C. , Zhao Hui 
Published: February 2017

Abstract
We develop a new data-driven model for the assisted history matching of production data from a reservoir under waterflood. Although the model is developed from production data and requires no prior knowledge of rock property fields, it incorporates far more fundamental physics than that of the popular capacitance-resistance model (CRM). The new model also represents a substantial improvement on an interwell numerical simulation model (INSIM) which was presented previously in a paper co-authored by the last two authors of the current paper. The new model, which is referred to as INSIM-FT, eliminates the three deficiencies of the original INSIM data-driven model. (1) For some complex cases, e.g., when a producer is converted to an injector or when injected water from more than one injector passes through an intermediate well node, the INSIM procedure for calculation of water saturation degrades to an ad hoc calculation which introduces inaccuracies. Our new model uses an accurate front-tracking procedure to calculate water saturation, hence the name INSIM-FT. (2) The original INSIM formulation assumes relative permeabilities are known a priori which defeats the objective of finding a model without requiring knowledge of petrophysical properties; INSIM-FT estimates relative permeabilities by historymatching. (3) Unlike CRM, the original INSIM model does not provide a reasonable characterization of how water from an injector is allocated among producers and thus does not reliably identify large-scale geological features such as faults. INSIM-FT remedies this INSIM deficiency.
The reliability of INSIM-FT for history-matching, future reservoir performance prediction and reservoir characterization is validated with two synthetic models, and its performance is compared with that of CRM. Finally, INSIM-FT is applied to a field case.
GPU-Offloaded General Purpose Simulator for Multiphase Flow in Porous Media
Authors: Khait Mark , Voskov Denis 
Published: February 2017

Abstract
Reservoir simulation plays an important role in the petroleum industry. Today, there is a specific demand to run ensembles of megaand even giga-cell models. The iterative solution of the large systems of nonlinear governing equations, which describe the multiphase mass transfer in the subsurface, takes the most of the simulation time. The linearization part of the solution process occupies a significant fraction of that time, especially in compositional models. Moreover, the implementation of the linearization step usually embodies the most substantial, complex, and specific part of the computational loop in modern simulators, defining which physical mechanisms and assumptions are employed. This significantly complicates the implementation of simulation codes for heterogeneous computing hardware, which promises significant improvements in simulation time. In this work, we use the recently proposed Operator-Based Linearization (OBL) approach to develop a general purpose reservoir simulation code aiming to substantially decrease the simulation time. OBL offers a simplified linearization method, enhancing the computational performance of simulation and providing an opportunity of a painless porting to heterogeneous computing architectures. To distinct the contribution of both factors, we developed two versions of the compositional simulation prototype code: for traditional CPU and GPU-accelerated hardware architectures. While the former allowed us to speed the linearization stage up by an order of magnitude in comparison with the conventional approach, based on Automatic Differentiation (AD), the latter improved it further by another order of magnitude. The developed prototype realizes the potential of the OBL approach and GPU computing architecture, proving significant improvement in general purpose simulation performance.
The Order of Accuracy of the Fixed-Stress Type Two-Pass and Deferred Correction Methods for Poromechanics
Authors: Yoon H. C. , Kim J. 
Published: February 2017

Abstract
We study the order of accuracy in time discretization for poromechanics, applying the fixed-stress split scheme. High-order methods in time are often used, for example, in order to match high-order schemes in space. We consider two operator splitting methods motivated from the fixed-stress split: a two-pass algorithm and a spectral deferred correction (SDC) method. The two-pass algorithm, known for a symmetric operator splitting scheme as Strang's splitting, is typically employed for a high-order method of non-stiff ordinary differential equations (ODEs). The SDC method is also a structure conserving efficient scheme for an arbitrary high-order of accuracy. However, poromechanics yields the governing equations that have a form of differential algebraic equations (DAEs), where typical high-order time integration schemes for non-stiff ODEs are not appropriate. Performing mathematical analysis, we find that both methods do not achieve high-order accuracy in poromechanics, although both methods can reduce the errors in their time discretizations. From numerical experiments, we find that the mathematic estimates are consistent with the numerical results of the fixed-stress type two-pass and SDC methods, which still provide the first-order accuracy in time.
Unstructured Gridding and Consistent Discretizations for Reservoirs with Faults and Complex Wells
Authors: Klemetsdal Ø. S. , Berge R. L. , Lie K.-A. , Nilsen H. M. , Møyner O. 
Published: February 2017

Abstract
This work consists of two parts. In the first part, we present new methods for generating unstructured polyhedral grids that align to prescribed geometric objects. Control-point alignment of cell centroids is introduced to accurately represent horizontal and multilateral wells, but can also be used to create volumetric representations of fracture networks. Boundary alignment of cell faces is introduced to accurately preserve geological features such as layers, fractures, faults, and/or pinchouts. Prescribed geometric objects will often intersect each other. To handle such cases, we propose a conflict-point handling scheme that creates conforming cells even at intersections. We also discuss how to generalize this method to 3D. Here, our method honors control-point alignment of cell centroids and boundary alignment of cell faces away from object intersections.
The predominant discretization method for multiphase flow in reservoir simulation is the two-point flux-approximation (TPFA) method. This finite-volume method is mass conservative, but only conditionally consistent and hence susceptible to grid-orientation effects. In the second part of the paper, we review a series of consistent methods and compare and contrast these methods both with respect to accuracy and monotonicity. Our comparisons include a multipoint flux-approximation (MPFA-O) method, the nonlinear TPFA method, mimetic methods, and the more recent virtual element methods. To limit the discussion, we focus on incompressible flow, for which we study the effects of deformed cell geometries, anisotropic permeability, and robustness with respect to various approaches to grid near wells and adapt it to lower-dimensional objects like faults and fractures.