Well Logging in Fractured Media

This chapter provides an overview of well logging in carbonate formations from the perspective of CO2 sequestration projects. The chapter begins with a summary of the various types of logs such as gamma ray, neutron porosity, bulk density, resistivity, photoelectric, sonic, pulsed neutron capture, nuclear magnetic resonance, image log, and elemental spectroscopy. Next comes a discussion of analyses performed with these log outputs for characterizing attributes such as: facies, shale volume, porosity, permeability, fluid saturation, geomechanical properties, and fractures and vugs. This is followed by best practices for log interpretation, including data QA/QC and a typical workflow. A case study on well-log interpretation is then presented using two fields from the Northern Michigan Pinnacle reef trend. This example covers data acquisition, porosity analysis, integration of core and log data, facies analysis, and fractures and vugs. The application of machine learning to well logging data is presented next, beginning with a discussion of machine learning basics, which is followed by an example application for vug characterization. Collectively, these topics cover the most common set of conventional and emerging techniques that are relevant in the utilization of well logs for characterization of carbonate formations.