bluuebunny/crossref_metadata_2025_split huggingface dataset:
Profile Changes and Self-sputtering during Low Energy Ion Implantation.
Authors: Vandervorst W. , Janssens T. , Brijs B. , Lindsay R. , Collart E. J. H. , Kirkwood David A. , Mathot G. , Terwagne G. 
Published: February 2013

AbstractContinued device scaling requires the formation of ever-shallower junctions with low resistance. A desirable option to form these junctions is still the use of conventional ion implantation. However in order to meet the junction depth/sheet resistance goals, a strong reduction in implant energy and increase in implant dose is required. Earlier work for B and BF2-implants, has suggested that during low energy ion implantation self-sputtering may become an important factor influencing/limiting the retained dose. The basic mechanism for the selfsputtering with increasing dose is the increasing dopant concentration at the surface leading to an increased probability for re-emission by the sputtering process. Simple models describing ion retention in combination with sputtering are based on this concept and indeed predict a selfsputtering process limiting the final retained dose. Unfortunately the theoretical calculations only predict a significant sputtering at doses >51016 at/cm2 whereas experimental results already show a limit in retained dose at 5 1015at/cm2.In order to confirm the experimental data, low energy B, BF2, As and Sb implants have been made. Dose retention was monitored using nuclear reaction analysis and RBS whereby details of the dopant profile (redistribution) were studied using high resolution SIMS. For As and Sb no self-sputtering up to a dose of 1 1016at/cm2 can be found. For B a small dose loss (<10%) is seen significantly below the literature data. For BF2 a 20 % dose loss is observed. None of the SIMS profiles provide sufficient evidence for enhanced B-surface migration as required to explain the enhanced self-sputtering. On the other hand such a surface migration is reminiscent of the observations in SIMS whereby also an enhanced mobility of B during ion irradiation is required to explain the anomalous B-surface peak in many SIMS profiles. Based on the SIMS profiles a component sputter yield for B can be derived which is significantly higher than the matrix sputter yield suggesting a weak bonding of the segregated species leading to a reduced surface binding energy and thus enhanced sputtering yield.
Use of Multi-Objective Algorithms in History Matching of a Real Field
Authors: Christie Mike , Eydinov Dmitry , Demyanov Vasily , Talbot Jack , Arnold Dan , Shelkov Vassili 
Published: February 2013

Abstract
Conventionally, automated history matching methods operated on a single number (the misfit or match quality) which is obtained by summing the least square misfits for all the quantities of interest in a history match. Multi-objective history matching allows the algorithm to be guided by (usually groups of) match quality components, with the overall history match probability determined by summing the components at the end. This feature encourages diversity in the history match, as the algorithm can trade off matches in one area against good fits elsewhere, and has also been shown to speed up history matching in some cases.
This paper describes a comparison of single and multi-objective history matching of a medium-sized field in Western Siberia with nearly 100 wells and over 10 years of history. We compared the performance of both single and multi objective versions of Particle Swarm Optimization. We also assess the effectiveness of various different choices of history match parameters chosen based on reservoir engineering knowledge. Using these techniques, we are able to obtain a high-quality group level match with a relatively low number of simulation runs.
The paper also describes trade-offs between the parallelism of the history matching process and that of the simulator on a 12 core windows workstation. This is an important trade-off as the extreme choices of using of all the cores by the simulator or limiting each simulation to a single core and using each core for a separate history matching run may not be optimal.
Solver Preconditioning Using the Combinatorial Multilevel Method
Authors: Wang Yuhe , Killough John E. 
Published: February 2013

Abstract
The purpose of this paper is to report the first preliminary study of the recently introduced Combinatorial Multilevel (CML) method for solver preconditioning in large-scale reservoir simulation with coupled geomechanics. The CML method is a variant of the popular Algebraic Multigrid (AMG) method yet with essential differences. The basic idea of this new approach is to construct a hierarchy of matrices by viewing the underlying matrix as a graph and by using the discrete geometry of the graph such as graph separators and expansion. In this way, the CML method combines the merits of both geometric and algebraic multigrid methods. The resulting hybrid approach not only provides a simpler and faster set-up phase compared to AMG, but the method can be proved to exhibit strong convergence guarantees for arbitrary symmetric diagonally-dominant matrices. In addition, the underlying theoretical soundness of the CML method contrasts to the heuristic AMG approach, which often can show slow convergence for difficult problems.
This new approach is implemented in a reservoir simulator for both pressure and displacement preconditioners in the multi-stage preconditioning technique. We present results based on several known benchmark problems and provide a comparison of performance and complexity with the widespread preconditioning schemes used in large-scale reservoir simulation. An adaptation of CML for unsymmetric matrices is shown to exhibit excellent convergence properties for realistic cases.
Automatic Well Control and Decision Support in a massive parallel Simulation Environment
Authors: Wiegand Klaus D. , Beckner Bret L. 
Published: February 2013

Abstract
ExxonMobil’s proprietary reservoir simulator, EMpower, includes a programmable decision support system for manipulating well rates and wellhead pressures during simulation runs. The so-called well management component allows users to write algorithms that monitor simulation progress and steer the depletion process according to simulation objectives and constraints at well, platform, reservoir, and field levels. A built-in nonlinear optimization package can be used to determine well allocation under a set of constraints, including pressure and rate limits in the surface facility network. The strength of the system is its flexibility, which is limited only by the amount of programming a user is able and willing to do. Drawbacks of the system are its complexity, reliance on user expertise, and the requirement to write programs.
The move towards massively parallel computing platforms, such as clusters with thousands of nodes, poses a major challenge to the well management environment as we know it. Its inherently sequential programming model, which is geared towards simulation users rather than software developers, cannot take advantage of the massive parallelization that is expected to dominate simulation technology in the next decade, and could be a roadblock for parallel scalability.
In the following, we describe our efforts to adapt the system to a massive parallel simulation environment. At the heart of the transformation lies an approach that parallelizes constraint management and work-overs at the well level, and uses numerical optimization to control material balance, production, and injection for well-groups. After laying out the approach and describing the mathematical derivation of the optimization problem, we provide examples for scalability and parallel efficiency.
New Locally Conservative Numerical Schemes for Hydrogeomechanical Couplings in Strongly Heterogeneous Presalt Reservoirs
Authors: Murad Marcio A. , Luizar-Obregon J. Alexei , Lopes Tuane V. , Garcia Eduardo , Radtke Luiz Carlos , Correa Maicon R. , Borges Marcio R. , de Lima Sidarta A. 
Published: February 2013

Abstract
We construct a new numerical modeling for two-phase immiscible flow in a strongly heterogeneous deformable carbonate underneath a rock salt composed by halite and anhydrite displaying creep behavior with the viscous strain ruled by a nonlinear constitutive law of power-law type. Within the framework of the so-called iteratively coupled methods and fixed-stress split algorithm we develop mixed finite element methods for the flow and geomechanics subsystems which furnish locally conservative Darcy velocity and transient porosity input fields for the transport problem for the water saturation. Such transport equation is decomposed within an operator splitting technique based on a predictor-corrector scheme with the predictor step discretized by a higher-order non-oscillatory finite volume central scheme. Numerical simulations of a water-flooding problem in secondary oil recovery are presented for different realizations of the input random fields (permeability, Young modulus and initial porosity). Comparisons between the accuracies of the proposed approach and the traditional one-way coupled hydro-geomechanical formulation are presented. In addition, simulations including the viscoelastic behavior of the overburden rock salt are performed showing the effects of salt stiffness and irreversible deformation upon finger grow and breakthrough curves. A notable feature of the formulation proposed herein is the accurate prediction of the influence of geomechanical effects upon the unstable movement of the water front, whose evolution is dictated by carbonate heterogeneity, unfavorable viscosity ratio and geomechanical effects without deteriorating the local conservative character of the numerical schemes.
Robust Semi-Implicit Three-Dimensional Upwind Techniques for Reducing Grid Orientation Effect in Thermal Simulations
Authors: Zheng Hongwen , Buchanan Wm. Lloyd 
Published: February 2013

Abstract
In field-scale thermal reservoir simulation, grid orientation is one important factor affecting the accuracy of numerical results. Traditionally thermal reservoir simulators adopt the nine-point method to handle this issue. However, the nine-point method introduces extra bandwidth of the Jacobian Matrix which significantly increases the storage and CPU requirements. Also, that method has limitations which make it difficult to integrate with advanced gridding techniques.
A new three-dimensional upwind technique was developed to reduce grid orientation effect without the disadvantages mentioned above. This new technique adopts a semi-implicit strategy such that no extra matrix bandwidth is added. Numerical results show that the new technique successfully reduces grid orientation effect while using much less CPU than the nine-point method.
Flexible and Efficient N-Porosity, Full-Featured Simulator Design, and Application
Authors: Hinkley R. E. , Wang Q. , Wang K. , Camilleri D. , Fleming G. , Watts J. W. 
Published: February 2013

Abstract
The need for flexible and efficient multi-porosity, reservoir-simulation capabilities has never been greater. Much of the world’s oil reserves are contained in highly variable fractured reservoirs. Moreover, there is now unprecedented interest in the simulation of unconventional gas reservoirs, where up to four porosity types may be required. This paper discusses the design of an N-porosity, full-featured reservoir simulator capable of handling these diverse scenarios. Essential to the design is the programming data-structure paradigm of the SubGrid. SubGrids represent collections of simulation nodes within spatial regions of interest and encapsulate all data and variables required. Any number of associated SubGrids may coexist, representing N-porosities. Inter- and intra-SubGrid connections may be arbitrarily specified. Because the linear solver operates on the associated SubGrids as distinct entities, the design has tremendous flexibility. For example, regions with simple connectivity, such as in dual-porosity, single-permeability models, can have simple pre-solver elimination performed while other regions with uniform intra-porosity connectivity require a merged SubGrid solution. The scheme efficiently treats regions with different numbers of porosities, levels of interconnectivity, and levels of implicitness. Applications may be applied across multiple reservoirs simultaneously. Treatment of missing "fracture" zones has always been an important feature in the dual-porosity, single-permeability simulation. The traditional approach is to treat the matrix within missing fracture zones effectively as though it were an interconnected portion of the fracture porosity. This preserves connectivity within the fracture-free zones and the more computationally efficient single-permeability solver pre-elimination step. A second missing "fracture" scheme is introduced, which differs in the way that the connections between the fracture and matrix blocks are computed at the boundary of fracture-free zones. Flexible transfer-function application and porosity dependency during equilibrium initialization are discussed.
High-Performance Modeling of CO2 Sequestration by Coupling Reservoir Simulation and Molecular Dynamics
Authors: Bao Kai , Yan Mi , Lu Ligang , Allen Rebecca , Salama Amgad , Jordan Kirk E. , Sun Shuyu 
Published: February 2013

Abstract
The present work describes a parallel computational framework for CO2 sequestration simulation by coupling reservoir simulation and molecular dynamics (MD) on massively parallel HPC systems. In this framework, a parallel reservoir simulator, Reservoir Simulation Toolbox (RST), solves the flow and transport equations that describe the subsurface flow behavior, while the molecular dynamics simulations are performed to provide the required physical parameters. Numerous technologies from different fields are employed to make this novel coupled system work efficiently.
One of the major applications of the framework is the modeling of large scale CO2 sequestration for long-term storage in the subsurface geological formations, such as depleted reservoirs and deep saline aquifers, which has been proposed as one of the most attractive and practical solutions to reduce the CO2 emission problem to address the global-warming threat. To effectively solve such problems, fine grids and accurate prediction of the properties of fluid mixtures are essential for accuracy. In this work, the CO2 sequestration is presented as our first example to couple the reservoir simulation and molecular dynamics, while the framework can be extended naturally to the full multiphase multicomponent compositional flow simulation to handle more complicated physical process in the future.
Accuracy and scalability analysis are performed on an IBM BlueGene/P and on an IBM BlueGene/Q, the latest IBM supercomputer. Results show good accuracy of our MD simulations compared with published data, and good scalability are observed with the massively parallel HPC systems. The performance and capacity of the proposed framework are well demonstrated with several experiments with hundreds of millions to a billion cells.
To our best knowledge, the work represents the first attempt to couple the reservoir simulation and molecular simulation for large scale modeling. Due to the complexity of the subsurface systems, fluid thermodynamic properties over a broad range of temperature, pressure and composition under different geological conditions are required, for which the experimental results are limited. Although equations of state can reproduce the existing experimental data within certain ranges of conditions, their extrapolation out of the experimental data range is still limited. The presented framework will definitely provide better flexibility and predictability compared with conventional methods.
Investigation of the Critical Velocity Required for a Gravity Stable Surfactant Flood
Authors: Tavassoli Shayan , Lu Jun , Pope Gary A. , Sepehrnoori Kamy 
Published: February 2013

Abstract
Classical stability theory predicts the critical velocity for a miscible fluid to be stabilized by gravity forces. This theory was tested for surfactant floods with ultra-low interfacial tension and found to be optimistic compared to both laboratory displacement experiments and fine-grid simulations. The inaccurate prediction of instabilities based on available analytical models is due to the complex physics of surfactant floods. First we simulated vertical sandpack experiments to validate the numerical model. Then we performed systematic numerical simulations in two and three dimensions to predict formation of instabilities in surfactant floods and to determine the velocity required to prevent instabilities by taking advantage of buoyancy. The 3D numerical grid was refined until the numerical results converged. A third-order TVD finite-difference method was used for these simulations. We investigated the effects of dispersion, heterogeneity, oil viscosity, relative permeability, microemulsion viscosity. These results indicate that it is possible to design a very efficient surfactant flood without any mobility control if the surfactant solution is injected at a low velocity in horizontal wells at the bottom of the geological zone and the oil captured in horizontal wells at the top of the zone. This approach is practical only if the vertical permeability of the geological zone is high. These experiments and simulations have provided new insight into how a gravity stable low-tension displacement behaves and in particular the importance of the microemulsion phase and its properties, especially its viscosity. Numerical simulations show high oil recovery efficiencies on the order of 60% of water flood residual oil saturation for gravity stable surfactant floods using horizontal wells. Thus under favorable reservoir conditions, gravity stable surfactant floods are very attractive alternatives to surfactant-polymer floods. Some of the world’s largest oil reservoirs are deep, high-temperature, high-permeability, light-oil reservoirs and thus candidates for gravity stable surfactant floods.
Fully Coupled Simulation of Multiple Compositional Reservoirs with a Shared Surface Facility Network
Authors: Fleming Graham , Wong Terry 
Published: February 2013

Abstract
When multiple reservoirs are produced through a common facility network, the capability to integrate the modeling of surface and subsurface can be critical to field development and optimization. The shared facility network imposes constraints that the combined production cannot exceed, determines the pressure drop in the flow lines, and the composition and volume of the sales and reinjection streams. Pressure drop in flow lines is particularly important in deepwater field development, where flow lines are long, and production from multiple reservoirs can flow through the same riser.
The most robust method for solving the combined surface-subsurface system is to fully couple and simultaneously solve the reservoir and facility equations. However, if the reservoirs fluids are represented with compositional equation of state models, and different pseudo-components are used in some or all of the reservoirs, then the reservoir fluid must be delumped into a common set of pseudo-components in the network. In this paper, we describe a method to consistently and efficiently model such a system with a fully coupled surface-subsurface simulator. At every point in the network, where fluid from only a single reservoir is present, the phase behavior calculations can use the fluid characterization for that reservoir and exactly reproduce the result that would have been obtained if the fluid had not been delumped into the network pseudo-components. However, at any point in the network, the characterization of the common network fluid can be used. In addition, if more compositional accuracy is required, the network fluid can be further delumped into more pseudo-components, or if accuracy is not critical, the fluid can be lumped into fewer pseudo-components for more computational efficiency. Examples demonstrating the flexibility, efficiency, and consistency of the method are provided.
Reduced-Order Modeling for Compositional Simulation Using Trajectory Piecewise Linearization
Authors: He Jincong , Durlofsky Louis J. 
Published: February 2013

Abstract
Compositional simulation can be very demanding computationally as a result of the potentially large number of system unknowns and the intrinsic nonlinearity of typical problems. In this work, we develop a reduced-order mod- eling procedure for compositional simulation. The technique combines trajectory piecewise linearization (TPWL) and proper orthogonal decomposition (POD) to provide a highly efficient surrogate model. The compositional POD-TPWL method represents new solutions in terms of linearizations around states generated (and saved) during previously simulated ‘training’ runs. High-dimensional states are projected (optimally) into a low-dimensional subspace using POD. The compositional POD-TPWL model is based on a molar formulation that uses pressure and overall component mole fractions as the primary unknowns. Several new features, including the use of a Petrov-Galerkin projection to reduce the number of equations (rather than the commonly used Galerkin projection), and a new procedure for determining which saved state to use for linearization, are incorporated into the method. Results are presented for heterogeneous three-dimensional reservoir models containing oil and gas phases with up to four hydrocarbon components. Reasonably close agreement between full-order reference solutions and compositional POD-TPWL simulations is demonstrated for the cases considered. Construction of the POD-TPWL model requires preprocessing overhead computations equivalent to about three full-order runs. Runtime speedups using POD-TPWL are, however, very significant – about a factor of 500 for the cases considered. The POD-TPWL model thus appears to be well suited for use in applications such as production optimization or uncertainty assessment, in which many simulations must be performed.