Wang, XinWei, Bingjie2016-06-292016-06-2920162016Wei, B. (2016). Well Production Prediction and Visualization Using Data Mining and Web GIS (Master's thesis, University of Calgary, Calgary, Canada). Retrieved from https://prism.ucalgary.ca. doi:10.11575/PRISM/28686http://hdl.handle.net/11023/3088Massive data sets have been accumulated in the oil and gas industry. As strategic assets, voluminous data of different data types should be leveraged and turned into information for agile and accurate decision-making. Three oil and gas data-related studies are covered in this thesis. Firstly, a data-driven model is proposed for predicting well production using time-series production data from analogous and adjacent wells. Secondly, interactive visualization tools are designed and implemented for oil and gas spatial and temporal datasets, following an “Overview first, zoom and filter, then details-on-demand” guideline (Shneiderman, 1996) in order to maximize information delivery in single displays. Thirdly, a web-based Geographic Information System (GIS) application is designed and implemented for a Steam Assisted Gravity Drainage (SAGD) dataset to provide users convenient access to public and proprietary SAGD data, as well as some data analysis and visualization functions.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.Engineering--PetroleumGeotechnologyWeb GISData visualizationData driven modelOil and gas production predictionmaster thesis10.11575/PRISM/28686