Uma aplicação da apredizagem por reforço na otimização da produção em um campo de petróleo

The objective of reservoir engineering is to manage fields of oil production in order to maximize the production of hydrocarbons according to economic and physical restrictions. The deciding of a production strategy is a complex activity involving several variables in the process. Thus, a smart system, which assists in the optimization of the options for developing of the field, is very useful in day-to-day of reservoir engineers. This paper proposes the development of an intelligent system to aid decision making, regarding the optimization of strategies of production in oil fields. The intelligence of this system will be implemented through the use of the technique of reinforcement learning, which is presented as a powerful tool in problems of multi-stage decision. The proposed system will allow the specialist to obtain, in time, a great alternative (or near-optimal) for the development of an oil field known

Análise de confiabilidade de uma bomba centrífuga: aplicação na injeção de água para recuperação de petróleo

The oil industry`s need to produce with maximum efficiency, not to mention the safety and the environment aspects, encourages the optimization of processes. It makes them look for a level of excellence in acquisition of equipment, ensuring the quality without prejudice security of facilities and peoples. Knowing the reliability of equipment and that this stands for a system is fundamental to the production strategy to seeks the maximum return on investment. The reliability analysis techniques have been increasingly applied in the industry as strategy for predicting failures likelihood ensuring the integrity of processes. Some reliability theories underlie the decisions to use stochastic calculations to estimate equipment failure. This dissertation proposes two techniques associating qualitative (through expertise opinion) and quantitative data (European North Sea oil companies fault database, Ored) applied on centrifugal pump to water injection system for secondary oil recovery on two scenarios. The data were processed in reliability commercial software. As a result of hybridization, it was possible to determine the pump life cycle and what impact on production if it fails. The technique guides the best maintenance policy - important tool for strategic decisions on asset management.

Uma aplicação da apredizagem por reforço na otimização da produção em um campo de petróleo

The objective of reservoir engineering is to manage fields of oil production in order to maximize the production of hydrocarbons according to economic and physical restrictions. The deciding of a production strategy is a complex activity involving several variables in the process. Thus, a smart system, which assists in the optimization of the options for developing of the field, is very useful in day-to-day of reservoir engineers. This paper proposes the development of an intelligent system to aid decision making, regarding the optimization of strategies of production in oil fields. The intelligence of this system will be implemented through the use of the technique of reinforcement learning, which is presented as a powerful tool in problems of multi-stage decision. The proposed system will allow the specialist to obtain, in time, a great alternative (or near-optimal) for the development of an oil field known