979 resultados para Simulação de fluxo


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The present study provides a methodology that gives a predictive character the computer simulations based on detailed models of the geometry of a porous medium. We using the software FLUENT to investigate the flow of a viscous Newtonian fluid through a random fractal medium which simplifies a two-dimensional disordered porous medium representing a petroleum reservoir. This fractal model is formed by obstacles of various sizes, whose size distribution function follows a power law where exponent is defined as the fractal dimension of fractionation Dff of the model characterizing the process of fragmentation these obstacles. They are randomly disposed in a rectangular channel. The modeling process incorporates modern concepts, scaling laws, to analyze the influence of heterogeneity found in the fields of the porosity and of the permeability in such a way as to characterize the medium in terms of their fractal properties. This procedure allows numerically analyze the measurements of permeability k and the drag coefficient Cd proposed relationships, like power law, for these properties on various modeling schemes. The purpose of this research is to study the variability provided by these heterogeneities where the velocity field and other details of viscous fluid dynamics are obtained by solving numerically the continuity and Navier-Stokes equations at pore level and observe how the fractal dimension of fractionation of the model can affect their hydrodynamic properties. This study were considered two classes of models, models with constant porosity, MPC, and models with varying porosity, MPV. The results have allowed us to find numerical relationship between the permeability, drag coefficient and the fractal dimension of fractionation of the medium. Based on these numerical results we have proposed scaling relations and algebraic expressions involving the relevant parameters of the phenomenon. In this study analytical equations were determined for Dff depending on the geometrical parameters of the models. We also found a relation between the permeability and the drag coefficient which is inversely proportional to one another. As for the difference in behavior it is most striking in the classes of models MPV. That is, the fact that the porosity vary in these models is an additional factor that plays a significant role in flow analysis. Finally, the results proved satisfactory and consistent, which demonstrates the effectiveness of the referred methodology for all applications analyzed in this study.

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The complexity of the Phenomenon of fluid flow in porous way causes a difficulty in its explicit description. Different in the cases where the flow is given through a pipe, where it is possible to measure the length and diameter of the pipe and to determine their ability to flow as a function of pressure, which is a complicated task in porous way. However, we try to approach clearly the equations used to conjecture the behavior of fluid flow in porous way. We made use of the Gambit to create a fractal geometry with the fluent we give the contour´s conditions we would want to analyze the data. The triangular mesh was created; it makes interactions with the discs of different rays, as barriers putted in the geometry. This work presents the results of a simulation with a flow of viscous fluids (oilliquid). The oil flows in a porous way constructed in 2D. The behavior evaluation of the fluid flow inside the porous way was realized with graphics, images and numerical results used for different datas analysis. The study was aimed in relation at the behavior of permeability (k) for different fractal dimensions. Taking into account the preservation of porosity and increasing the fractal distribution of the discs. The results showed that k decreases when we increase the numbers of discs, although the porosity is the same for all generations of the first simulation, in other words, the permeability decreases when we increase the fractality. Well, there are strong turbulence in the flow each time we increase the number of discs and this hinders the passage of the same to the exit. These results permitted to put in evidence how the permeability (k) is affected in a porous way with obstacles distributed in a diversified form. We also note that k decreases when we increase the pressure variation (P) within geometry. So, in front of the results and the absence of bibliographic subsidies about other theories, the work realized here can possibly by considered the unpublished form to explain and reflect on how the permeability is changed when increasing the fractal dimension in a porous way

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The present study provides a methodology that gives a predictive character the computer simulations based on detailed models of the geometry of a porous medium. We using the software FLUENT to investigate the flow of a viscous Newtonian fluid through a random fractal medium which simplifies a two-dimensional disordered porous medium representing a petroleum reservoir. This fractal model is formed by obstacles of various sizes, whose size distribution function follows a power law where exponent is defined as the fractal dimension of fractionation Dff of the model characterizing the process of fragmentation these obstacles. They are randomly disposed in a rectangular channel. The modeling process incorporates modern concepts, scaling laws, to analyze the influence of heterogeneity found in the fields of the porosity and of the permeability in such a way as to characterize the medium in terms of their fractal properties. This procedure allows numerically analyze the measurements of permeability k and the drag coefficient Cd proposed relationships, like power law, for these properties on various modeling schemes. The purpose of this research is to study the variability provided by these heterogeneities where the velocity field and other details of viscous fluid dynamics are obtained by solving numerically the continuity and Navier-Stokes equations at pore level and observe how the fractal dimension of fractionation of the model can affect their hydrodynamic properties. This study were considered two classes of models, models with constant porosity, MPC, and models with varying porosity, MPV. The results have allowed us to find numerical relationship between the permeability, drag coefficient and the fractal dimension of fractionation of the medium. Based on these numerical results we have proposed scaling relations and algebraic expressions involving the relevant parameters of the phenomenon. In this study analytical equations were determined for Dff depending on the geometrical parameters of the models. We also found a relation between the permeability and the drag coefficient which is inversely proportional to one another. As for the difference in behavior it is most striking in the classes of models MPV. That is, the fact that the porosity vary in these models is an additional factor that plays a significant role in flow analysis. Finally, the results proved satisfactory and consistent, which demonstrates the effectiveness of the referred methodology for all applications analyzed in this study.

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Until the early 90s, the simulation of fluid flow in oil reservoir basically used the numerical technique of finite differences. Since then, there was a big development in simulation technology based on streamlines, so that nowadays it is being used in several cases and it can represent the physical mechanisms that influence the fluid flow, such as compressibility, capillarity and gravitational segregation. Streamline-based flow simulation is a tool that can help enough in waterflood project management, because it provides important information not available through traditional simulation of finite differences and shows, in a direct way, the influence between injector well and producer well. This work presents the application of a methodology published in literature for optimizing water injection projects in modeling of a Brazilian Potiguar Basin reservoir that has a large number of wells. This methodology considers changes of injection well rates over time, based on information available through streamline simulation. This methodology reduces injection rates in wells of lower efficiency and increases injection rates in more efficient wells. In the proposed model, the methodology was effective. The optimized alternatives presented higher oil recovery associated with a lower water injection volume. This shows better efficiency and, consequently, reduction in costs. Considering the wide use of the water injection in oil fields, the positive outcome of the modeling is important, because it shows a case study of increasing of oil recovery achieved simply through better distribution of water injection rates

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The numeric simulation is an important tool applied in understanding the dynamics of groundwater flow. In a hydrogeological model the processes responsible for groundwater flow are described by numerical formulations that allow the simplification, representation and understanding of the dynamics of the Aquifer System. In this work, a steady state groundwater flow simulation of Urucuia Aquifer System (UAS) part of the Corrente river basin was conducted, using the finite element method through software FEFLOW, to understand the dynamics of groundwater flow and quantify the hydrologic balance. The aquifer system Urucuia lodges in the São Francisco hydrogeological province and corresponds to a set of interconnected aquifers that occur in rocks from Urucuia group in the Urucuia sub-basin described by Campos e Dardenne (1997). The system is a porous media one, in a shape of a thick table mountain, consisting essentially of sandstones. The Corrente river basin is located in UAS in Western State of Bahia and it's one of the main units to maintaining permanent flow (Q95) and average natural flow of the São Francisco river. The simulation performed in this work obtained the following results for the modelled region: horizontal hydraulic conductivity of 3 x 10-4 m/s and vertical one 6 x 10-5 m/s; maximum recharge of 345 mm and minimum of 85 mm/a. It was concluded that: (1) regional groundwater flow has eastbound; with an exception of the extreme northeast portion, where the flow has opposite direction; (2) there are smaller water side dividers with an approximate direction EW, that guide the flow of water to the drainage that cut the aquifer; and (3) the UAS at Corrente river basin can be understood as a free regional aquifer system, isotropic and homogeneous. Regionally, the small lithological variations present in the Urucuia group can be neglected and do not exhibit significant influences on the dynamics of ground water flow

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Until the early 90s, the simulation of fluid flow in oil reservoir basically used the numerical technique of finite differences. Since then, there was a big development in simulation technology based on streamlines, so that nowadays it is being used in several cases and it can represent the physical mechanisms that influence the fluid flow, such as compressibility, capillarity and gravitational segregation. Streamline-based flow simulation is a tool that can help enough in waterflood project management, because it provides important information not available through traditional simulation of finite differences and shows, in a direct way, the influence between injector well and producer well. This work presents the application of a methodology published in literature for optimizing water injection projects in modeling of a Brazilian Potiguar Basin reservoir that has a large number of wells. This methodology considers changes of injection well rates over time, based on information available through streamline simulation. This methodology reduces injection rates in wells of lower efficiency and increases injection rates in more efficient wells. In the proposed model, the methodology was effective. The optimized alternatives presented higher oil recovery associated with a lower water injection volume. This shows better efficiency and, consequently, reduction in costs. Considering the wide use of the water injection in oil fields, the positive outcome of the modeling is important, because it shows a case study of increasing of oil recovery achieved simply through better distribution of water injection rates

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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The high dependence of Portugal from foreign energy sources (mainly fossil fuels), together with the international commitments assumed by Portugal and the national strategy in terms of energy policy, as well as resources sustainability and climate change issues, inevitably force Portugal to invest in its energetic self-sufficiency. The 20/20/20 Strategy defined by the European Union defines that in 2020 60% of the total electricity consumption must come from renewable energy sources. Wind energy is currently a major source of electricity generation in Portugal, producing about 23% of the national total electricity consumption in 2013. The National Energy Strategy 2020 (ENE2020), which aims to ensure the national compliance of the European Strategy 20/20/20, states that about half of this 60% target will be provided by wind energy. This work aims to implement and optimise a numerical weather prediction model in the simulation and modelling of the wind energy resource in Portugal, both in offshore and onshore areas. The numerical model optimisation consisted in the determination of which initial and boundary conditions and planetary boundary layer physical parameterizations options provide wind power flux (or energy density), wind speed and direction simulations closest to in situ measured wind data. Specifically for offshore areas, it is also intended to evaluate if the numerical model, once optimised, is able to produce power flux, wind speed and direction simulations more consistent with in situ measured data than wind measurements collected by satellites. This work also aims to study and analyse possible impacts that anthropogenic climate changes may have on the future wind energetic resource in Europe. The results show that the ECMWF reanalysis ERA-Interim are those that, among all the forcing databases currently available to drive numerical weather prediction models, allow wind power flux, wind speed and direction simulations more consistent with in situ wind measurements. It was also found that the Pleim-Xiu and ACM2 planetary boundary layer parameterizations are the ones that showed the best performance in terms of wind power flux, wind speed and direction simulations. This model optimisation allowed a significant reduction of the wind power flux, wind speed and direction simulations errors and, specifically for offshore areas, wind power flux, wind speed and direction simulations more consistent with in situ wind measurements than data obtained from satellites, which is a very valuable and interesting achievement. This work also revealed that future anthropogenic climate changes can negatively impact future European wind energy resource, due to tendencies towards a reduction in future wind speeds especially by the end of the current century and under stronger radiative forcing conditions.

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In the present study we elaborated algorithms by using concepts from percolation theory which analyze the connectivity conditions in geological models of petroleum reservoirs. From the petrophysical parameters such as permeability, porosity, transmittivity and others, which may be generated by any statistical process, it is possible to determine the portion of the model with more connected cells, what the interconnected wells are, and the critical path between injector and source wells. This allows to classify the reservoir according to the modeled petrophysical parameters. This also make it possible to determine the percentage of the reservoir to which each well is connected. Generally, the connected regions and the respective minima and/or maxima in the occurrence of the petrophysical parameters studied constitute a good manner to characterize a reservoir volumetrically. Therefore, the algorithms allow to optimize the positioning of wells, offering a preview of the general conditions of the given model s connectivity. The intent is not to evaluate geological models, but to show how to interpret the deposits, how their petrophysical characteristics are spatially distributed, and how the connections between the several parts of the system are resolved, showing their critical paths and backbones. The execution of these algorithms allows us to know the properties of the model s connectivity before the work on reservoir flux simulation is started

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Nearly 3 x 1011 m3 of medium and light oils will remain in reservoirs worldwide after conventional recovery methods have been exhausted and much of this volume would be recovered by Enhanced Oil Recovery (EOR) methods. The in-situ combustion (ISC) is an EOR method in which an oxygen-containing gas is injected into a reservoir where it reacts with the crude oil to create a high-temperature combustion front that is propagated through the reservoir. The High Pressure Air Injection (HPAI) method is a particular denomination of the air injection process applied in light oil reservoirs, for which the combustion reactions are dominant between 150 and 300°C and the generation of flue gas is the main factor to the oil displacement. A simulation model of a homogeneous reservoir was built to study, which was initially undergone to primary production, for 3 years, next by a waterflooding process for 21 more years. At this point, with the mature condition established into the reservoir, three variations of this model were selected, according to the recovery factors (RF) reached, for study the in-situ combustion (HPAI) technique. Next to this, a sensitivity analysis on the RF of characteristic operational parameters of the method was carried out: air injection rate per well, oxygen concentration into the injected gas, patterns of air injection and wells perforations configuration. This analysis, for 10 more years of production time, was performed with assistance of the central composite design. The reservoir behavior and the impacts of chemical reactions parameters and of reservoir particularities on the RF were also evaluated. An economic analysis and a study to maximize the RF of the process were also carried out. The simulation runs were performed in the simulator of thermal processes in reservoirs STARS (Steam, Thermal, and Advanced Processes Reservoir Simulator) from CMG (Computer Modelling Group). The results showed the incremental RF were small and the net present value (NPV) is affected by high initial investments to compress the air. It was noticed that the adoption of high oxygen concentration into the injected gas and of the five spot pattern tends to improve the RF, and the wells perforations configuration has more influence with the increase of the oil thickness. Simulated cases relating to the reservoir particularities showed that smaller residual oil saturations to gas lead to greater RF and the presence of heterogeneities results in important variations on the RF and on the production curves

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The history match procedure in an oil reservoir is of paramount importance in order to obtain a characterization of the reservoir parameters (statics and dynamics) that implicates in a predict production more perfected. Throughout this process one can find reservoir model parameters which are able to reproduce the behaviour of a real reservoir.Thus, this reservoir model may be used to predict production and can aid the oil file management. During the history match procedure the reservoir model parameters are modified and for every new set of reservoir model parameters found, a fluid flow simulation is performed so that it is possible to evaluate weather or not this new set of parameters reproduces the observations in the actual reservoir. The reservoir is said to be matched when the discrepancies between the model predictions and the observations of the real reservoir are below a certain tolerance. The determination of the model parameters via history matching requires the minimisation of an objective function (difference between the observed and simulated productions according to a chosen norm) in a parameter space populated by many local minima. In other words, more than one set of reservoir model parameters fits the observation. With respect to the non-uniqueness of the solution, the inverse problem associated to history match is ill-posed. In order to reduce this ambiguity, it is necessary to incorporate a priori information and constraints in the model reservoir parameters to be determined. In this dissertation, the regularization of the inverse problem associated to the history match was performed via the introduction of a smoothness constraint in the following parameter: permeability and porosity. This constraint has geological bias of asserting that these two properties smoothly vary in space. In this sense, it is necessary to find the right relative weight of this constrain in the objective function that stabilizes the inversion and yet, introduces minimum bias. A sequential search method called COMPLEX was used to find the reservoir model parameters that best reproduce the observations of a semi-synthetic model. This method does not require the usage of derivatives when searching for the minimum of the objective function. Here, it is shown that the judicious introduction of the smoothness constraint in the objective function formulation reduces the associated ambiguity and introduces minimum bias in the estimates of permeability and porosity of the semi-synthetic reservoir model

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The understanding of the occurrence and flow of groundwater in the subsurface is of fundamental importance in the exploitation of water, just like knowledge of all associated hydrogeological context. These factors are primarily controlled by geometry of a certain pore system, given the nature of sedimentary aquifers. Thus, the microstructural characterization, as the interconnectivity of the system, it is essential to know the macro properties porosity and permeability of reservoir rock, in which can be done on a statistical characterization by twodimensional analysis. The latter is being held on a computing platform, using image thin sections of reservoir rock, allowing the prediction of the properties effective porosity and hydraulic conductivity. For Barreiras Aquifer to obtain such parameters derived primarily from the interpretation of tests of aquifers, a practice that usually involves a fairly complex logistics in terms of equipment and personnel required in addition to high cost of operation. Thus, the analysis and digital image processing is presented as an alternative tool for the characterization of hydraulic parameters, showing up as a practical and inexpensive method. This methodology is based on a flowchart work involving sampling, preparation of thin sections and their respective images, segmentation and geometric characterization, three-dimensional reconstruction and flow simulation. In this research, computational image analysis of thin sections of rocks has shown that aquifer storage coefficients ranging from 0,035 to 0,12 with an average of 0,076, while its hydrogeological substrate (associated with the top of the carbonate sequence outcropping not region) presents effective porosities of the order of 2%. For the transport regime, it is evidenced that the methodology presents results below of those found in the bibliographic data relating to hydraulic conductivity, mean values of 1,04 x10-6 m/s, with fluctuations between 2,94 x10-6 m/s and 3,61x10-8 m/s, probably due to the larger scale study and the heterogeneity of the medium studied.

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Modelos para simulação do fluxo de água no solo e previsão de produtividade de culturas requerem informações sobre parâmetros das curvas de retenção e condutividade hidráulica do solo. Funções de pedotransferência (PTFs) se constituem numa alternativa para obtenção dessas informações, a partir de dados de textura e estrutura disponíveis em levantamentos de solos. Neste trabalho, foram ajustadas PTFs para os parâmetros do modelo de van Genuchten (vG), utilizando dados de 838 curvas de retenção de diferentes locais do Nordeste. As PTFs apresentaram boa qualidade de ajuste para os parâmetros θr e θs em contraste com a baixa capacidade preditiva para logα e n. Tais resultados sugerem a viabilidade do seu uso em modelos de simulação do balanço hídrico simplificado e para algumas aplicações práticas de irrigação. No entanto, para uso em modelos complexos de fluxo de água é importante avaliar a sensibilidade das variáveis prognósticas (produtividade agrícola, concentração de solutos) a variações nos parâmetros de vG. A alta variabilidade observada tanto nas propriedades morfológicas como nos parâmetros de vG para a região de estudo sugere o agrupamento dos dados em classes texturais ou tipos de solos.

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In the present study we elaborated algorithms by using concepts from percolation theory which analyze the connectivity conditions in geological models of petroleum reservoirs. From the petrophysical parameters such as permeability, porosity, transmittivity and others, which may be generated by any statistical process, it is possible to determine the portion of the model with more connected cells, what the interconnected wells are, and the critical path between injector and source wells. This allows to classify the reservoir according to the modeled petrophysical parameters. This also make it possible to determine the percentage of the reservoir to which each well is connected. Generally, the connected regions and the respective minima and/or maxima in the occurrence of the petrophysical parameters studied constitute a good manner to characterize a reservoir volumetrically. Therefore, the algorithms allow to optimize the positioning of wells, offering a preview of the general conditions of the given model s connectivity. The intent is not to evaluate geological models, but to show how to interpret the deposits, how their petrophysical characteristics are spatially distributed, and how the connections between the several parts of the system are resolved, showing their critical paths and backbones. The execution of these algorithms allows us to know the properties of the model s connectivity before the work on reservoir flux simulation is started