Date of Graduation
Statler College of Engineering and Mineral Resources
Petroleum and Natural Gas Engineering
Shahab D. Mohaghegh.
Intelligent Production Data Analysis - IPDA, is a new methodology for Reservoir Characterization based only on monthly production rate data. This technique combines conventional methods of production data analysis (decline curve analysis, type curve matching and history matching) with intelligent systems. The study targets the validation of this methodology under a controlled environment, attempting three main objectives: Identifying Sweet Spots, Forecasting Reserves and recognizing under-performer wells.;The study investigates the behavior of five different reservoirs, modeled using a commercial simulator. The structure, parameters and heterogeneity of each configuration was inspired by existing formations. Records of production rate data were generated from the simulated fields (both single and multi-layer formations) and used as input to perform an "Intelligent Production Data Analysis".;The findings highlight strength of this technique in tracking the fluid movement in the reservoir as a function of time. Furthermore, this study identifies some limitations and circumstances under which the analysis may not result in correct recommendations.
Mata, Domingo A., "Validation of a new technique of production data analysis for single and multi-layer formations under controlled environment" (2007). Graduate Theses, Dissertations, and Problem Reports. 1834.