Parceria Brasil - China: a questão do petróleo

Pós-graduação em Relações Internacionais (UNESP - UNICAMP - PUC-SP) - FFC

Estudo da cadeia petrolífera no Brasil: uma contextualização das tendências da indústria nacional e das relevâncias do PRH48

In the past few years, the Brazilian oil and gas sector had a considered growth, gaining enough relevance at international level, and being extremely important for the Brazilian socioeconomic development. However, the sector is still limited due to technical deficiencies. This work aims to conduct a current study, comprehending the entire oil chain, since it is possible to mention the Brazilian market updates on this context. To support this study, the historical development of the Brazilian petroleum industry was presented and the main stages of the production process were exposed with an emphasis on exploration and production phases. The new technologies developed for deepwater extractions, such as the pre-salt regions, were also discussed and, in the end, the relation of this growing market with the opportunities of the Human Resources Program of n. 48 was highlighted. This program identifies the market's actual needs and it's scarce's areas with the purpose of building capacity and qualified workforces, since it is also aimed, in a national level, a self-sufficient human resources for the sector

A genetic neuro-model reference adaptive controller for petroleum wells drilling operations

Motivated by rising drilling operation costs, the oil industry has shown a trend towards real-time measurements and control. In this scenario, drilling control becomes a challenging problem for the industry, especially due to the difficulty associated to parameters modeling. One of the drill-bit performance evaluators, the Rate of Penetration (ROP), has been used in the literature as a drilling control parameter. However, the relationships between the operational variables affecting the ROP are complex and not easily modeled. This work presents a neuro-genetic adaptive controller to treat this problem. It is based on the Auto-Regressive with Extra Input Signals model, or ARX model, to accomplish the system identification and on a Genetic Algorithm (GA) to provide a robust control for the ROP. Results of simulations run over a real offshore oil field data, consisted of seven wells drilled with equal diameter bits, are provided. © 2006 IEEE.