Journal
NEUROCOMPUTING
Volume 73, Issue 10-12, Pages 1987-1992Publisher
ELSEVIER
DOI: 10.1016/j.neucom.2009.10.020
Keywords
Fault detection; Oil; Integrated operations; Time series; Intelligent systems
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Data-centric methods like soft computing and machine learning have gained greater interest and acceptance in the oil and gas industry in recent years. We give an overview of the opportunities and challenges facing applied time series prediction in this domain, with a focus on fault prediction. In particular, we argue that the physical processes and hierarchies of information flow in the industry strongly determine the choice of soft computing or machine learning methods. (C) 2010 Elsevier B.V. All rights reserved.
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