50 resultados para Mercado de trabalho - Modelos matemáticos
Resumo:
Water injection in oil reservoirs is a recovery technique widely used for oil recovery. However, the injected water contains suspended particles that can be trapped, causing formation damage and injectivity decline. In such cases, it is necessary to stimulate the damaged formation looking forward to restore the injectivity of the injection wells. Injectivity decline causes a major negative impact to the economy of oil production, which is why, it is important to foresee the injectivity behavior for a good waterflooding management project. Mathematical models for injectivity losses allow studying the effect of the injected water quality, also the well and formation characteristics. Therefore, a mathematical model of injectivity losses for perforated injection wells was developed. The scientific novelty of this work relates to the modeling and prediction of injectivity decline in perforated injection wells, considering deep filtration and the formation of external cake in spheroidal perforations. The classic modeling for deep filtration was rewritten using spheroidal coordinates. The solution to the concentration of suspended particles was obtained analytically and the concentration of the retained particles, which cause formation damage, was solved numerically. The acquisition of the solution to impedance assumed a constant injection rate and the modified Darcy´s Law, defined as being the inverse of the normalized injectivity by the inverse of the initial injectivity. Finally, classic linear flow injectivity tests were performed within Berea sandstone samples, and within perforated samples. The parameters of the model, filtration and formation damage coefficients, obtained from the data, were used to verify the proposed modeling. The simulations showed a good fit to the experimental data, it was observed that the ratio between the particle size and pore has a large influence on the behavior of injectivity decline.
Resumo:
GOMES, Z. B. ; LOURENÇO, André Luís Cabral de . Atuação do Estado como empregador de última Instância: uma proposta para eliminar o desemprego estrutural do Brasil. In: Encontro Nacional de Economia Política, 13. 2008, João Pessoa/PB. Anais... João Pessoa: ENEP, 2008.
Resumo:
The theoretical recital of the present study it is initiated of the evidence that the work occupies an important space in the man s life in way that the majority of the people works and passes great part of its time inside organizati ons. However, it is verified that the relation between man and work is becoming increasingly disagreement a time that the employees had started to complain work s routines, stress, not use all their potential and inadequate work s conditions. It can be observed by the way of Dejours (1994) studies. Thus, as contribution for the quality of work life s (QWL) studies the research developed here objectified to characterize the public employees quality of work life at EMATER -RN taking as reference an instrumen t of research synthesized from the typical academic literature of the subject. The synthesis of an ampler instrument is a necessity not taken care to the literature that treats on the subject but already perceived by some studies like Moraes et al (1990); Rodrigues (1989); Siqueira & Coleta (1989); Moraes et al (1992); Carvalho & Souza (2003); El -Aouar & Souza (2003) and Mourão, Kilimnick & Fernandes (2005); Adorno, Marques & Borges (2005) amongst others. These studies point out weak points of the existing models in the QWL s literature, as well as they recommend the elaboration of a model more flexible, that contemplates Brazilian cultural characteristics, and that contemplates the entire variable studied in the main existing models. For reach this objectiv e the adopted methodology was characterized as a case study with collected data in qualitative and quantitative way. Questionnaires and comments had been used as sources of evidences. These evidences had been tabulated through of statistical package SPSS ( Statistical Package for Social Science), in which the main technique of multivariate analysis used were the factorial analysis. As for the gotten results, it was verified the grouping of the quality of work life s indicators in 11 factors which are: Work s execution, Individual accomplishment, Work s equity, Relation individual and organization, Work s organization, Adequacy of the remuneration, Relation between head and subordinate, Effectiveness of the communication and the learning, Relation between work and personal life, Participation and Effectiveness of the work processes. Whatever to the characterization of the EMATER -RN s quality of work life it was clearly that to the measure that the satisfaction s evaluation with the QWL in the organization walks to intrinsic factors for extrinsic factors this level of satisfaction goes diminishing what points to the importance to improve these extrinsic factors in the institution. In summary it is possible to conclude that the organization studied has offered a significant set of referring variable to the quality of work life of the individual
Resumo:
Forecast is the basis for making strategic, tactical and operational business decisions. In financial economics, several techniques have been used to predict the behavior of assets over the past decades.Thus, there are several methods to assist in the task of time series forecasting, however, conventional modeling techniques such as statistical models and those based on theoretical mathematical models have produced unsatisfactory predictions, increasing the number of studies in more advanced methods of prediction. Among these, the Artificial Neural Networks (ANN) are a relatively new and promising method for predicting business that shows a technique that has caused much interest in the financial environment and has been used successfully in a wide variety of financial modeling systems applications, in many cases proving its superiority over the statistical models ARIMA-GARCH. In this context, this study aimed to examine whether the ANNs are a more appropriate method for predicting the behavior of Indices in Capital Markets than the traditional methods of time series analysis. For this purpose we developed an quantitative study, from financial economic indices, and developed two models of RNA-type feedfoward supervised learning, whose structures consisted of 20 data in the input layer, 90 neurons in one hidden layer and one given as the output layer (Ibovespa). These models used backpropagation, an input activation function based on the tangent sigmoid and a linear output function. Since the aim of analyzing the adherence of the Method of Artificial Neural Networks to carry out predictions of the Ibovespa, we chose to perform this analysis by comparing results between this and Time Series Predictive Model GARCH, developing a GARCH model (1.1).Once applied both methods (ANN and GARCH) we conducted the results' analysis by comparing the results of the forecast with the historical data and by studying the forecast errors by the MSE, RMSE, MAE, Standard Deviation, the Theil's U and forecasting encompassing tests. It was found that the models developed by means of ANNs had lower MSE, RMSE and MAE than the GARCH (1,1) model and Theil U test indicated that the three models have smaller errors than those of a naïve forecast. Although the ANN based on returns have lower precision indicator values than those of ANN based on prices, the forecast encompassing test rejected the hypothesis that this model is better than that, indicating that the ANN models have a similar level of accuracy . It was concluded that for the data series studied the ANN models show a more appropriate Ibovespa forecasting than the traditional models of time series, represented by the GARCH model
Resumo:
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.