bluuebunny/crossref_metadata_2025_split huggingface dataset:
Evaluation of Reservoir and Production System Integration in Production Strategy Selection
Authors: von Hohendorff Filho João Carlos , José Schiozer Denis 
Published: February 2017

Abstract
In offshore petroleum field studies, the integration between reservoir and production system simulators may improve production forecasts. Therefore, it is important to check if this integration is necessary and a methodology to do it adequately. In this work, we analyzed the influence of this integration in the development of a petroleum field focusing on the effects on the production strategy parameters for a benchmark model based on an offshore field in Brazil.
The methodology is based on a 12-step procedure for closed loop reservoir development and management. The production facilities are integrated with the reservoir in Step 11 and we propose to re-optimize the production strategy using information about pressure gradients inside the satellite well pipes for production forecast, while evaluating net present value as the objective-function. We adapted an assisted optimization workflow to include the optimization of new variables such as, pipe diameters of production system, platform position and artificial lift application, and compared this with the production strategy obtained from the same benchmark in a nonintegrated approach.
Comparing nonintegrated and integrated production strategies, we observed changes that indicate the need to integrate reservoir and production systems in the decision making process. (1) Platform position was more affected by economic indicators than production loss due to pressure drop in flowlines. (2) Economic return and field oil recovery were significantly affected by the diameters of the production pipes. Artificial lift application with high gas injection rates enhanced well performance. (3) A re-optimization of the number of wells had little effect on the cumulative oil production but larger influence on net present value, indicating potentially unnecessary wells in a nonintegrated project. (4) The integration demanded further optimization of well placement, significantly impacting both net present value and the recovery factor.
The integrating production facilities with the reservoir, generated a significant increase in the net present value, maintained the same oil recovery factor and required less investment.
Multiscale Gradient Computation for Multiphase Flow in Porous Media
Authors: Moraes R. , Rodrigues J. R. , Hajibeygi H. , Jansen J. D. 
Published: February 2017

Abstract
A multiscale gradient computation method for multiphase flow in heterogeneous porous media is developed. The method constructs multiscale primal and dual coarse grids, imposed on the given fine-scale computational grid. Local multiscale basis functions are computed on (dual-) coarse blocks, constructing an accurate map (prolongation operator) between coarse- and fine-scale systems. While the expensive operations involved in computing the gradients are performed at the coarse scale, sensitivities with respect to uncertain parameters (e.g., grid block permeabilities) are expressed in the fine scale via the partial derivatives of the prolongation operator. Hence, the method allows for updating of the geological model, rather than the dynamic model only, avoiding upscaling and the inevitable loss of information. The formulation and implementation are based on automatic differentiation (AD), allowing for convenient extensions to complex physics. An IMPES coupling strategy for flow and transport is followed, in the forward simulation. The flow equation is computed using a multiscale finite volume (MSFV) formulation and the transport equation is computed at the fine scale, after reconstruction of mass conservative velocity field. To assess the performance of the method, a synthetic multiphase flow test case is considered. The multiscale gradients are compared against those obtained from a fine-scale reference strategy. Apart from its computational efficiency, the benefits of the method include flexibility to accommodate variables expressed at different scales, specially in multiscale data assimilation and reservoir management studies.
A Framework for Mechanistic Modeling of Alkali-Surfactant-Polymer Process in an Equation-of-State Compositional Simulator
Authors: Nghiem L. , Skoreyko F. , Gorucu S. E. , Dang C. , Shrivastava V. 
Published: February 2017

Abstract
Alkaline/Surfactant/Polymer (ASP) is an important chemical EOR process that involves the generation of in-situ soap through the reaction of the acid component in the oil with the alkali, in conjunction with intra-aqueous reactions, mineral dissolution and precipitation, micro-emulsion behavior and salinity gradient. The mechanistic simulation of ASP is very complex and has been carried out with specialized chemical flood simulators. Current trends in EOR processes show an interest in hybrid methods where chemical flooding is combined with other EOR methods such as low salinity waterflood, foam and gas/CO2 injection. Thus, it is beneficial to develop such capabilities in an Equation-of-State (EOS) compositional simulator for screening and combining different EOR processes.
This paper presents a framework for mechanistic modeling of the ASP process within an EOS compositional simulator. A new approach for modeling the Winsor Type I, II and III micro-emulsion phase behavior is introduced based on laboratory solubility data. In the Type III system, the emulsion is distributed judiciously between the oil and water phase without the introduction of a third liquid phase. The optimal salinity variation with the soap/(soap + synthetic surfactant) mole fraction is modeled. This feature allows the design of salinity gradient, an essential requirement for a successful ASP flood. The above physics are coupled with comprehensive geochemistry calculations (intra-aqueous reactions and mineral precipitation/dissolution reactions) and three-phase oil/gas/water flash calculations with an equation of state and Henry's law. The whole system of associated equations is solved simultaneously with the flow and energy equations using Newton's method, making the simulator one of the most robust and comprehensive simulators for EOR methods.
The simulator is validated with ASP core flood experiments. The optimization of the ASP process for a typical field is illustrated and discussed with regard to alkali, synthetic surfactant and polymer injection with decreasing salinity.
On the Convergence of System-AMG in Reservoir Simulation
Authors: Gries Sebastian 
Published: February 2017

Abstract
System-AMG provides a flexible framework for linear systems in simulation applications that involve various different types of physical unknowns. Reservoir simulation applications, with their driving elliptic pressure unknown, are principally well-suited to exploit System-AMG as a robust and efficient solver method.
However, in order to be efficient and robust, the coarse grid correction process of AMG on the one hand needs to be possible, i.e., the matrix needs to fulfill certain requirements. It has been demonstrated earlier how to ensure this by the dynamic rowsumming (DRS) method.
On the other hand, the coarse grid correction must be physically meaningful in order to speed up the overall convergence. It has been common practice in CPR-type applications to use an approximate pressure-saturation decoupling to fulfill this requirement. This, however, can have drastic impacts on AMG’s applicability and, thus, is not performed by the DRS-method.
In this work, we are going to see that the pressure-saturation decoupling indeed is not necessary for ensuring an efficient interplay between the coarse grid correction process and the fine-level problem. We will find that a comparable influence of the pressure on the different involved PDEs is much more crucial.
As an extreme case w.r.t. the outlined requirement, we will discuss linear systems from compositional simulations under the volume balance formulation. In these systems, the pressure typically is associated with a volume-balance, rather than a diffusion process. The corresponding coarse grid correction does, hence, not provide any benefit regarding the overall convergence: the other PDEs involve pressure-based diffusive parts that have a drastically different structure than the volume-balance has. We will see how System-AMG can still be used in such cases.
A Parallel Solution for Large Surface Networks in a Fully Integrated Reservoir Simulator
Authors: Fleming Graham , Wang Qinghua 
Published: February 2017

Abstract
Integrated modeling of surface and subsurface is necessary to ensure physical accuracy in reservoir simulation with complex wells and surface facilities. In this fully implicit coupled approach, two physical domains, reservoir and surface network, are assembled into a single global system and solved simultaneously. However, flows in these two domains behave very differently. The surface network, comprised of wells and surface facilities, usually requires many more Newton iterations than the reservoir domain; therefore, the global Newton iteration begins with a standalone network solution as a preconditioner, followed by a global linear system solution. For large surface networks, the computational effort necessary to solve the surface network equations can be significant. Parallelization of the reservoir domain is a well-studied topic, but little consideration has been given to parallel solutions for integrated models with large facilities. In this paper, an approach to parallelization of the surface network is presented.
The network solution is involved in two stages, the linear global solution and the nonlinear standalone preconditioning. In the global solution stage, a multiplicative Schwarz method is chosen to solve the global linear system, and a parallel sparse direct solver is applied to solve the surface network matrix. Before the global linear solution, the coefficient matrix for the surface network is reduced to a Schur complement with connection-based variables eliminated, including total flow rate on network connections and component flow rates on perforation connections. This elimination is also performed in parallel. The parallelization of the nonlinear solution of the surface network in the preconditioning stage is more challenging. Similar to the reservoir domain, a domain decomposition method with a bottom-up approach is used to partition the surface network to substructures. Fortunately, the surface network often has a sparse tree structure. Most of the network computations, constraint setting, targeting, pressure, volume, temperature (PVT), and hydraulic calculations can be parallelized readily with a message passing interface (MPI); however, load imbalance can be a problem because the network structure changes over time, and the cost of the nonlinear solutions involved in each substructure can vary dramatically.
This paper demonstrates the performance of the network parallelization for a compositional model with a large surface network. The scalability of the standalone network solution, the linear global solution, and the full system are presented and compared to a serial approach for the network.
To achieve a reasonable scalability in reservoir models with large surface facilities, new algorithms and data structures are designed to parallelize the solutions for the coupled system of reservoir and surface network.
Flow Diagnostics on Fully Unstructured Grids
Authors: Zhang Zhao , Geiger Sebastian , Rood Margaret , Jacquemyn Carl , Jackson Matthew , Hampson Gary , Carvalho Felipe Moura , Silva Clarissa Coda , Silva Julio Machado , Sousa Mario Costa 
Published: February 2017

Abstract
Flow-diagnostics are a common way to rank and cluster ensembles of reservoir models based on their approximate dynamic behaviour prior to commencing full-physics reservoir simulation. Traditionally, flow diagnostics are carried out on corner-point grids inherent to geocellular models.
The novel "Rapid Reservoir Modelling" (RRM) concept enables fast and intuitive prototyping and updating of reservoir models. In RRM, complex reservoir heterogeneities are modelled as discrete volumes bounded by surfaces that can be modified using simple sketching operations in real time. The resulting reservoir models are discretized using fully unstructured 3D meshes where the grid conforms to the reservoir geometry.
This paper presents a new and computationally efficient numerical scheme that enables flow diagnostic calculations on fully unstructured grids. Time-of-flight and steady-state tracer distributions are computed directly on the grid. The results of these computations allows us to estimate swept reservoir volumes, injector-producer pairs, well-allocation factors, flow capacity, storage capacity and dynamic Lorenz coefficients which all help approximate the dynamic reservoir behaviour.
We use the Control Volume Finite Element Method (CVFEM) to solve the elliptic pressure equation. A scalable matrix solver (SAMG) is used to invert the linear system. A new edge-based CVFEM is developed to solve hyperbolic transport equations for time-of-flight and tracer distributions. An optimal reordering technique is employed to deal with each control volume locally such that the hyperbolic equations can be computed in an efficient node-by-node manner. This reordering algorithm scales linearly with the number of unknowns.
The total CPU time, including grid generation and flow diagnostics, is typically below 3 seconds for grids with 50k unknowns. Such fast calculations provide, for the first time, real-time feedback on changes in the dynamic reservoir behaviour while the reservoir model is updated.
Numerical Modeling of Unstable Water Floods and Tertiary Polymer Floods into Highly Viscous Oils
Authors: Loubens R. de , Vaillant G. , Regaieg M. , Yang J. , Moncorgé A. , Fabbri C. , Darche G. 
Published: February 2017

Abstract
The saturation distribution after unstable water flooding into highly viscous oil may have a decisive impact on the efficiency of tertiary polymer flooding, in particular due to hysteresis effects associated with oil banking. In this work, we model water flood and tertiary polymer flood experiments performed on Bentheimer sandstone slabs with heavy oils of about 2000 cP and 7000 cP, and compare the numerical results with experimental production, pressure and X-ray data.
The unstable water floods are initially simulated in 2D with our parallel in-house research reservoir simulator using a high-resolution discretization. In agreement with existing literature, we find that Darcy-type simulations based on steady-state relative permeabilities - inferred here from a 3D quasistatic pore network model (PNM) - cannot predict the measured water flood data. Even qualitatively, the viscous fingering patterns are not reproduced. An adaptive dynamic pore network model is then applied on a 2D pore network constructed from the statistics of the 3D network. If the fingering patterns simulated with this 2D PNM are qualitatively in good agreement with the experimental data, a quantitative match cannot be obtained due to the limitations of 2D modeling. Although 3D dynamic PNM at the slab scale would currently lead to prohibitively high computational cost, it has the potential to address the deficiencies of continuum models at highly unfavorable viscosity ratio.
For the tertiary polymer floods characterized by a much more favorable mobility ratio, Darcy-type modeling is applied and history matching is conducted from the end of the water floods. We find that unless hysteresis due to oil banking is accounted for in the relative permeability model, it is not possible to reconcile the experimental data sets. This hysteresis phenomenon, associated with oil invasion into previously established water channels, explains the rapid propagation of the oil bank. For the considered experiments, a simultaneous history match of good quality is obtained with the production and pressure data, and the simulated 2D saturation maps are in reasonable agreement with X-ray data.
This paper addresses the challenges in modeling highly unstable water flooding, using both a conventional Darcy-type simulator and adaptive dynamic PNM, by confronting the simulated results with experimental data including saturation maps. It also highlights the important role of relative permeability hysteresis in the tertiary recovery of viscous oils by polymer injection.
An Improved Slack Variable Method to Determine Active Constraints in Large Surface Networks
Authors: Wang Qinghua , Fleming Graham 
Published: February 2017

Abstract
In a fully integrated reservoir model consisting of one or more reservoirs and a surface network of complex wells and facilities, determining the active constraints in the network, while ensuring that the network equations are nonsingular, is a challenge. This paper introduces an improved slack variable method to address this difficulty.
The high solution cost of the matrix equations associated with the slack variable method makes it inefficient for simulation of reservoirs with a large surface network. After elimination of the nonslack variables, the resultant Schur complement is often a dense matrix and loses the typical sparse tree structure of the original network Jacobian, which makes it costly to solve. This paper revisits the slack variable method and designs two approaches to address the solution cost. The first approach, the pseudo slacks, conserves the sparse pattern of the surface network by introducing several pseudo variables that are added to the slack matrix; it works best for cases with targeting or constraints for a large group of wells. The second approach, minimal slacks, uses a simple heuristic technique to remove slack variables unless they are required to ensure the equations are nonsingular. This method reduces the slack matrix dimension but can increase the number of iterations required to solve the network.
Numerical experiments show significant performance improvements compared to the previous slack variable method in reservoir models with large surface networks.
Joint Optimization of Economic Project Life and Well Controls
Authors: Shirangi Mehrdad G. , Volkov Oleg , Durlofsky Louis J. 
Published: February 2017

Abstract
A new methodology for the joint optimization of economic project life and time-varying well controls is introduced. The procedure enables the maximization of net present value (NPV) subject to satisfaction of a specified modified internal rate of return. Use of this framework allows an operator to avoid situations where NPV continues to increase in time, but the late-time cash flows are negligible (in terms of an appropriate financial metric) relative to the capital invested in the project. The optimization is formulated as a nested procedure in which economic project life is optimized in the outer loop, and the associated well settings (time-varying bottomhole pressures in the cases considered) are optimized in the inner loop. The inner-loop optimization is accomplished by use of an adjointgradient-based approach, while the outer-loop optimization entails an interpolation technique. We demonstrate the successful application of this framework for production optimization for two-and three-dimensional reservoir models under waterflood. The tradeoff between maximized NPV and rate of return is assessed, as is the impact of discount rate on optimal operations. We believe this to be the first production optimization formulation that explicitly incorporates both NPV and rate of return. As such, this approach may represent an alternative to existing treatments that entail the bi-objective optimization of long-and short-term NPV.
A Double Control Volume Finite Element Method with Dynamic Unstructured Mesh Optimization
Authors: Salinas P.. , Pavlidis D.. , Xie Z.. , Pain C. C. , Jackson M. D. 
Published: February 2017

Abstract
A novel high-order, Double Control Volume Finite Element Method in which pressure is discretized using finite volumes is presented to model multiphase flow porous media simulations. This approach shows a better behavior to calculate the pressure field than the well-known Control Volume Finite Element Method. The latter, as many other formulations, have problems to calculate the pressure field when the elements conforming the mesh, triangles (2D) or tetrahedra (3D), have very obtuse angles. This limits the advantages that can be obtained by using dynamic adaptive meshing methods, as the meshes are constrained to have good quality elements rather than just optimizing the elements to adapt to the peculiarities of the flow. This paper presents a novel formulation that shows to be more resilient with regard to elements with very obtuse angles, enabling dynamic mesh adaptivity to be more effective.
Interactions Between Viscous Fingering and Channeling for Unstable Water/Polymer Floods in Heavy Oil Reservoirs
Authors: Luo Haishan , Delshad Mojdeh , Pope Gary A. , Mohanty Kishore K. 
Published: February 2017

Abstract
Unstable floods and resulting viscous fingers remain a big challenge for reservoir simulation as the gridblock size is usually many orders larger than the viscous finger wavelength. This problem becomes especially pronounced with increasing applications of polymer and other chemical floods in the development of heavy oil reservoirs. Traditional reservoir simulators do not consider sub-grid viscous fingering effects and tend to overestimate the waterflood oil recovery. Using extremely fine grid models with centimeters size is unrealistic for field-scale simulations.
While some researchers disregard viscous fingering by claiming that channeling dominates at the large scale for heterogeneous reservoirs, they miss the existence of viscous fingering at the small scale, which affects the displacement efficiency. To overcome this limitation, an effective-fingering model was developed to upscale fingering effects. The model divides each gridblock into three dynamic regions: two-phase flow, single phase oil flow, and bypassed-oil regions. Model parameters represent the maximum fraction of viscous fingering and the growth rates of different regions, which are used to modify flow functions. Model parameters from history match of a set of laboratory experiments show clear power-law correlations with a dimensionless viscous finger number, a function of viscosity ratio, velocity, permeability, interfacial tension, and core cross-sectional area.
The correlation was achieved in the lab scale by considering homogeneous cores, and we extended it further to the field scale by performing high-order spatial accuracy numerical simulations at the intermediate scale using fine gridblock sizes roughly the same as that of the core. Geostatistical realizations of the permeability field were generated with various variances and correlation lengths. In a statistical way, we were able to quantify the viscous finger number valid for a gridblock at the field scale affected by various heterogeneities using the effective-fingering model. We also observed that channelized permeability distributions increase the viscous finger number drastically, showing the important role of channeling in such cases. This new model was applied to a field case with high heterogeneity undergoing water/polymer floods. We observed that the oil recovery was improved by the polymer slug because of the enhancement in both local displacement efficiency and sweep efficiency.
In summary, we developed an upscaling model that provides a fresh-new insight on how to simulate unstable water/polymer floods at the field scale, which effectively accounts for the interplay of viscous fingering and channeling.