Abstract

The oil production process is highly complex and requires the combination of several disciplines and technological tools for its management. System integration and the automation of the workflows required to develop oil production operations are two main problems nowadays at the oil and gas production industry. This work approaches these problems through the implementation of distributed artificial intelligence architecture, designed for the automated production management. The architecture comprises a standardized schema to access information sources, a production ontological framework and an intelligent workflow mechanism based on multi-agent systems and electronic institution. Our architecture present several novelties: the incorporation of the semantic integration, the extension of the agents theory through the electronic institutions paradigm to solve the real-time decision problems typical in the industry, the Holon-Agent hybrid model used to make more feasible its implementation, among others. An oil production management case study is presented in order to demonstrate the applicability of the proposed architecture.

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