Advances in Subsurface Data Analytics

Data Analytics in Energy Resources Exploration brings together the fundamentals of popular and emerging machine learning algorithms with their applications in subsurface analysis, including geology, geophysics, and petrophysics. Each chapter focuses on one machine learning algorithm and includes detailed workflow, applications, and case studies. In addition, some of the chapters contain a comparison of an algorithm with respect to others to better equip the readers with different strategies to implement automated workflows for subsurface analysis. Data Analytics in Energy Resources Exploration will help researchers in academia and professional geoscientists working in the oil and gas industry to understand and appreciate the existence of several machine learning and deep learning models, how to optimize their performance, and their detailed applications in geosciences by bringing together several contributions in a single volume. Covers fundamentals of simple machine learning and emerging deep learning algorithms written by practitioners in academia and industry Presents detailed case studies of individual machine learning algorithms around the world, including those used for conventional and unconventional reservoirs Offers an analysis of future trends