Implementation and Interpretation of Machine and Deep Learning to Applied Subsurface Geological Problems (eBook)

1. Regression models to estimate total organic carbon (TOC) from well-log data2. Predicting brittleness indexes in tight formation sequences3. Classifying lithofacies in clastic, carbonate, and mixed reservoir sequences4. Permeability and water saturation distributions in complex reservoirs5. Trapping mechanisms in potential sub-surface carbon storage reservoirs6. The accurate picking of formation tops in field development wells7. Assessing formation loss of circulation risks with mud-log datasets8. Delineating fracture densities and apertures using well-log image data9. Determining reservoir microfacies using photomicrograph and computed tomography image data10. Characterizing coal-bed methane reservoirs with well-log datasets