812 resultados para Modelagem trifásica
Resumo:
LINS, Filipe C. A. et al. Modelagem dinâmica e simulação computacional de poços de petróleo verticais e direcionais com elevação por bombeio mecânico. In: CONGRESSO BRASILEIRO DE PESQUISA E DESENVOLVIMENTO EM PETRÓLEO E GÁS, 5. 2009, Fortaleza, CE. Anais... Fortaleza: CBPDPetro, 2009.
Resumo:
SOUZA, Anderson A.S. ; MEDEIROS, Adelardo A. D. ; GONÇALVES, Luiz Marcos G. . Algorítmo de mapeamento usando modelagem probabilística. In: SIMPOSIO BRASILEIRO DE AUTOMAÇÃO INTELIGENTE, 2007, Natal. Anais... Natal, 2007.
Resumo:
Deep bed filtration occurs in several industrial and environmental processes like water filtration and soil contamination. In petroleum industry, deep bed filtration occurs near to injection wells during water injection, causing injectivity reduction. It also takes place during well drilling, sand production control, produced water disposal in aquifers, etc. The particle capture in porous media can be caused by different physical mechanisms (size exclusion, electrical forces, bridging, gravity, etc). A statistical model for filtration in porous media is proposed and analytical solutions for suspended and retained particles are derived. The model, which incorporates particle retention probability, is compared with the classical deep bed filtration model allowing a physical interpretation of the filtration coefficients. Comparison of the obtained analytical solutions for the proposed model with the classical model solutions allows concluding that the larger the particle capture probability, the larger the discrepancy between the proposed and the classical models
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Waterflooding is a technique largely applied in the oil industry. The injected water displaces oil to the producer wells and avoid reservoir pressure decline. However, suspended particles in the injected water may cause plugging of pore throats causing formation damage (permeability reduction) and injectivity decline during waterflooding. When injectivity decline occurs it is necessary to increase the injection pressure in order to maintain water flow injection. Therefore, a reliable prediction of injectivity decline is essential in waterflooding projects. In this dissertation, a simulator based on the traditional porous medium filtration model (including deep bed filtration and external filter cake formation) was developed and applied to predict injectivity decline in perforated wells (this prediction was made from history data). Experimental modeling and injectivity decline in open-hole wells is also discussed. The injectivity of modeling showed good agreement with field data, which can be used to support plan stimulation injection wells
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This work aims presenting the development of a model and computer simulation of a sucker rod pumping system. This system take into account the well geometry, the flow through the tubing, the dynamic behavior of the rod string and the use of a induction motor model. The rod string were modeled using concentrated parameters, allowing the use of ordinary differential equations systems to simulate it s behavior
Resumo:
Injectivity decline, which can be caused by particle retention, generally occurs during water injection or reinjection in oil fields. Several mechanisms, including straining, are responsible for particle retention and pore blocking causing formation damage and injectivity decline. Predicting formation damage and injectivity decline is essential in waterflooding projects. The Classic Model (CM), which incorporates filtration coefficients and formation damage functions, has been widely used to predict injectivity decline. However, various authors have reported significant discrepancies between Classical Model and experimental results, motivating the development of deep bed filtration models considering multiple particle retention mechanisms (Santos & Barros, 2010; SBM). In this dissertation, inverse problem solution was studied and a software for experimental data treatment was developed. Finally, experimental data were fitted using both the CM and SBM. The results showed that, depending on the formation damage function, the predictions for injectivity decline using CM and SBM models can be significantly different
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A legislação ambiental e os principais agentes que se relacionam com a empresa se constituem em fatores exógenos que não podem ser negligenciados ao formular-se e avaliar-se a política ambiental corporativa. As influências exógenas e seus efeitos sobre a gestão ambiental e o gerenciamento de projetos de exploração e produção (E&P) e, por essa via, sobre o desempenho ambiental, foram objetos de estudo desta tese. Embora o desempenho ambiental seja um assunto relevante, a pesquisa sobre esse tema ainda é escassa. Tal carência desponta ainda mais acentuada quando se aborda o desempenho ambiental de projetos na indústria de petróleo e gás. O principal objetivo deste estudo foi avaliar a relação entre a legislação ambiental vigente, as ações de órgãos reguladores, fornecedores, empresas terceirizadas e comunidades locais e o desempenho ambiental dos projetos de E&P na indústria de petróleo e gás e, também, analisar os efeitos do sistema de gestão ambiental e o gerenciamento dos projetos sobre tal desempenho. Na fase abdutiva, foi conduzido um estudo de caso com abordagem qualitativa em uma grande empresa brasileira do setor de petróleo e gás, na fase dedutiva, foi realizada uma pesquisa survey explanatória de corte transversal com abordagem quantitativa, incluindo 113 projetos de E&P de cinco unidades executoras da empresa. Foi formulado um modelo conceitual, com cinco construtos e sete hipóteses de pesquisa, representativo dos efeitos de fatores externos sobre o desempenho ambiental dos projetos de E&P. Os dados foram tratados aplicando a Análise Fatorial Exploratória e a Modelagem de Equações Estruturais com aplicação dos softwares IBM® SPSS® Statistics 20.0 e IBM® SPSS® Amos 18.0. O modelo de equações estruturais foi reespecificado e estimado utilizando o método de Máxima Verossimilhança e o procedimento bootstrap com 2000 reamostragens, até alcançar adequados valores dos índices de ajustamento. O modelo mostrou boa aderência às evidências empíricas, representando uma teoria explicativa dos fatores que influenciam o desempenho ambiental dos projetos de E&P na empresa estudada. As estatísticas descritivas apontaram adequado desempenho dos projetos de E&P com relação aos efluentes descartados, volume de água reutilizada, redução de resíduos e práticas de reciclagem. Identificou-se que projetos de maior porte alcançam melhor desempenho ambiental em relação aos de menor tamanho. Não foram achadas diferenças significativas entre os desempenhos de projetos executados por unidades operacionais distintas. Os resultados da modelagem indicaram que nem a legislação ambiental, nem os agentes externos exercem influência significativa sobre a sistemática da gestão dos projetos de E&P. Os agentes externos atuam sobre a gestão ambiental da empresa exercitando capacidades colaborativas, obstrutivas e propositivas. A legislação ambiental é percebida como entrave ao desenvolvimento dos projetos ao longo de seu ciclo de vida, principalmente, pelas deficiências dos órgãos ambientais. Identificou-se que o sistema de gestão ambiental influencia diretamente o Programa de Desenvolvimento e Execução de Projetos de E&P, que, por sua vez, provoca efeitos diretos e indiretos sobre o desempenho ambiental. Finalmente, comprovou-se que o Sistema de Gestão Ambiental da empresa é determinante para o desempenho ambiental dos projetos de E&P, tanto pelos seus efeitos diretos, como pelos indiretos, estes últimos mediados pela sistemática de gestão dos projetos de E&P
Resumo:
Discrepancies between classical model predictions and experimental data for deep bed filtration have been reported by various authors. In order to understand these discrepancies, an analytic continuum model for deep bed filtration is proposed. In this model, a filter coefficient is attributed to each distinct retention mechanism (straining, diffusion, gravity interception, etc.). It was shown that these coefficients generally cannot be merged into an effective filter coefficient, as considered in the classical model. Furthermore, the derived analytic solutions for the proposed model were applied for fitting experimental data, and a very good agreement between experimental data and proposed model predictions were obtained. Comparison of the obtained results with empirical correlations allowed identifying the dominant retention mechanisms. In addition, it was shown that the larger the ratio of particle to pore sizes, the more intensive the straining mechanism and the larger the discrepancies between experimental data and classical model predictions. The classical model and proposed model were compared via statistical analysis. The obtained p values allow concluding that the proposed model should be preferred especially when straining plays an important role. In addition, deep bed filtration with finite retention capacity was studied. This work also involves the study of filtration of particles through porous media with a finite capacity of filtration. It was observed, in this case, that is necessary to consider changes in the boundary conditions through time evolution. It was obtained a solution for such a model using different functions of filtration coefficients. Besides that, it was shown how to build a solution for any filtration coefficient. It was seen that, even considering the same filtration coefficient, the classic model and the one here propposed, show different predictions for the concentration of particles retained in the porous media and for the suspended particles at the exit of the media
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Knowledge of the native prokaryotes in hazardous locations favors the application of biotechnology for bioremediation. Independent strategies for cultivation and metagenomics contribute to further microbiological knowledge, enabling studies with non-cultivable about the "native microbiological status and its potential role in bioremediation, for example, of polycyclic aromatic hydrocarbons (HPA's). Considering the biome mangrove interface fragile and critical bordering the ocean, this study characterizes the native microbiota mangrove potential biodegradability of HPA's using a biomarker for molecular detection and assessment of bacterial diversity by PCR in areas under the influence of oil companies in the Basin Petroleum Geology Potiguar (BPP). We chose PcaF, a metabolic enzyme, to be the molecular biomarker in a PCR-DGGE detection of prokaryotes that degrade HPA s. The PCR-DGGE fingerprints obtained from Paracuru-CE, Fortim-CE and Areia Branca-RN samples revealed the occurrence of fluctuations of microbial communities according to the sampling periods and in response to the impact of oil. In the analysis of microbial communities interference of the oil industry, in Areia Branca-RN and Paracuru-CE was observed that oil is a determinant of microbial diversity. Fortim-CE probably has no direct influence with the oil activity. In order to obtain data for better understanding the transport and biodegradation of HPA's, there were conducted in silico studies with modeling and simulation from obtaining 3-D models of proteins involved in the degradation of phenanthrene in the transport of HPA's and also getting the 3-D model of the enzyme PcaF used as molecular marker in this study. Were realized docking studies with substrates and products to a better understanding about the transport mechanism and catalysis of HPA s