Energy Analytics Learning Machine (or EALM) system is a machine learning based, “brutally empirical” analysis system for use in optimizing the payout from one or more energy sources. EALM system optimizes exploration, production, distribution and/or consumption of an energy source while minimizing costs to the producer, transporter, refiner and/or consumer. Normalized data are processed to determine clusters of correlation in multi-dimensional space to identify a machine learned ranking of importance weights for each attribute. Predictive and prescriptive optimization on the normalized energy data is performed utilizing unique combinations of machine learning and statistical algorithm ensembles. The unstructured textual energy data are classified to correlate with optimal production to capture the dynamics of one or more energy sources of physically real or theoretically calculated systems to provide categorization results from labeled data sets to identify patterns.