Geovisualization for Association Rule Mining in CHOPS Well Data

Date
2015-09-25
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Abstract
Association 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.
Description
Keywords
Artificial Intelligence, Computer Science, Engineering--Petroleum
Citation
Sun, X. (2015). Geovisualization for Association Rule Mining in CHOPS Well Data (Master's thesis, University of Calgary, Calgary, Canada). Retrieved from https://prism.ucalgary.ca. doi:10.11575/PRISM/26297