Carregamentos aleatórios no dimensionamento probabilístico de revestimentos de poços de petróleo
Ano de defesa: | 2017 |
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Autor(a) principal: | |
Orientador(a): | |
Banca de defesa: | |
Tipo de documento: | Dissertação |
Tipo de acesso: | Acesso aberto |
Idioma: | por |
Instituição de defesa: |
Universidade Federal do Rio de Janeiro
Brasil Instituto Alberto Luiz Coimbra de Pós-Graduação e Pesquisa de Engenharia Programa de Pós-Graduação em Engenharia Civil UFRJ |
Programa de Pós-Graduação: |
Não Informado pela instituição
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Departamento: |
Não Informado pela instituição
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País: |
Não Informado pela instituição
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Palavras-chave em Português: | |
Link de acesso: | http://hdl.handle.net/11422/9803 |
Resumo: | The use of safety factors, currently standard practice in the industry, stems from the uncertainty that surrounds the casing design process. However, the WSD approach doesn’t formally quantify the risk associated with each design. As such, it isn’t equipped to compare two different designs, neither from a risk perspective nor from a cost perspective. This dissertation develops an RBD methodology to calculate a casing string’s probability of failure using random resistance and load models. The largest advantage to the RBD approach is the ease of risk tolerance calibration, which decision makers can adjust to reflect their own risk aversion. A FORM-based model of normalization of probability distributions was proposed and validated using Monte Carlo Simulation. It was shown that the probability of failure can differ from the deterministic probability of failure by a factor of more than 50. The analysis has also shown that the most important variables from a variability standpoint are the material tensile strenght, the pore pressure and the fracture gradient, cumulatively responsible for more than 90% of the observed variability. On the other hand, the joint’s external diameter and wall thickness, as well as the weight of the reservoir fluid and the position of the top of cement column, are the least important, accounting for less than 0,3% of the observed variability. |