Mahinpey, NaderWang, XinWang, Xi2016-01-152016-01-152016-01-152016Wang, X. (2016). Discovering Relationships between Reservoir Properties and Production Data for CHOPS Using Data Mining Methods (Master's thesis, University of Calgary, Calgary, Canada). Retrieved from https://prism.ucalgary.ca. doi:10.11575/PRISM/25718http://hdl.handle.net/11023/2752Cold Heavy Oil Production with Sand (CHOPS) produces sand, and greatly contributes to primary oil recovery. It’s generally believed that wormholes, resulting from sand flow, enhance oil recovery in this process. However, due to complexity and variability, it’s difficult for wormhole models to precisely describe how wormholes develop within the formation. In this study, we regard wormholes as an integral black box. We apply data mining methods to explore how the reservoir attributes influence the CHOPS wells production. Gain ratio is used to rank and select the most important attributes for oil production. For overall oil production performance, cumulative porosity, cumulative oil saturation, effective thickness, and average shale content are the most important and relevant attributes. Decision trees constructed by C4.5 algorithm provide details of how to classify oil production instances according to reservoir attributes. All the correctly classified rates are over 55%, which is reliable accuracy in our results.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.Computer ScienceEngineering--PetroleumCHOPSWormholesData Mining MethodsWekaGain Ratiomaster thesis10.11575/PRISM/25718