A unique survey of recently developed machine learning approaches for an unbiased analysis of geophysical data from borehole logs Analysis and Interpretation of Borehole Logs: Data-driven Approaches shows how to exploit the advantages of algorithms in making log data interpretation at the same time both quicker and more reliable. The application of these AI-driven techniques to field data for extracting relevant information is demonstrated with the help of numerous examples. Tabulated data and representative illustrations aid in understanding the underlying theory and show how to arrive at a meaningful interpretation of well-logs. Throughout, the focus is on common tasks and challenges in the oil, gas and mining industries, such as the characterization of conventional and unconventional hydrocarbon-hosted sediments and depositional patterns of different stratigraphic units, lithology classification, assessment of hydrocarbon saturations, and the delineation of gas-hydrates. Analysis and Interpretation of Borehole Logs is a valuable resource for all geophysicists and engineers who are using well log data for the characterization of subsurface structures and deposits.