期刊
NEUROCOMPUTING
卷 73, 期 10-12, 页码 1987-1992出版社
ELSEVIER
DOI: 10.1016/j.neucom.2009.10.020
关键词
Fault detection; Oil; Integrated operations; Time series; Intelligent systems
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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