Automatic Determination of Lithology From Well Logs

Abstract

Summary: A procedure combining modern wireline measurements with a lithofacies data base has been developed to produce an automatic lithologic description of the formations crossed by a well. The database lithofacies are defined from petrographic knowledge and translated in terms of log responses. The assignment of depth levels to a lithofacies is done with the data base and with a discriminant function (Bayesian decision rule). External knowledge can be taken into account by use of artificial intelligence methods. A confidence factor is produced for each result. Logs currently in the data base are the density, neutron, sonic transit time, gamma ray, photoelectric cross section, and concentrations of thorium, potassium, and uranium. Major lithofacies groups represented in the data base include sandstones, limestones, dolomites, shales, coals, and evaporites. These are subdivided by introducing cement and special minerals and by considering porosity ranges. The construction of the data base is a critical step. It is largely empirical and requires careful calibration against intervals with well-known lithologies (e.g., from cores). The data base can be tuned to local conditions. The procedure has been tested in several environments and compared with cores and mud log descriptions. A detailed lithologic column can be produced at the wellsite and used in decision making. The results can also serve as input for further geologic studies of facies and sequences or for quantitative evaluation of formations.