The E&P community, both in the industry and academia, is painfully aware of the challenges and complexity of performing seismic interpretation and reservoir characterization in increasingly larger, more intricate, and more heterogeneous data sets. This increase in size is coupled with an emphasis on more quantitative methods in frontier exploration and mature basins. Unconventional reservoirs present an even higher level of challenges and opportunities due to the large number of wells available in resource plays. Continuous advances in the areas of pattern recognition and machine learning such as big data analytics, semisupervised learning, functional data analysis, regression techniques, multidimensional scaling,...
Introduction to special section: Pattern recognition and machine learning
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Vikram Jayaram, Per Age Avseth, Kostia Azbel, Theirry Coléou, Deepak Devegowda, Paul de Groot, Dengliang Gao, Kurt Marfurt, Marcilio Matos, Tapan Mukerji, Manuel Poupon, Atish Roy, Brian Russell, Brad Wallet, Vikas Kumar; Introduction to special section: Pattern recognition and machine learning. Interpretation 2015;; 3 (4): SAEi–SAEii. doi: https://doi.org/10.1190/INT2015-0918-SPSEINTRO.1
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