Study on Intelligent Monitoring and Controlling System in Oil Drilling Optimization

Abstract:

With the increase of drilling data scale, real-time optimal drilling engineering seems to be difficult only by manual or traditional computer data, numerical, even simple knowledge processing. In such a case, Integration knowledge system is proven to be helpful in optimal drilling and improvement of drilling efficiency. A integrated and shared platform is built up about multi-source heterogeneous drilling data and information, to establish the conditions of intelligent reasoning; A multi-hierarchy and multi-modality knowledge model is created based on Ontology, they can define the performance, structure, function, axiom and case of glossary in oil drilling optimization domain, and integrate drilling optimization requirement, static and dynamic drilling data and Problem-Solving Method(PSM)；An evolutionary uncertainty reasoning mechanism is built up to integrate rule and case reasoning based on Bayesian Network; An integrated knowledge system is exploited based on the knowledge model of and its reasoning. By application in oil field, the results show its intelligent level and reliability improve clearly, and prove that optimal drilling knowledge model created based on ontology can meet the neets of share and re-usability of knowledge in a special field, and the model has wide application prospects.

• Periodical: Applied Mechanics and Materials (Volumes 263-266)
• Pages: 1319-1322
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.263-266.1319
• Online since: December 2012
• Authors: Jian Ming Guo, Zheng Wang, Yan Ping Wang
• Keywords: Intelligent Monitoring and Controlling, Knowledge Model, Oil Drilling Engineering

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