Abstract
Oil well drilling is a complex process which frequently is leading to operational problems. The process generates huge amounts of data. In order to deal with the complexity of the problems addressed, and the large number of parameters involved, our approach extends a pure case-based reasoning method with reasoning within a model of general domain knowledge. The general knowledge makes the system less vulnerable for syntactical variations that do not reflect semantically differences, by serving as explanatory supportfor case retrieval and reuse. A tool, called TrollCreek, has been developed. It is shown how the combined reasoning method enables focused decision support for fault diagnosis and prediction of potential unwanted events in this domain.
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Skalle, P., Aamodt, A. (2005). Knowledge-Based Decision Support in Oil Well Drilling. In: Shi, Z., He, Q. (eds) Intelligent Information Processing II. IIP 2004. IFIP International Federation for Information Processing, vol 163. Springer, Boston, MA. https://doi.org/10.1007/0-387-23152-8_56
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DOI: https://doi.org/10.1007/0-387-23152-8_56
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