941 resultados para black oil model


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This paper discusses preconditioned Krylov subspace methods for solving large scale linear systems that originate from oil reservoir numerical simulations. Two types of preconditioners, one being based on an incomplete LU decomposition and the other being based on iterative algorithms, are used together in a combination strategy in order to achieve an adaptive and efficient preconditioner. Numerical tests show that different Krylov subspace methods combining with appropriate preconditioners are able to achieve optimal performance.

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Programa informático desarrollado en plataforma EXCEL (VBA) y dirigido al diseño de Separadores de dos y tres fases, verticales y horizontales. El programa de ordenador o aplicación tiene la capacidad de determinar las propiedades físicas del fluido, utilizando diferentes correlaciones sobre la base del “Black Oil Model”, con dichas propiedades el Programa predice el tipo de flujo presente. Si el tipo de flujo es “Slug Flow” el programa determinara las dimensiones del “Slug catcher” necesario. Bajo las condiciones de funcionamiento existentes el programa diseñará el separador elegido: dos o tres fases, vertical u horizontal. Por último, la aplicación informática estimará el coste del equipo. Abstract Computer program developed in EXCEL (VBA) platform and aimed for the design of Two-Phase, Three-Phase, Vertical or Horizontal Separators. The computer Program or Application has the capability to determine the fluid physical properties utilizing different correlations on the basis of the Black Oil Model, with those Properties the Program will predict the Flow Regime present. If the flow regime is Slug Flow the program will determine the necessary slug catcher dimensions. Under certain operational conditions the program will design the selected: Two-Phase or Three-Phase, Vertical or Horizontal Separator. Finally the computer Application will estimate the cost of the equipment.

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This paper presents a scalable, statistical ‘black-box’ model for predicting the performance of parallel programs on multi-core non-uniform memory access (NUMA) systems. We derive a model with low overhead, by reducing data collection and model training time. The model can accurately predict the behaviour of parallel applications in response to changes in their concurrency, thread layout on NUMA nodes, and core voltage and frequency. We present a framework that applies the model to achieve significant energy and energy-delay-square (ED2) savings (9% and 25%, respectively) along with performance improvement (10% mean) on an actual 16-core NUMA system running realistic application workloads. Our prediction model proves substantially more accurate than previous efforts.

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O modelo Black-Litterman calcula os retornos esperados de mercado como uma combinação de um conjunto de expectativas específicas de cada investidor e um ponto de referência neutro. A combinação dessas duas fontes de informações são feitas pelo modelo utilizando a abordagem bayesiana. Os resultados obtidos a partir do modelo Black-Litterman, ao contrário da abordagem tradicional, são bastante intuitivos, estáveis e consistentes em relação as expectativas dos investidores. O objetivo dessa dissertação é fazer uma análise detalhada de cada um dos componentes do modelo Black-Litterman e verificar se a utilização o modelo de Black-Litterman, introduzindo as opiniões de mercado com base no relatório FOCUS do Banco Central, supera o retorno dos fundos multimercados brasileiros.

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Qual o efeito de eleições em ativos reais? É possível mensurar diretamente a diferença de preços mesmo que só possamos enxergar um dos resultados potenciais? Essa dissertação estima esses efeitos utilizando metodologia baseada em opções sobre ações. O modelo aqui desenvolvido adaptção tradicional Black-Scholes para incorporar dois novos parâmetros: um salto no preço do ativo perfeitamente antecipado e uma série de probabilidades diárias refletindo as crenças sobre quem venceria a corrida eleitoral. Aplicamos esse método para o caso brasileiro das Eleições Presidenciais de 2014 e a Petrobras - uma importante companhia do setor petrolífero do país -utilizando dados de bolsa do segundo turno das eleições. Os resultados encontrados mostram uma diferença de 65-77% para o valor da companhia, dependendo de quem vencesse nas urnas. Isso é equivalente a aproximadamente 2.5% do PIB de 2014 do país.

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In Brazilian Northeast there are reservoirs with heavy oil, which use steam flooding as a recovery method. This process allows to reduce oil viscosity, increasing its mobility and consequently its oil recovery. Steam injection is a thermal method and can occurs in continues or cyclic form. Cyclic steam stimulation (CSS) can be repeated several times. Each cycle consisting of three stages: steam injection, soaking time and production phase. CSS becomes less efficient with an increase of number of cycles. Thus, this work aims to study the influence of compositional models in cyclic steam injection and the effects of some parameters, such like: flow injection, steam quality and temperature of steam injected, analyzing the influence of pseudocomponents numbers on oil rate, cumulative oil, oil recovery and simulation time. In the situations analyzed was compared the model of fluid of three phases and three components known as Blackoil . Simulations were done using commercial software (CMG), it was analyzed a homogeneous reservoir with characteristics similar to those found in Brazilian Northeast. It was observed that an increase of components number, increase the time spent in simulation. As for analyzed parameters, it appears that the steam rate, and steam quality has influence on cumulative oil and oil recovery. The number of components did not a lot influenced on oil recovery, however it has influenced on gas production

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A mathematical model and numerical simulations are presented to investigate the dynamics of gas, oil and water flow in a pipeline-riser system. The pipeline is modeled as a lumped parameter system and considers two switchable states: one in which the gas is able to penetrate into the riser and another in which there is a liquid accumulation front, preventing the gas from penetrating the riser. The riser model considers a distributed parameter system, in which movable nodes are used to evaluate local conditions along the subsystem. Mass transfer effects are modeled by using a black oil approximation. The model predicts the liquid penetration length in the pipeline and the liquid level in the riser, so it is possible to determine which type of severe slugging occurs in the system. The method of characteristics is used to simplify the differentiation of the resulting hyperbolic system of equations. The equations are discretized and integrated using an implicit method with a predictor-corrector scheme for the treatment of the nonlinearities. Simulations corresponding to severe slugging conditions are presented and compared to results obtained with OLGA computer code, showing a very good agreement. A description of the types of severe slugging for the three-phase flow of gas, oil and water in a pipeline-riser system with mass transfer effects are presented, as well as a stability map. (C) 2011 Elsevier Ltd. All rights reserved.

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In this work we are concerned with the analysis and numerical solution of Black-Scholes type equations arising in the modeling of incomplete financial markets and an inverse problem of determining the local volatility function in a generalized Black-Scholes model from observed option prices. In the first chapter a fully nonlinear Black-Scholes equation which models transaction costs arising in option pricing is discretized by a new high order compact scheme. The compact scheme is proved to be unconditionally stable and non-oscillatory and is very efficient compared to classical schemes. Moreover, it is shown that the finite difference solution converges locally uniformly to the unique viscosity solution of the continuous equation. In the next chapter we turn to the calibration problem of computing local volatility functions from market data in a generalized Black-Scholes setting. We follow an optimal control approach in a Lagrangian framework. We show the existence of a global solution and study first- and second-order optimality conditions. Furthermore, we propose an algorithm that is based on a globalized sequential quadratic programming method and a primal-dual active set strategy, and present numerical results. In the last chapter we consider a quasilinear parabolic equation with quadratic gradient terms, which arises in the modeling of an optimal portfolio in incomplete markets. The existence of weak solutions is shown by considering a sequence of approximate solutions. The main difficulty of the proof is to infer the strong convergence of the sequence. Furthermore, we prove the uniqueness of weak solutions under a smallness condition on the derivatives of the covariance matrices with respect to the solution, but without additional regularity assumptions on the solution. The results are illustrated by a numerical example.

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In this paper, we investigate the suitability of the grand canonical Monte Carlo in the description of adsorption equilibria of flexible n-alkane (butane, pentane and hexane) on graphitized thermal carbon black. Potential model of n-alkane of Martin and Siepmann (J. Phys. Chem. 102 (1998) 2569) is employed in the simulation, and we consider the flexibility of molecule in the simulation. By this we study two models, one is the fully flexible molecular model in which n-alkane is subject to bending and torsion, while the other is the rigid molecular model in which all carbon atoms reside on the same plane. It is found that (i) the adsorption isotherm results of these two models are close to each other, suggesting that n-alkane model behaves mostly as rigid molecules with respect to adsorption although the isotherm for longer chain n-hexane is better described by the flexible molecular model (ii) the isotherms agree very well with the experimental data at least up to two layers on the surface.

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In Brazilian Northeast there are reservoirs with heavy oil, which use steam flooding as a recovery method. This process allows to reduce oil viscosity, increasing its mobility and consequently its oil recovery. Steam injection is a thermal method and can occurs in continues or cyclic form. Cyclic steam stimulation (CSS) can be repeated several times. Each cycle consisting of three stages: steam injection, soaking time and production phase. CSS becomes less efficient with an increase of number of cycles. Thus, this work aims to study the influence of compositional models in cyclic steam injection and the effects of some parameters, such like: flow injection, steam quality and temperature of steam injected, analyzing the influence of pseudocomponents numbers on oil rate, cumulative oil, oil recovery and simulation time. In the situations analyzed was compared the model of fluid of three phases and three components known as Blackoil . Simulations were done using commercial software (CMG), it was analyzed a homogeneous reservoir with characteristics similar to those found in Brazilian Northeast. It was observed that an increase of components number, increase the time spent in simulation. As for analyzed parameters, it appears that the steam rate, and steam quality has influence on cumulative oil and oil recovery. The number of components did not a lot influenced on oil recovery, however it has influenced on gas production

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In this paper, we examine the predictability of observed volatility smiles in three major European index options markets, utilising the historical return distributions of the respective underlying assets. The analysis involves an application of the Black (1976) pricing model adjusted in accordance with the Jarrow-Rudd methodology as proposed in 1982. Thereby we adjust the expected future returns for the third and fourth central moments as these represent deviations from normality in the distributions of observed returns. Thus, they are considered one possible explanation to the existence of the smile. The obtained results indicate that the inclusion of the higher moments in the pricing model to some extent reduces the volatility smile, compared with the unadjusted Black-76 model. However, as the smile is partly a function of supply, demand, and liquidity, and as such intricate to model, this modification does not appear sufficient to fully capture the characteristics of the smile.

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Tensile-strained GaAsP/GaInP single quantum well (QW) laser diode (I-D) structures have been grown by low-pressure metal organic chemical vapor deposition (LP-MOCVD) and related photoluminescence (PL) properties have been investigated in detail. The samples have the same well thickness of 16 nm but different P compositions in a GaAsP QW. Two peaks in room temperature (RT) PL spectra are observed for samples with a composition larger than 0.10. Temperature and excitation-power-dependent PL spectra have been measured for a sample with it P composition of 0.15. It is found that the two peaks have a 35 meV energy separation independent of temperature and only the low-energy peak exists below 85 K. Additionally, both peak intensities exhibit a monotonous increase as excitation power increases. Analyses indicate that the two peaks arise from the intrinsic-exciton recombination mechanisms of electron-heavy hole (e-hh) and electron-light hole (e-hh). A theoretical calculation based oil model-solid theory, taking, into account the spin-orbit splitting energy, shows good agreement with our experimental results. The temperature dependence of PL intensity ratio is well explained using the spontaneous emission theory for e-hh and e-hh transitions. front which the ratio can be characterized mainly by the energy separation between the fill and Ill states.

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Signal transduction pathways describe the dynamics of cellular response to input signalling molecules at receptors on the cell membrane. The Mitogen-Activated Protein Kinase (MAPK) cascade is one of such pathways that are involved in many important cellular processes including cell growth and proliferation. This paper describes a black-box model of this pathway created using an advanced two-stage identification algorithm. Identification allows us to capture the unique features and dynamics of the pathway and also opens up the possibility of regulatory control design. In the approach described, an optimal model is obtained by performing model subset selection in two stages, where the terms are first determined by a forward selection method and then modified using a backward selection model refinement. The simulation results demonstrate that the model selected using the two-stage algorithm performs better than with the forward selection method alone.