14 resultados para sensitivity analysis

em Universidade Federal do Rio Grande do Norte(UFRN)


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Electrical resistive heating (ERH) is a thermal method used to improve oil recovery. It can increase oil rate and oil recovery due to temperature increase caused by electrical current passage through oil zone. ERH has some advantage compared with well-known thermal methods such as continuous steam flood, presenting low-water production. This method can be applied to reservoirs with different characteristics and initial reservoir conditions. Commercial software was used to test several cases using a semi-synthetic homogeneous reservoir with some characteristics as found in northeast Brazilian basins. It was realized a sensitivity analysis of some reservoir parameters, such as: oil zone, aquifer presence, gas cap presence and oil saturation on oil recovery and energy consumption. Then it was tested several cases studying the electrical variables considered more important in the process, such as: voltage, electrical configurations and electrodes positions. Energy optimization by electrodes voltage levels changes and electrical settings modify the intensity and the electrical current distribution in oil zone and, consequently, their influences in reservoir temperature reached at some regions. Results show which reservoir parameters were significant in order to improve oil recovery and energy requirement in for each reservoir. Most significant parameters on oil recovery and electrical energy delivered were oil thickness, presence of aquifer, presence of gas cap, voltage, electrical configuration and electrodes positions. Factors such as: connate water, water salinity and relative permeability to water at irreducible oil saturation had low influence on oil recovery but had some influence in energy requirements. It was possible to optimize energy consumption and oil recovery by electrical variables. Energy requirements can decrease by changing electrodes voltages during the process. This application can be extended to heavy oil reservoirs of high depth, such as offshore fields, where nowadays it is not applicable any conventional thermal process such as steam flooding

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Water injection is the most widely used method for supplementary recovery in many oil fields due to various reasons, like the fact that water is an effective displacing agent of low viscosity oils, the water injection projects are relatively simple to establish and the water availability at a relatively low cost. For design of water injection projects is necessary to do reservoir studies in order to define the various parameters needed to increase the effectiveness of the method. For this kind of study can be used several mathematical models classified into two general categories: analytical or numerical. The present work aims to do a comparative analysis between the results presented by flow lines simulator and conventional finite differences simulator; both types of simulators are based on numerical methods designed to model light oil reservoirs subjected to water injection. Therefore, it was defined two reservoir models: the first one was a heterogeneous model whose petrophysical properties vary along the reservoir and the other one was created using average petrophysical properties obtained from the first model. Comparisons were done considering that the results of these two models were always in the same operational conditions. Then some rock and fluid parameters have been changed in both models and again the results were compared. From the factorial design, that was done to study the sensitivity analysis of reservoir parameters, a few cases were chosen to study the role of water injection rate and the vertical position of wells perforations in production forecast. It was observed that the results from the two simulators are quite similar in most of the cases; differences were found only in those cases where there was an increase in gas solubility ratio of the model. Thus, it was concluded that in flow simulation of reservoirs analogous of those now studied, mainly when the gas solubility ratio is low, the conventional finite differences simulator may be replaced by flow lines simulator the production forecast is compatible but the computational processing time is lower.

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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 objective of this dissertation is to propose a Multi Criteria Decision Aid Model to be used by the costumers of the travel agencies and help them to choose the best package travel. The main objective is to contribute for the simplification of the travel package decision choice from the identification of the models of values and preference of the customers and applying them to the existing package. It is used the Analytic Hierarchy Process (AHP) method to structuralize a decision hierarchic model composed by six criteria (package cost, hotel category, security of the city, travel time, direct flight and position in ranking of the 10 most visited destination) and five real alternatives of packages for a holiday of three days created from travel agency data. The decision analysis was realized for the choice of a travel package by a group composed by two couples that regularly travels together, to which was asked to do a pairwise judgment of the criteria and the alternatives. The mains results show that, although been a group that travels together, there are different models of values in the weights of the criteria and a certain convergence in the scales of preferences of the alternatives in the criteria. It was not pointed a dominant alternative for all the members of the group separately, but an analysis of a total utility of the group shows a classification and an order of the travel packages and an alternative clearly in front of the others. The sensitivity analysis revels that there are changes in the ranking, but the two alternatives best classified in the normal analysis are the same ones in the sensitivity analysis, although with the positions changed. The analysis also led to a simplification of the process with the exclusion of alternatives dominated for the others ones. As main conclusion, it is evaluated that the model and method suggested allow a simplification of the decision process in the choice of travel packages

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The portfolio theory is a field of study devoted to investigate the decision-making by investors of resources. The purpose of this process is to reduce risk through diversification and thus guarantee a return. Nevertheless, the classical Mean-Variance has been criticized regarding its parameters and it is observed that the use of variance and covariance has sensitivity to the market and parameter estimation. In order to reduce the estimation errors, the Bayesian models have more flexibility in modeling, capable of insert quantitative and qualitative parameters about the behavior of the market as a way of reducing errors. Observing this, the present study aimed to formulate a new matrix model using Bayesian inference as a way to replace the covariance in the MV model, called MCB - Covariance Bayesian model. To evaluate the model, some hypotheses were analyzed using the method ex post facto and sensitivity analysis. The benchmarks used as reference were: (1) the classical Mean Variance, (2) the Bovespa index's market, and (3) in addition 94 investment funds. The returns earned during the period May 2002 to December 2009 demonstrated the superiority of MCB in relation to the classical model MV and the Bovespa Index, but taking a little more diversifiable risk that the MV. The robust analysis of the model, considering the time horizon, found returns near the Bovespa index, taking less risk than the market. Finally, in relation to the index of Mao, the model showed satisfactory, return and risk, especially in longer maturities. Some considerations were made, as well as suggestions for further work

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This work proposes a computational methodology to solve problems of optimization in structural design. The application develops, implements and integrates methods for structural analysis, geometric modeling, design sensitivity analysis and optimization. So, the optimum design problem is particularized for plane stress case, with the objective to minimize the structural mass subject to a stress criterion. Notice that, these constraints must be evaluated at a series of discrete points, whose distribution should be dense enough in order to minimize the chance of any significant constraint violation between specified points. Therefore, the local stress constraints are transformed into a global stress measure reducing the computational cost in deriving the optimal shape design. The problem is approximated by Finite Element Method using Lagrangian triangular elements with six nodes, and use a automatic mesh generation with a mesh quality criterion of geometric element. The geometric modeling, i.e., the contour is defined by parametric curves of type B-splines, these curves hold suitable characteristics to implement the Shape Optimization Method, that uses the key points like design variables to determine the solution of minimum problem. A reliable tool for design sensitivity analysis is a prerequisite for performing interactive structural design, synthesis and optimization. General expressions for design sensitivity analysis are derived with respect to key points of B-splines. The method of design sensitivity analysis used is the adjoin approach and the analytical method. The formulation of the optimization problem applies the Augmented Lagrangian Method, which convert an optimization problem constrained problem in an unconstrained. The solution of the Augmented Lagrangian function is achieved by determining the analysis of sensitivity. Therefore, the optimization problem reduces to the solution of a sequence of problems with lateral limits constraints, which is solved by the Memoryless Quasi-Newton Method It is demonstrated by several examples that this new approach of analytical design sensitivity analysis of integrated shape design optimization with a global stress criterion purpose is computationally efficient

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This paper presents an analysis of technical and financial feasibility of the use of a solar system for water heating in a fictitious hotel located in the Northeast region. Thereunto it is used techniques of solar collectors´ sizing and methods of financial mathematics, such as Net Present Value (NPV), Internal Rate of Return (IRR) and Payback. It will also be presented a sensitivity analysis to verify which are the factors that impact the viability of the solar heating. Comparative analysis will be used concerning three cities of distinct regions of Brazil: Curitiba, Belém and João Pessoa. The viability of using a solar heating system will be demonstrated to the whole Brazil, especially to the northeast region as it is the most viable for such an application of solar power because of its high levels of solar radiation. Among the cities examined for a future installation of solar heating systems for water heating in the hotel chain, João Pessoa was the one that has proved more viable.

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This work presents an optimization technique based on structural topology optimization methods, TOM, designed to solve problems of thermoelasticity 3D. The presented approach is based on the adjoint method of sensitivity analysis unified design and is intended to loosely coupled thermomechanical problems. The technique makes use of analytical expressions of sensitivities, enabling a reduction in the computational cost through the use of a coupled field adjoint equation, defined in terms the of temperature and displacement fields. The TOM used is based on the material aproach. Thus, to make the domain is composed of a continuous distribution of material, enabling the use of classical models in nonlinear programming optimization problem, the microstructure is considered as a porous medium and its constitutive equation is a function only of the homogenized relative density of the material. In this approach, the actual properties of materials with intermediate densities are penalized based on an artificial microstructure model based on the SIMP (Solid Isotropic Material with Penalty). To circumvent problems chessboard and reduce dependence on layout in relation to the final optimal initial mesh, caused by problems of numerical instability, restrictions on components of the gradient of relative densities were applied. The optimization problem is solved by applying the augmented Lagrangian method, the solution being obtained by applying the finite element method of Galerkin, the process of approximation using the finite element Tetra4. This element has the ability to interpolate both the relative density and the displacement components and temperature. As for the definition of the problem, the heat load is assumed in steady state, i.e., the effects of conduction and convection of heat does not vary with time. The mechanical load is assumed static and distributed

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The management of water resources in the river basin level, as it defines the Law nº 9433/97, requires the effective knowledge of the processes of hydrological basin, resulting from studies based on consistent series of hydrological data that reflect the characteristics of the basin. In this context, the objective of this work was to develop the modeling of catchment basin of the river Jundiaí - RN and carry out the study of attenuation of a flood of the dam Tabatinga, by means of a monitoring project of hydrological data and climatology of the basin, with a view to promoting the development of research activities by applying methodologies unified and appropriate for the assessment of hydrological studies in the transition region of the semiarid and the forest zone on the coast of Rio Grande do Norte. For the study of the hydrological characteristics of the basin was conducted the automatic design of the basin of the river Jundiaí, with the aid of programs of geoprocessing, was adopted a hydrological model daily, the NRCS, which is a model determined and concentrated. For the use of this model was necessary to determine some parameters that are used in this model, as the Curve Number. Having in mind that this is the first study that is being conducted in the basin with the employment of this model, it was made sensitivity analysis of the results of this model from the adoption of different values of CN, situated within a range appropriate to the conditions of use, occupation and the nature of the soil of this basin. As the objective of this study was also developing a simulation model of the operation of the Tabatinga dam and with this flood control caused in the city of Macaíba, it was developed a mathematical model of fluid balance, developed to be used in Microsoft Excel. The simulation was conducted in two phases: the first step was promoted the water balance daily that allowed the analysis of the sensitivity of the model in relation to the volume of waiting, as well as the determination of the period of greatest discharges daily averages. From this point, it was assumed for the second stage, which was in the determination of the hydrograph of discharges effluent slots, that was determined by means of the fluid balance time, on the basis of the discharges effluents generated by a mathematical equation whose parameters were adjusted according to the hydrograph daily. Through the analyzes it was realized that the dam Tabatinga only has how to carry out the attenuation of floods through the regularization of the volume of waiting, with this there is a loss of approximately 56.5% on storage capacity of this dam, because for causing the attenuation effect of filled the shell of this dam has to remain more than 5m below the level of the sill, representing at least 50.582.927m3. The results obtained with the modeling represents a first step in the direction of improving the level of hydrological information about the behavior of the basins of the semiarid. In order to monitor quantitatively the hydrographic basin of the river Jundiaí will be necessary to install a rain gauge register, next to the Tabatinga dam and a pressure transducer, for regular measurements of flow in the reservoir of the dam. The climatological data will be collected in full automatic weather station installed in Agricultural School Jundiaí

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With an increasing number of mature fields, heavy oil recovery has performed one of the great challenges of the oil industry. The Brazilian Northeast, for example, has numerous heavy oil reservoirs are explored with the use of thermal methods. Among the types of methods used for heavy oil, there is the method of in-situ combustion, a technique in which heat is produced within the container, unlike the injection of heated fluid when the heat is generated at the surface and transported to the reservoir. In this type of process, it is common to use vertical wells as injectors and producers. However, methods which use horizontal wells like oil producers are increasingly studied because of greater contact area between the formation and combustion front. Thus, the main objective of this work was to study the different configurations of wells (CIS THAITM and CAGD) in the process of in-situ combustion in oil recovery using a semi-synthetic tank with Brazilian Northeast features. The method "toe-to-heel air injection" (THAITM) is a process of enhanced oil recovery, which is the integration of in-situ combustion with technological advances in drilling horizontal wells. This method uses horizontal wells such as oil producers, keeping vertical injection wells for injecting air. The oil drain process by differential gravitational assisted with combustion (CAGD) is an integrated, in this configuration the horizontal injector well is drilled at the top formation with a horizontal production well in the lower section. The simulations were performed in a commercial program of thermal processes, called "STARS" (Steam, Thermal, and Advanced Processes Reservoir Simulator), the company CMG (Computer Modelling Group). An analysis of the air flow injection was performed and it was found that each method had a maximum injection to the base model, a show that through this air injection limit was reduced cumulative production of oil. Analyses of operating parameters were used: injection flow, configuration and completion of wells. In the sensitivity analysis we found that the air injection flow showed greater influence on THAI method, since the CIS method the completion of the wells was the most influential parameter and CAGD configuration wells showed the greatest influence in the recovered fraction. The economic results have shown that the best case obtained in CAGD method because, despite having higher initial cost showed the best financial return compared to the best cases the CIS and THAI.

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With an increasing number of mature fields, heavy oil recovery has performed one of the great challenges of the oil industry. The Brazilian Northeast, for example, has numerous heavy oil reservoirs are explored with the use of thermal methods. Among the types of methods used for heavy oil, there is the method of in-situ combustion, a technique in which heat is produced within the container, unlike the injection of heated fluid when the heat is generated at the surface and transported to the reservoir. In this type of process, it is common to use vertical wells as injectors and producers. However, methods which use horizontal wells like oil producers are increasingly studied because of greater contact area between the formation and combustion front. Thus, the main objective of this work was to study the different configurations of wells (CIS THAITM and CAGD) in the process of in-situ combustion in oil recovery using a semi-synthetic tank with Brazilian Northeast features. The method "toe-to-heel air injection" (THAITM) is a process of enhanced oil recovery, which is the integration of in-situ combustion with technological advances in drilling horizontal wells. This method uses horizontal wells such as oil producers, keeping vertical injection wells for injecting air. The oil drain process by differential gravitational assisted with combustion (CAGD) is an integrated, in this configuration the horizontal injector well is drilled at the top formation with a horizontal production well in the lower section. The simulations were performed in a commercial program of thermal processes, called "STARS" (Steam, Thermal, and Advanced Processes Reservoir Simulator), the company CMG (Computer Modelling Group). An analysis of the air flow injection was performed and it was found that each method had a maximum injection to the base model, a show that through this air injection limit was reduced cumulative production of oil. Analyses of operating parameters were used: injection flow, configuration and completion of wells. In the sensitivity analysis we found that the air injection flow showed greater influence on THAI method, since the CIS method the completion of the wells was the most influential parameter and CAGD configuration wells showed the greatest influence in the recovered fraction. The economic results have shown that the best case obtained in CAGD method because, despite having higher initial cost showed the best financial return compared to the best cases the CIS and THAI.

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Electrical resistive heating (ERH) is a thermal method used to improve oil recovery. It can increase oil rate and oil recovery due to temperature increase caused by electrical current passage through oil zone. ERH has some advantage compared with well-known thermal methods such as continuous steam flood, presenting low-water production. This method can be applied to reservoirs with different characteristics and initial reservoir conditions. Commercial software was used to test several cases using a semi-synthetic homogeneous reservoir with some characteristics as found in northeast Brazilian basins. It was realized a sensitivity analysis of some reservoir parameters, such as: oil zone, aquifer presence, gas cap presence and oil saturation on oil recovery and energy consumption. Then it was tested several cases studying the electrical variables considered more important in the process, such as: voltage, electrical configurations and electrodes positions. Energy optimization by electrodes voltage levels changes and electrical settings modify the intensity and the electrical current distribution in oil zone and, consequently, their influences in reservoir temperature reached at some regions. Results show which reservoir parameters were significant in order to improve oil recovery and energy requirement in for each reservoir. Most significant parameters on oil recovery and electrical energy delivered were oil thickness, presence of aquifer, presence of gas cap, voltage, electrical configuration and electrodes positions. Factors such as: connate water, water salinity and relative permeability to water at irreducible oil saturation had low influence on oil recovery but had some influence in energy requirements. It was possible to optimize energy consumption and oil recovery by electrical variables. Energy requirements can decrease by changing electrodes voltages during the process. This application can be extended to heavy oil reservoirs of high depth, such as offshore fields, where nowadays it is not applicable any conventional thermal process such as steam flooding

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Water injection is the most widely used method for supplementary recovery in many oil fields due to various reasons, like the fact that water is an effective displacing agent of low viscosity oils, the water injection projects are relatively simple to establish and the water availability at a relatively low cost. For design of water injection projects is necessary to do reservoir studies in order to define the various parameters needed to increase the effectiveness of the method. For this kind of study can be used several mathematical models classified into two general categories: analytical or numerical. The present work aims to do a comparative analysis between the results presented by flow lines simulator and conventional finite differences simulator; both types of simulators are based on numerical methods designed to model light oil reservoirs subjected to water injection. Therefore, it was defined two reservoir models: the first one was a heterogeneous model whose petrophysical properties vary along the reservoir and the other one was created using average petrophysical properties obtained from the first model. Comparisons were done considering that the results of these two models were always in the same operational conditions. Then some rock and fluid parameters have been changed in both models and again the results were compared. From the factorial design, that was done to study the sensitivity analysis of reservoir parameters, a few cases were chosen to study the role of water injection rate and the vertical position of wells perforations in production forecast. It was observed that the results from the two simulators are quite similar in most of the cases; differences were found only in those cases where there was an increase in gas solubility ratio of the model. Thus, it was concluded that in flow simulation of reservoirs analogous of those now studied, mainly when the gas solubility ratio is low, the conventional finite differences simulator may be replaced by flow lines simulator the production forecast is compatible but the computational processing time is lower.

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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