A Case Based System for Oil and Gas Well Design

Authors:
Simon Kravis;Rosemary Irrgang
Affiliations:
-;-
Venue:
IEA/AIE '02 Proceedings of the 15th international conference on Industrial and engineering applications of artificial intelligence and expert systems: developments in applied artificial intelligence
Year:
2002

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Abstract

A case base system for a complex problem like oil field design needs to be richer than the usual case based reasoning system. The system described in this paper contains large heterogeneous cases with metalevel knowledge. A multi level indexing scheme with both preallocated and dynamically computed indexing capability has been implemented. A user interface allows dynamic creation of similarity measures based on modelling of the user's intentions. Both user aiding and problem solution facilities are supported, a novel feature is that risk estimates are also provided. Performance testing indicates that the case base produces on average, better predictions for new well developments than company experts. Early versions of the system have been deployed into oil companies in 6 countries around the world and research is continuing on refining the system in response to industry feedback.