Primer on Machine Learning in Subsurface Geosciences

Dr. Shuvajit Bhattacharya is a researcher at the Bureau of Economic Geology, the University of Texas at Austin. He is an applied geophysicist/petrophysicist specializing in seismic interpretation, petrophysical modeling, machine learning, and integrated subsurface characterization. He uses advanced computational technologies to solve complex problems in geosciences, which have societal and economic impacts. Dr. Bhattacharya has completed several projects in diverse geologic settings in the US, Norway, Australia, South Africa, and India. He worked in both academia and industry. He has published and presented more than 50 technical articles in peer-reviewed journals and conferences. His current research focuses on the pressing issues and frontier technologies in energy exploration, development, and subsurface fluid storage (carbon, hydrogen, and wastewater). He completed his Ph.D. at West Virginia University and an M.Sc. at the Indian Institute of Technology Bombay.

• Introduction.- Brief Review of Statistical Measures.- Basic Steps in Machine Learning and Deep Learning Models.- Brief Review of Popular Machine Learning and Deep Learning Algorithms.- Applications of ML/DL in Geophysics and Petrophysics Domain.- Applications of ML/DL in Geology Domain.- Multi-scale Data Integration and Analytics.- The Road Ahead.