Modelo de otimização de cronograma para alocação de recursos críticos na exploração e produção de petróleo :uma aplicação do modelo de Análise Hierárquica Coppe Cosenza(MAH)

• Ano de defesa: 2017
• Autor(a) principal: Rodrigues, Paulo Emílio Paes
• Tipo de documento: Tese
• 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 de Produção; UFRJ
• Palavras-chave em Português: Engenharia de Produção; Óleo e gás; Lógica fuzzy; CNPQ::ENGENHARIAS::ENGENHARIA DE PRODUCAO
• Link de acesso: http://hdl.handle.net/11422/10115

The energy market, more specifically oil and gas, is one of the great drivers of the economy in both the macroeconomic and the microeconomic scenario. Oil production has risen sharply in recent years, and the outlook for the coming years with the discovery of the pre-salt layer is an increase in production, which will boost the country’s position as one of the world’s leading oil producers. For this prognosis to be confirmed, oil companies have been investing heavily in research on new technologies in the exploration and production of oil. One area within this research is drilling for oil wells where optimization of well drilling can bring savings of several million in the total cost of the project, since the equipment involved is of high cost, as well as being a scarce resource And concurred. Today the allocation of special equipment considered critical in the drilling project is determined by deterministic mathematical models. In a real environment, variables do not have a deterministic behavior: calculations are usually based on imprecise, ambiguous and subjective variables, which means that planning of equipment allocation is not optimal. The present research aims to submit an equipment allocation model based on fuzzy logic with the application of the Coppe-Cosenza model, to the problem of Programming of Projects with Restriction of Resources, where the use of imprecise, subjective and Ambiguity allows planning of equipment allocation more appropriate to the problems faced.