Abstract
A system that applies a method of knowledge-intensive case-based reasoning, for repair and prevention of unwanted events in the domain of offshore oil well drilling, has been developed in cooperation with an oil company. From several reoccurring problems during oil well drilling the problem of “lost circulation”, i.e. loss of circulating drilling fluid into the geological formation was picked out as a pilot problem. An extensive general knowledge model was developed for the domain of oil well drilling. About fifty different cases were created on the basis of information from one North Sea operator. When the completed CBR-system was tested against a new case, five cases with descending similarity were selected by the tool. In an informal evaluation, the two best fitting cases proved to give the operator valuable advise on how to go about solving the new case.
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Skalle, P., Sveen, J., Aamodt, A. (2000). Improved Efficiency of Oil Well Drilling through Case Based Reasoning. In: Mizoguchi, R., Slaney, J. (eds) PRICAI 2000 Topics in Artificial Intelligence. PRICAI 2000. Lecture Notes in Computer Science(), vol 1886. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-44533-1_71
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DOI: https://doi.org/10.1007/3-540-44533-1_71
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