Derivation of lithofacies from geophysical logs : a review of methods from manual picking to machine learning

The aims of this report are to document: 1. A range of methods that are currently used by the BGS stratigraphers to extract lithological information from geophysical logs (includes manual classification, cut-off analysis, mineral composition by linear inversion). 2. Alternative methods which, at present, are not routinely applied but are sufficiently practical and accessible that they could become important, including unsupervised (k-mean clustering) and supervised machine learning approaches. The report does not aim or claim to be a complete inventory of all possible methods to derive lithological information from geophysical logs. The authors welcome correspondence and information on any additional methods that are available or emerging.