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Oilfield equipment's state diagnostics on the basis of data mining technologies

Authors: S.V. Kononov (PU SurgutASUneft, Surgutneftegaz OAO), Ya.S. Korovin, M.G. Tkachenko (Scientific research institute of multiprocessor computer systems, Southern Federal University)

Key words: data mining, diagnostics, forecasting, artificial neural networks,
oil production equipment.

The solution of the problem of oil-extracting production efficiency and safety raise by the information systems constructed on the Data mining technology basis application is offered. The description of new Database knowledge discovery methods, so as the oilfield equipment state diagnostics and forecasting methods is provided. The architecture and the main functionality of automated software system applied for oilfield objects state online monitoring, developed on new methods and algorithms basis, is described.

Key words: data mining, diagnostics, forecasting, artificial neural networks,
oil production equipment.

The solution of the problem of oil-extracting production efficiency and safety raise by the information systems constructed on the Data mining technology basis application is offered. The description of new Database knowledge discovery methods, so as the oilfield equipment state diagnostics and forecasting methods is provided. The architecture and the main functionality of automated software system applied for oilfield objects state online monitoring, developed on new methods and algorithms basis, is described.



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