Wang, XinSun, Xiaodong2015-09-252015-11-202015-09-252015http://hdl.handle.net/11023/2505Association rule mining has recently been applied to improve the oil recovery of CHOPS by discovering the association rules between reservoir properties and oil production from CHOPS well data. However, it leaves reservoir engineers with big challenging tasks to find interesting rules, understand the rules by the distribution patterns of relevant wells and make subsequent predictions by the application areas of the rules. In this thesis, three kinds of rule filters are developed to find out the interesting rules. Moreover, point-based and surface-based geovisualization methods are proposed to display the distribution patterns of relevant wells, build and represent potentially applicable areas for the rules on the map. A system prototype, containing association rule mining with filters, geovisualization functions, is developed. A case study has been carried out on a real CHOPS well dataset in western Alberta, Canada. The findings in the case study illustrate the feasibility of the proposed methods.engUniversity of Calgary graduate students retain copyright ownership and moral rights for their thesis. You may use this material in any way that is permitted by the Copyright Act or through licensing that has been assigned to the document. For uses that are not allowable under copyright legislation or licensing, you are required to seek permission.Artificial IntelligenceComputer ScienceEngineering--PetroleumgeovisualizationCHOPS well dataAssociation rule miningdata mining for oil and gasmaster thesis10.11575/PRISM/26297