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Plan recommendation for well engineering.

Thomson, Richard; Massie, Stewart; Craw, Susan; Ahriz, Hatem; Mills, Ian

Authors

Richard Thomson

Hatem Ahriz

Ian Mills



Contributors

Kishan G. Mehrotra
Editor

Chilukuri K. Mohan
Editor

Jae C. Oh
Editor

Pramod K. Varshney
Editor

Moonis Ali
Editor

Abstract

Good project planning provides the basis for successful offshore well drilling projects. In this domain, planning occurs in two phases: an onshore phase develops a project plan; and an offshore phase implements the plan and tracks progress. The Performance Tracker applies a case-based reasoning approach to support the reuse of project plans. Cases comprise problem parts that store project initiation data, and solution parts that record the tasks and subtasks of actual plans. An initial evaluation shows that nearest neighbour retrieval identifies projects in which the retrieved tasks and subtasks are relevant for the new project. The Performance Tracker can be viewed as a recommender system in which recommendations are plans. Thus the data that is routinely captured as part of the performance tracking during offshore implementation is utilised as experiences. This conference was held in Syracuse, NY.

Start Date Jun 28, 2011
Publication Date Dec 31, 2011
Publisher Springer (part of Springer Nature)
Pages 436-445
Series Title Lecture notes in computer science
Series Number 6704
ISBN 9783642218262
Institution Citation THOMSON, R., MASSIE, S., CRAW, S., AHRIZ, H. and MILLS, I. 2011. Plan recommendation for well engineering. In Mehrotra, K.G., Mohan, C.K., Oh, J.C., Varshney, P.K. and Ali, M. (eds.) Modern approaches in applied intelligence: proceedings of the 24th International conference on industrial, engineering and other applications of applied intelligent systems (IEA/AIE 2011), 28 June - 1 July 2011, Syracuse, USA. Lecture notes in computer science, 6704. Berlin: Springer [online], part II, pages 436-445. Available from: https://doi.org/10.1007/978-3-642-21827-9_45
DOI https://doi.org/10.1007/978-3-642-21827-9_45
Keywords Case based reasoning; Recommender systems

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