Predictive Analytics Bring New Capabilities To Shale Development HOUSTON-Predictive analytics are used in many fields as a forecasting tool to speed decision-making and ramp performance, making use of vast amounts of historical and available data. Physical models, machine learning methods, artificial intelligence algorithms and more traditional statistical approaches are used to make more accurate predictions. Predictive analytics have been successfully applied to unconventional resource plays to search for meaningful associations between production data and petrotechnical data where relevant associations can be used to predict sweet spots and determine optimum well spacings or lateral lengths. These methods apply proven statistical methods to search for these associations. Several innovative predictive methods are applicable for use by geoscientists, as well as reservoir, drilling and production engineers. These techniques include physics-based forecasting, "deep learning" and other novel machine learning methods for enriching the models. The resulting models and outcomes can be used for prospecting, well planning, geosteering and anticipatory production optimization. They are potential game changers for shale players. 40 THE AMERICAN OIL & GAS REPORTER By Duane Dopkin, Indy Chakrabarti and Zvi Koren