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Interdisciplinary Machine Learning in Science and Engineering ()

Siddharth Misra, Harold Vance Department of Petroleum Engineering
Applications of Machine Learning to Predict the Physical Properties of the Subsurface


Dr. Misra will present 3 case studies on the use of machine learning techniques for subsurface characterization. In the first case study, neural network models learn to predict NMR T2 distribution. In the second case study, simple data-driven models learn to predict compressional and shear travel-time measurements. In the third case study, machine learning was used to process dual-energy CT scan images to predict the geomechanical properties.