bluuebunny/crossref_metadata_2025_split huggingface dataset:
Pore Size Variability and Sieving Effect in Liquid Shale—A Multiple Permeability Approach and Eagle Ford Case Study
Authors: Alfi Masoud , An Cheng , Cao Yang , Yan Bicheng , Barrufet Maria A. , Killough John E. 
Published: February 2017

Abstract
We propose a robust multiple permeability model to account for pore size variability and filtration effects in shale reservoirs and to explain the behavior of unconventional resources such as anomalous gas oil ratios. Recent developments in technology transformed unconventional low-permeability shales into reliable energy sources. With regard to capacity, unconventional resources are found to be more abundant than conventional ones. These resources have opened new challenges and technical difficulties along with enhanced capacities. Recent advances in high precision analytical tools have revealed that pore size distribution in shale reservoirs cover a wide range. Molecules in pores with different sizes may exhibit significantly different thermodynamic behavior. Rock fluid interactions and space hindrance effects play an important role when pore sizes become close to species' molecular dimeters. This effect can result in a composition difference between pores with large and small diameters in shale reservoirs (sieving effect), with small pores mostly filled with smaller hydrocarbon molecules and large molecules residing in larger pores. To account for such a diverse behavior, this paper proposes a multiple permeability model, which divides shale media into three different permeability/porosity systems: fracture, matrix with large pores and matrix with small pores. We use a modified version of the Peng Robinson equation of state to model the equilibrium hydrocarbon distribution in large and small pores. Our thermodynamics calculations show that as pore dimeter decreases, the concentration of larger hydrocarbon molecules in those pores decreases because of size filtration. A synthetic reservoir model is used along with the multiple permeability model to analyze reservoir production behavior at different conditions. The so-called sieving effect is believed to be responsible for the anomalous production behavior (lower-than-expected or constant gas oil ratios for extended production periods). Our model is then applied to a real Eagle Ford case to history-match production data with the stimulated reservoir volume built upon the fracture microseismic data. The results show that our multiple permeability model provides a powerful tool to evaluate the complicated flow dynamics in liquid shales.
Algebraic Dynamic Multilevel Method for Compositional Simulations
Authors: Cusini M. , Fryer B. , Kruijsdijk C. P. , Hajibeygi H. 
Published: February 2017

Abstract
A dynamic multilevel compositional solver (C-ADM) is introduced for fully(and sequentially-) implicit systems arising from compositional displacements in natural porous media. The fully (or sequential) implicit system is first described at a fine-scale resolution, where phases are allowed to consist of different components (based on thermodynamics equilibrium). In addition, heterogeneous capillary functions (defined based on Leverett's J-function) and gravitational effects are both considered, adding significantly to the non-linear complexity of the processes. Given this complex fine-scale system for a heterogeneous reservoir, C-ADM defines a dynamic multilevel system, based on an error criterion, where the grid resolution is defined based on the physics of the process as well as geological complexities and location of wells. Once this multilevel grid is defined, sequences of prolongation and restriction operators are employed to obtain an accurate and efficient multilevel system. CADM allows for a general set of prolongation operators, e.g., constant, bilinear (or polynomial), and multiscale basis functions. The restriction operators, however, are constructed based on a mass-conservative finite-volume formulation at all levels. For several challenging test cases it is shown that C-ADM employs only a small fraction of the fine-scale grids to provide an accurate description of the process. C-ADM casts a promising approach in the application of dynamic grid refinement methods for real-field applications.
Simulation of Deviated Wells Using 3D Unstructured Grids of Flexible Resolution
Authors: Artus Vincent , Fructus Dorian , Houzé Olivier 
Published: February 2017

Abstract
A method is presented for the numerical simulation of wells with arbitrary trajectories using 3D unstructured grids, with a resolution that automatically adjusts to the simulation context: for pressure transient analysis (logarithmic time steps) or low permeability reservoirs a very fine grid is used. The grid is progressively coarsened when early-time transients can be ignored and/or mobility increases. Different discretization controls are applied for full late time consistency between the various resolutions.
A criterion is derived to determine the optimum grid resolution based on the mobility of the fluid in the vicinity of the wellbore and the smallest time step to simulate.
The finest grid uses a full 3D voronoi module around the wellbore, with cells of progressively increasing size away. This module is connected to a coarser background 2.5D voronoi grid for the bulk of the reservoir. Generalized transmissibility derivations accurately account for the well trajectory and estimate the fluxes across potentially non-orthogonal connections.
Progressively coarsened grids are then used to adapt to the problem. For relatively fine grids, generalized derivations of transmissibility and well index values capture the radial effects and avoid the numerical pseudo-skin typically observed with 2.5D grids.
As illustrated with various cases, such approach accurately and consistently simulates wells of complex geometries for all resolutions. The outcome is a new method for generating 3D unstructured grids that automatically adapt to the expected time resolution of the simulation, while ensuring consistency between transient and long-term simulations via original discretization controls.
Accurate Dual-Porosity Modeling of CO2 Storage in Fractured Reservoirs
Authors: March Rafael , Elder Herwald , Doster Florian , Geiger Sebastian 
Published: February 2017

Abstract
Naturally fractured reservoirs are currently being considered as potential candidates for geological storage of CO2. Simulations of fractured reservoirs are notoriously challenging. Dual-porosity models are a cost-effective way of representing fractured reservoirs whose fundamental ingredient are transfer functions that represent fracture-matrix interaction in an up-scaled manner. In order to develop accurate transfer functions, it is essential to capture the underlying physics of the fluid transfer. Material properties and dominant processes in CO2 storage differ from the ones in conventional production environments. In this contribution we develop a novel transfer function that accounts for these differences. We first analyse the simplifying hypotheses that are commonly made in the current existing transfer functions. Those simplifications lead to inaccurate results in the context of CO2 storage. We then develop a transfer function for buoyancy displacement based on the timescale of the one-dimensional equation for immiscible two-phase flow in porous media. We analyse how the newly developed transfer functions improve over the current existing ones in simple matrix-block geometries. The results are evaluated against high-resolution numerical simulations of matrix blocks considering realistic physical properties of CO2/Brine systems and fractured rocks. Our results show that the developed transfer functions are able to represent accurately the basic physics of the process, and improve over other existing transfer functions in the literature. The transfer functions are also implemented in a dual-porosity simulator and different CO2 injection scenarios are tested. We show that a careful design of the injection schedule may increase the mass of CO2 that is stored in the matrix block.
Simulation Capability Development for Four-Phase Flow through Porous Media
Authors: Fang Chen , Li Zhidong , Guo Weidong , Chempath Shaji , Selvam Balki , Lu Pengbo 
Published: February 2017

Abstract
Historically, numerical reservoir simulators have been mainly used to model three distinct phases, i.e., hydrocarbon liquid, vapor, and aqueous phases. Not surprisingly, most simulator architectures are designed and implemented within a three-phase framework, for both phase-equilibrium calculations and solving dynamic flow through porous media. Recently, many reservoir recovery processes involve more than one hydrocarbon liquid phase in subsurface, e.g., second hydrocarbon liquid phase forming in CO2 miscible / near-miscible injection, asphaltene deposition induced by gas injection, solvent-based Enhanced Oil Recovery (EOR) processes. Therefore, it is critical to accurately model the formation and flow of four separate phases in the reservoir, namely, heavy hydrocarbon liquid, light hydrocarbon liquid, vapor, and aqueous, or LLVA. Modeling the four-phase flow poses a series of significant numerical modeling challenges that most existing commercial simulators cannot address effectively and reliably. There have been numerous research and development efforts on this topic in both industry and academia. However, most of the proposed approaches require major architecture redesign and significant implementation revamp.
This paper highlights our simulation capability development for modeling four-phase flow in a computationally efficient and numerically stable manner while capturing the essential physics. First of all, we incorporate a newly-developed robust flash algorithm into the phase equilibrium calculations for the three hydrocarbon phases (LLV). Several algorithm improvements have been made to ensure stability and robustness of the flash engine over the full range of pressure and composition variation, without sacrificing computational efficiency. Secondly, a novel fit-for-purpose algorithm has been derived and implemented to model the four-phase (LLVA) flow within the conventional three-phase reservoir simulation framework, avoiding a major code rewrite. The particular algorithm is analytically rigorous and physically sound, suitable for multiple enhanced oil recovery (EOR) processes, for both heavy oil and light oil.
These unique modeling capability enhancements enable us to model complex recovery processes efficiently and effectively and provide the ability to understand the physical processes, design / optimize operating strategy, as well as predict reservoir performance.
Equation-of-State Approach to Model Relative Permeability Including Hysteresis and Wettability Alteration
Authors: Khorsandi Saeid , Li Liwei , Johns Russell T. 
Published: February 2017

Abstract
Commercial compositional simulators commonly apply correlations or empirical relations based on tuned experimental data to calculate phase relative permeabilities. These relations cannot adequately capture effects of hysteresis, fluid compositional variations and rock wettability alteration. Furthermore, these relations require phases to be labeled, which is not accurate for complex miscible or near miscible displacements with multiple hydrocarbon phases. Therefore, these relations can be discontinuous for miscible and near-miscible displacements causing inaccuracies and numerical problems in simulation.
This paper develops an equation-of-state (EoS) to model robustly and continuously the relative permeability as functions of phase saturations and distributions, fluid compositions, rock surface properties, and rock structure. Phases are not labelled; instead, the phases in each grid block are ordered based on their compositional similarity. Phase compositions and rock surface properties are used to calculate wettability and contact angles. The model is tuned to measured two-phase relative permeability curves with few tuning parameters and then used to predict relative permeability away from the measured experimental data. The model is applicable to all flow in porous media processes, but is especially important for low salinity polymer, surfactant, miscible gas and water-alternating-gas flooding. The results show excellent ability to match measured data, and to predict observed trends in hysteresis and oil saturation trapping including those from Land's model and for a wide range in wettability. The results also show that relative permeabilities are continuous at critical points and yields a physically correct numerical solution when incorporated within a compositional simulator (PennSim). The model has very few tuning parameters, and the parameters are directly related to physical properties of rock and fluid, which can be measured. The new model also offers the potential for incorporating results from CT-scans and pore-network models to determine some input parameters for the new EoS.
An Automated Adaptive Scheme for Asynchronous Coupled Flow and Geomechanics Simulation
Authors: Ita Joel , Malekzadeh Farshad , White Deandra 
Published: February 2017

Abstract
In a coupled reservoir fluid flow-Geomechanics simulation, the rate of change in the pore compressibility can be orders of magnitude different from pressure diffusion rate. The significant contrast between characteristic times of the two physical processes presents opportunities to optimize the amount of coupling required during the time evolution of the simulation via asynchronous (aka loose) coupling.
Examination of the governing equations for flow in a deformable porous medium reveals that the variation of the Lagrangian porosity (δφ) depends implicitly on the variation in pore pressure (δp) and also on the variation of the bulk strain (δε). However, the pore compressibility used in reservoir simulation supposes that (δφ) is a function of (δp) only. To accomplish this, past studies have employed chain-ruling where ∂ε/∂p is substituted to find an expression for (δφ) that is a function of (δp) only. In most cases, ∂ε/∂p is not known analytically and must be derived numerically using changes in strain and pressure seen at previous coupling stages during the time evolution of the simulation. Because of the reliance on previous history, the determination of when to take the next coupling step is usually based on an arbitrary condition like requiring a fixed number of time steps to occur in the flow simulation between coupling steps.
When a coupling step occurs, a posteriori error estimate of the pore volume change is made. The simulation continues if the error is sufficiently small. If the error is large, the simulation reverts to the state at the previously coupling step and a smaller time interval elapses before the next step is taken. Obviously, reverting to a previous step is inefficient and should be avoided. Given that the error is governed by how closely the numerical determination of ∂ε/∂p is to its actual value over the time period considered and that the actual value of ∂ε/∂p depends on the heterogeneity in the subsurface as well as the rate of hydrocarbon production, a physically based coupling criterion is required for maximal efficiency.
Here, results are shown from simulations where the error in ∂ε/∂p is estimated a priori based on the rate of change of pressure. This information is then used to estimate when a significant error in porosity has accumulated which triggers a coupling step. Additionally, in each coupled time step, the actual error is calculated and use of this information results in an automated coupling method that is self-corrective and unconditionally stable. This scheme also exhibits a significant performance gain compared to other common schemes utilizing arbitrary or time based conditions for coupling when accuracy is taken into consideration.
Influence of Foam on the Stability Characteristics of Immiscible Flow in Porous Media
Authors: van der Meer J. M. , Farajzadeh R. , Jansen J. D. 
Published: February 2017

Abstract
Accurate field-scale simulations of foam enhanced oil recovery are challenging, due to the sharp transition between gas and foam. Hence, unpredictable numerical and physical behavior is often observed, casting doubt on the validity of the simulation results. In this paper a thorough stability analysis of the foam model is presented, to validate the simulation results and lay a foundation for a tailor-made solver, which can both handle large-scale reservoir simulations and accurately resolve front instabilities. We study the effect of a strongly non-monotonous total mobility function arising from foam models on the stability characteristics of the flow. To this end, we generalize the linear stability analysis of Riaz and Tchelepi (2004–2007) to nearly discontinuous relative permeability functions, and compare the results with those of highly accurate numerical simulations. In addition, we present a qualitative analysis for the effect of different reservoir and fluid properties on the foam fingering behavior. In particular, we consider the effect of heterogeneity of the reservoir, injection rates, and foam quality. Relative permeability functions play an important role in the onset of fingering behavior of the injected fluid (Riaz and Tchelepi, 2006a). Hence, we can deduce that stability properties are highly dependent on the nonlinearity of the foam transition. The foam-water interface is governed by a very small total mobility ratio, implying a stable front. The transition between gas and foam, however, exhibits a huge total mobility ratio, leading to instabilities in the form of viscous fingering. This implies that there is an unstable pattern behind the front. An indication of this behavior was shown in (Farajzadeh et al., 2016) for a similar foam model, but the authors did not provide a satisfying explanation for the cause of these instabilities. Here we closely study the influence of the foam on instabilities at and behind the front, and are able to predict the flow stability for different foam qualities. We deduce that instabilities are indeed able to grow behind the front, but are later absorbed by the expanding wave. The stability analysis, validated by numerical simulations, provides valuable insights about the important scales and wavelengths of the foam model. In this way we remove any ambiguity regarding the effect of grid resolution on the convergence of the solutions. This makes it possible to design a suitable computational solver that captures all the appropriate scales, while retaining computational efficiency.
Inexact Hierarchical Scale Separation: An Efficient Linear Solver for Discontinuous Galerkin Discretizations
Authors: Thiele Christopher , Araya-Polo Mauricio , Alpak Faruk O. , Riviere Beatrice , Frank Florian 
Published: February 2017

Abstract
Hierarchical scale separation (HSS) is a new approach to solve large sparse systems of linear equations arising from discontinuous Galerkin (DG) discretizations. We investigate its applicability to systems stemming from the nonsymmetric interior penalty DG discretization of the Cahn-Hilliard equation, discuss its hybrid parallel implementation for large-scale simulations, and compare its performance to a widely used iterative solver. The solution of the linear systems, in particular in massively parallel applications, is a known performance bottleneck in direct numerical approaches.
HSS splits the linear system into a coarse-scale system of reduced size corresponding to the local mean values of the DG solution, and a set of decoupled local fine-scale systems corresponding to the higher order components of the DG solution. The scheme then alternates between coarse-scale and fine-scale system solves until both components converge, employing a standard iterative solver for the coarse-scale system and direct solves for the set of small fine-scale systems, which allow for an optimal parallelization. The motivation of HSS is to increase parallelism by decoupling the linear systems, therefore reducing the communication overhead within sparse matrix-vector multiplications of classical iterative solvers. Providing some mild assumptions on the underlying DG basis functions, the above-mentioned splitting can be done on the resulting linear systems (i. e. without knowledge of the numerical scheme), which further motivates the development of the HSS scheme as a blackbox solver for DG discretizations.
We propose a modified HSS algorithm ("inexact HSS," IHSS") that shifts computation to the highly parallel fine-scale solver, and thus reduces global synchronization. The key result is that the IHSS scheme significantly speeds up the linear system solves and outperforms a standard GMRES solver (up to 9x speedup for some configurations). A hybrid parallel IHSS solver has been implemented using the Trilinos package. Its convergence for linear systems from the Cahn-Hilliard problem is verified, and its performance is compared to a standard iterative solver from the same package. In the future, IHSS may possibly be used as a blackbox solver to speed up DG based simulations, e.g., of reservoir flow or multicomponent transport.
Well Trajectory Optimization Constrained to Structural Uncertainties
Authors: Hanea R. G. , Casanova P. , Wilschut F. Hustoft , Fonseca R. M. 
Published: February 2017

Abstract
A key objective in any reservoir development plan is to achieve maximum reservoir exploitation which is usually quantified using an economic objective such as net present value (NPV). A key element of such an optimized development plan is an optimized well planning scheme (number, placement and trajectories of the wells). In the well planning phase, it is important to quantify the geological uncertainty. In this study, a new approach is presented in which the targets and thereby the trajectories of the wells are optimized while the geological uncertainties are taken into account. The latter is achieved by using an ensemble of updated reservoir models resulting from assisted history matching (AHM) as the input for the optimization of the field development plan. For the case presented in this study, the reservoir structure, more specific the top and bottom of the reservoir, is assumed to be the main source of uncertainty. To optimize the well targets and trajectories, the Stochastic Simplex Approximate Gradients (StoSAG) methodology is used. A parameterization of the well path is proposed, in which the angles, azimuths and measured depths of the targets are used as controls to optimize the trajectories of the horizontal wells. With this parameterization, the horizontal section is not always straight, in contrast to the approaches presented in many previous publications. The proposed workflow has been applied successfully on a realistic synthetic case inspired from a real field case. The results show that significant increases in objective function can be achieved when well trajectories are optimized constrained to uncertainties in the structural model.