bluuebunny/crossref_metadata_2025_split huggingface dataset:
Ideologi Gerakan Politik Islam Di Indonesia
Authors: Basyir Kunawi 
Published: February 2017

Seiring dengan perkembangan dan perubahan setting sosial politik pasca Orde Baru (Orba) tanpa diduga memberikan ruang bagi berkembangnya wacana pro dan kontra masalah demokrasi di Indonesia. Tiap-tiap kelompok mengajukan argumentasi untuk mengukuhkan pendirian mereka, sayang argumentasi yang dibangun tidak lagi ditujukan untuk berusaha meyakinkan wacana tersebut akan tetapi melakukan stigmatisasi satu sama lain. Kiranya perdebatan (diskursus) wacana tentang politik Islam yaitu “hubungan antara Islam dan Negara” menjadi pemicu adanya pro dan kontra terhadap pemberlakukan demokrasi di Indonesia,. Tema tersebut menjadi tema perdebatan yang belum terselesaikan. Perbedaan yang mendasar di kalangan internal yang diikuti oleh sikap antagonistik sejumlah kelompok Islam yang secara aksiomatik menolak dan menerima gagasan demokrasi di Indonesia ini saling beradu konsep dan gerakan dengan mengusung isu yang berbeda. Bagi kelompok fundementalis mengusung isu khilafah dan atau syariat Islam sedang kelopok Islam modernis mengusung isu demokrasi sebagi jargon idiologi gerakan politiknya. Dengan demikian Indonesia menjadi sebuah tontonan yang menarik bagi kalangan akademisi untuk mengkajinya.
Acompañamiento a emprendedores en la Universidad EAN: del modelo IN3 a EAN Impacta (2011-2016)
Authors: Orozco Triana Jairo Alonso , Parra Bernal León Darío , Ruíz Arias Catalina Lucía , Matíz Bulla Francisco Javier 
Published: February 2017

Rev.esc.adm.neg
Desde su fundación, la Universidad EAN es pionera en ofrecer educación enfocada a fortalecer competencias emprendedoras, por este motivo es siempre un desafío diseñar programas enfocados a potenciar emprendedores. Este artículo enmarca el acompañamiento emprendedor dentro de unas tendencias globales y necesarias en del ecosistema colombiano, tales como: el pensamiento en diseño aplicado en los negocios, el emprendimiento ágil, los programas de aceleración y la innovación a partir de la investigación, los cuales se han convertido en buenas prácticas para la incubación de empresas desde las universidades (Bhatli, 2014). A partir de lo anterior, se analiza la evolución, procesos y resultados de los programas de acompañamiento desarrollados en la Universidad EAN: Modelo IN3 (Incuba-Innova-Integra), el Punto de Atención al Emprendedor (PAE) y su Fondo de Capital Semilla, y finalmente el programa actual llamado EAN Impacta.
Influencia de las prácticas de gobierno corporativo y gestión en la percepción de la unidad y armonía en empresas familiares
Authors: Gómez Betancourt Gonzalo Eduardo , Betancourt Ramírez José Bernardo , Lagos Cortés Diógenes , Aparicio Castillo Ricardo 
Published: February 2017

Rev.esc.adm.neg
El presente artículo hace parte del resultado de la investigación «Ética, Responsabilidad Social y Desarrollo», a partir de una revisión de literatura y de la experiencia previa de los autores se identificaron 47 prácticas de gobierno y gestión que pueden incidir en la percepción de unidad y armonía. En una muestra de empresas mexicanas y colombianas se aplicó un análisis de regresión logística donde se encontró que buscar consejo para gestionar el patrimonio, formación continua de líderes, tener accionistas formados, tener estrategia familiar, realizar asambleas de accionistas anualmente y reuniones adicionales de propietarios son las prácticas que mayor influencia tienen en la percepción de Unidad y Armonía en la empresa familiar.
Compositional Three-Phase Relative Permeability and Capillary Pressure Models Using Gibbs Free Energy
Authors: Neshat Sajjad S. , Pope Gary A. 
Published: February 2017

Abstract
This paper presents new coupled three-phase relative permeability and capillary pressures models for implementation in a four-phase flow compositional EOS simulator. Identification of hydrocarbon and aqueous phases based on their molar Gibbs free energy is a key feature of the new model. Instead of using phase labels (gas/oil/solvent/aqueous) to define parameters such as relative permeability endpoints, residual saturations and exponents, the parameters are continuously interpolated between reference values using the Gibbs free energy of each phase at each time step. Models independent of phase label have many advantages in terms of both numerical stability and physical consistency. The models integrate and unify relevant physical parameters including trapping number and hysteresis into one rigorous algorithm for application in numerical reservoir simulators. The robustness of the new models is demonstrated with simulations of miscible WAG and solvent stimulation to remove condensate and/or water blocks in both conventional and unconventional formations.
Assessment of Chemical Performance Uncertainty in Chemical EOR Simulations
Authors: Adepoju Olaoluwa O , Hussein Hoteit , Chawathe Adwait 
Published: February 2017

Abstract
Chemical floods such as surfactant and/or polymer floods are enhanced oil recovery techniques that have been proven at both laboratory and field scale to increase sweep and/or displacement efficiency. Even though the compatibility and the efficiency of the injected chemicals are thoroughly tested and validated in the laboratory, uncertainty still remains regarding their actual performance in the reservoir. These uncertainties can result from the differences in the scale of investigation (core scale to field scale), lack of understanding of reservoir heterogeneity and connectivity, and the long term chemical performance and the chemical slug integrity in the reservoir.
In order to properly design a chemical flood, the uncertainties related to chemical performance have to be considered along with subsurface uncertainties during formal analysis using Design of Experiments. In addition to traditional subsurface uncertainty analysis, this work focused on two methodologies to systematically incorporate in-situ chemical performance uncertainties. The first methodology varies chemical properties such as polymer rheology, adsorption, permeability reduction, inaccessible pore volume and non-Newtonian behavior individually during uncertainty analysis. The drawbacks of this approach are the computationally cumbersome parameter combinations and an increased possibility of testing unphysical combinations of chemical parameters.
The second methodology considers the overall chemical performance in the reservoir as an uncertainty parameter. In this case, the chemical properties are not varied individually but as a set to express the uncertainty range of chemical quality. The advantage of using chemical performance as an uncertainty parameter is that the possibility of testing unphysical combination of chemical properties is eliminated and there are less uncertainty parameters (thus increased computational efficiency). The drawback of this approach is that inadvertent bias can be introduced in the uncertainty analysis because of limited knowledge of the subsurface, and extreme end-points in the uncertainty space may remain untested.
The two approaches are compared in this paper and case studies were conducted. The results show how realistic low, mid and high performance models were generated that account for both subsurface and chemical uncertainties.
CO2 Water-Alternating-Gas Flooding Optimization of the Chigwell Viking I Pool in the Western Canadian Sedimentary Basin
Authors: Hewson C. W. , Leeuwenburgh O. 
Published: February 2017

Abstract
An ensemble-based production optimization technique is applied to a simulation model of OMERS Energy's Chigwell Viking ‘I’ Pool in order to determine optimal CO2-WAG cycle length, injection rates and production bottom hole pressures (BHPs). An ensemble-based approximate gradient calculation is used in an expected net present value (NPV) maximization. A single model was fist used to contrast the individual optimization of injection rates and the injection cycle lengths with the combined optimization of rates and WAG cycle lengths in order to determine the best parameters to consider for WAG optimization. By combining cycle length, injection rate and production BHP controls, a significant increase in the NPV is observed relative to using injection rate and production BHP control only. The model's non-uniform well placement and geological properties require full individual controllability of the wells to realize the optimal sweep. The controllability offered by combining cycle length, injection rates and production BHP as controls for individual wells is seen to lead to solutions where some wells are under gas-only injection and other wells are under water-only injection for some time. The obtained solutions in general require fewer switches between injection phases and therefore offer a reduction of the operational costs and risks.
The optimization workflow and control parameterization are also applied to an ensemble of model realizations obtained by generating samples of the uncertain model parameters. The improvements in expected NPV demonstrate the practical applicability of ensemble-based approaches for optimization under uncertainty to real field cases. If CO2 storage credits are added to the objective function, a different control strategy is found that also leads to an increase in NPV. This result highlights the potential for economic incentives to increase both CO2 storage and oil recovery. We also demonstrate that the availability of CO2 (or, similarly, its price) will influence the optimal strategy, and therefore that strategies that work in one CO2 availability/price scenario may not necessarily be optimal in another one. The techniques discussed in this paper, however, can be applied to determine the optimal strategy for each particular operational scenario.
Simulation of Dynamic Steam-Trap Control Technique - Formulation, Implementation, and Performance Analysis
Authors: Heidari M. , Nghiem Long X. 
Published: February 2017

Abstract
Steam-trap subcool is a technique that is used to maintain the energy efficiency of the Steam-Assisted Gravity Drainage (SAGD) process by most heavy oil producers in Canada. The concept is rather simple, i.e., create a resistance (liquid pool) around the production well to prevent steam from escaping the steam chamber into the production well. A numerical steam-trap based on thermodynamic approach was implemented by Edmunds (1998) and it has been used in simulations with Sink/Source or more advanced wellbore models in commercial codes. In this approach, a hard constraint is solved to guarantee that the bottom-hole temperature is below the water saturation temperature and that the location of the hottest spot along the wellbore is static. Steam-trap is a dynamic process and inflow temperatures can vary significantly along the wellbore according to the local fluid and rock properties along the well. It is highly possible that the location of hottest spot along the well will change frequently with time during SAGD operation.
In this study, simulation of a dynamic steam-trap control technique is provided. The location of hottest spot along the wellbore is scanned at every time step. Severe numerical instabilities are observed when the thermodynamic approach is used as a hard constraint. A new constraint based on the total production rate at reservoir condition is introduced. Details of mathematical formulation and the numerical behavior of the new method are discussed in this paper. Several real field models with different wellbore designs (multiple tubing strings) are simulated and the results of the new approach are compared with the thermodynamic approach. Simulation results show that the numerical performance of this new approach is significantly more stable. A time comparison also shows the new constraint outperforms the thermodynamic hard constraint.
Dynamic Load Balancing Using Hilbert Space-Filling Curves for Parallel Reservoir Simulations
Authors: Liu Hui , Wang Kun , Yang Bo , Yang Min , He Ruijian , Shen Lihua , Zhong He , Chen Zhangxin 
Published: February 2017

Abstract
New reservoir simulators designed for parallel computers enable us to overcome performance limitations of workstations and personal computers and to simulate large-scale reservoir models with billions of grid cells. With development of parallel reservoir simulators, more complex physics and detailed models can be studied. The key to design efficient parallel reservoir simulators is not to improve the performance of individual CPUs drastically but to utilize the aggregation of computing power of all requested nodes through high speed networks. An ideal scenario is that when the number of MPI processors is doubled, the running time of parallel reservoir simulators is reduced by half. In real simulation, numerical difficulties and performance problems appear when the number of MPI processors grows due to the deteriorating linear solver efficiency and increasing communication overhead, which are determined by a grid distribution.
The goal of load balancing (grid partitioning) is to minimize overall computations and to make sure that all MPI processors have a similar workload. Geometric methods divide a grid by using a location of cells while topological methods work with connectivity of cells, which is generally described as a graph. The geometric methods are much faster than the topological methods. This paper introduces a Hilbert space-filling curve method. A space-filling curve is a continuous curve and defines a map between a onedimensional space and a multi-dimensional space. A Hilbert space-filling curve is one special space-filling curve discovered by Hilbert and has many useful characteristics, such as good locality, which means that two objects that are close to each other in a multi-dimensional space are also close to each other in a one dimensional space. This property can model communications in grid-based parallel applications. The idea of the Hilbert space-filling curve method is to map a computational domain into a one-dimensional space, partition the one-dimensional space to certain intervals, and assign all cells in a same interval to a MPI processor. To implement a dynamic load balancing method, we need a mapping kernel that converts high-dimensional coordinates to a scalar value, and an efficient one-dimensional partitioning module that divides a one-dimensional space and makes sure that all intervals have a similar workload.
The Hilbert space-filling curve method is compared with other load balancing methods, such as the K-way method from ParMETIS and other geometric methods from Zoltan. The results show that our Hilbert space-filling curve is much faster than graph methods. It also has good partition quality. This method has been applied to reservoir models with billions of grid cells and linear scalability has been obtained on many parallel computing systems.
A Comprehensive Geochemical-Based Approach at Modeling and Interpreting Brine Dilution in Carbonate Reservoirs
Authors: Awolayo Adedapo N. , Sarma Hemanta K. , Nghiem Long X. 
Published: February 2017

Abstract
It has been amply proven through laboratory studies, affirmed by a few field trials, that dilution of brine injected has a potent impact on improving oil recovery in carbonate reservoirs. However, debate still exists as to the mechanisms responsible for such impact. The widely acknowledged underlying mechanism is the wettability alteration, achieved through a combination of lower ionic strength, multi-ion exchange, surface charge and mineral alteration. Therefore, the motive behind this study is to develop a model that can further support and interpret the brine dilution approach in the framework of carbonate reservoirs.
In this paper, we formulated a theory for the observed behavior that coupled equations of multi-component transport and geochemical reactions. The geochemical system considered a choice of significant ions and minerals, relevant to the published experiments. Mechanisms included in the model were dispersion/diffusion, instantaneous equilibrium reactions in terms of intra-aqueous and sorption reactions, and non-equilibrium rate controlled kinetic reactions-mineral alteration. The equivalent modification in wettability was represented by interpolating through a set of flow functions, particularly the relative permeability characteristics.
The model was employed to interpret recently published experimental data on carbonate core plugs (Austad et al. (2011); Yousef et al. (2011); Yi and Sarma (2012); Chandrasekhar and Mohanty (2013)) where systematic dilutions of injectate against the initial formation brine were analyzed. Considering known values of injection rate, thermodynamic equilibrium constants, and reaction rate constants, the model was able to capture the trend of the experimental oil recovery and effluent ion concentrations. Thus, the model could help interpret the observed behavior as a sequel to an interplay between surface charge and mineral alteration. The trend typically reflected a speedy transient period at early times, trailed by relaxed transient period and finally reaching a steady state solution.
The model was used to closely examine the dominant chemical mechanism responsible for improved oil mobilization relating to brine dilution during smart waterflooding. A thorough understanding of the mechanisms at play during any recovery process is crucial for its successful implementation as well as reliable production modeling, forecasting and optimization.
A Near-Wellbore Study with a Drucker-Prager Plasticity Model Coupled with a Parallel Compositional Reservoir Simulator
Authors: White Deandra , Ganis Benjamin , Liu Ruijie , Wheeler Mary F. 
Published: February 2017

Abstract
Permanent deformations in the solid matrix can be caused by many field scenarios, such as high injection rates. A pressure differential in the field can create geomechanical loading of large magnitude that may increase stress from an elastic regime to a plastic regime. Simple geomechanical models based on linear elasticity are insufficient in predicting these types of effects. To accurately predict rock formation damage and failure responses, nonlinear analyses based on geomaterial plasticity models should be included in modeling frameworks through rigorous coupling with reservoir flow simulators.
In this work we integrate an implementation of the Drucker-Prager plasticity model into the parallel compositional reservoir simulator, IPARS (Integrated Parallel Accurate Reservoir Simulator). Fluid flow is formulated on general distorted hexahedral grids using the multipoint flux mixed finite element method. The mechanics and flow systems are solved separately and coupled using a fixed-stress iterative coupling algorithm. This allows multiple flow models to be used with nonlinear mechanics without modification, and allows each type of physics to employ the best preconditioner for its linear systems. The fixed-stress iteration converges to the fully coupled solution on each time step.
With these components in place, we conduct a study on wellbore stability using different flow and geomaterial models. We demonstrate the capabilities of our integrated simulator in predicting near-wellbore plastic strain development and its effect on multiphase component concentrations. Our simulations run efficiently in parallel using MPI on high performance computing platforms up to hundreds or thousands of processors. The results of the simulations are useful in predicting wellbore failure.
Our integrated simulator has several distinctive features. The use of general hexahedral finite element grids is particularly well-suited to handle domain specific applications such as near-wellbore studies. The multipoint flux scheme is an accurate and convergent method, it is locally conservative, and its linear systems are efficiently solved with multigrid methods. The use of a fixed-stress iterative coupling scheme is novel for coupling nonlinear mechanics with compositional fluid flow. Finally, to achieve fast convergence rates for solving nonlinear solid mechanics problems, a material integrator has been consistently formulated to give quadratic convergence rates.
Probabilistic Uncertainty Quantification of a Complex Field Using Advanced Proxy Based Methods and GPU-Based Reservoir Simulation
Authors: Goodwin N. , Esler K. , Ghasemi M. , Mukundakrishnan K. , Wang H. , Gilman J. R. , Lee B. 
Published: February 2017

Abstract

Objectives/Scope
History matching large, complex fields has remained time consuming, and valid probabilistic uncertainty quantification has been a distant goal. Significant advances have been made recently in the development of improved sampling algorithms, efficient and accurate proxy models, and extremely high-performance forward simulation using GPUs and scalable algorithms. Combining these, we present a highly efficient workflow for robust probabilistic forecasts of a real field model with detailed reservoir characterization and over thirty years of production history.

Methods, Procedures, Process
The model used here describes a highly faulted offshore field produced from two platforms with 11 distinct sand sub-intervals and 22 major faults. Geostatistical methods were used to estimate each reservoir's static property distribution based on well logs. This static 3D model was upscaled and combined with reservoir engineering data and historical-interpretations to provide initial fluid distribution for use in flow simulation history matching and forecasts. Hamiltonian Markov Chain Monte Carlo techniques coupled with an efficient implementation of proxy models are used for uncertainty quantifications. A fast, highly efficient and scalable GPU-based reservoir simulator is employed for all forward simulations.

Results, Observations, Conclusions
The complexity of the geological properties of the reservoir requires a large number of cells to adequately describe the dynamics of production, and many adjustable parameters are needed to characterize the uncertainties in the model. While the use of advanced sampling and proxies vastly reduces the number of detailed flow simulations needed, hundreds of forward simulations are still required to calibrate the proxies and production forecasts. The bandwidth and computational throughput provided by GPUs allow such simulations to be performed extremely fast using only a modest amount of hardware. Through this case study, we show that by coupling an advanced history matching, prediction and optimization tool with a fast GPU reservoir simulator, accurate probabilistic uncertainty quantification can be made practical even for large models.

Novel/Additive Information
The workflow presented here can potentially transform the way probabilistic uncertainty quantifications are performed on large real field models. It will lay the foundation for the next generation of fast and accurate uncertainty tools and workflows.