1. A method of automatically interpreting well log data indicative of physical attributes of a portion of a subterranean formation comprising: obtaining training data comprising well logs including facies classification information for at least a portion of the well logs; dividing the training data into two subsets, a training set and a cross-validation set; using an automated supervised learning facies identification method to determine a preliminary identification of facies in the subterranean formation based on the training set; calculating a confusion matrix for the supervised learning facies identification method by comparing predicted and observed facies for the cross-validation set; calculating a facies transition matrix characterizing changes between contiguous facies; using the preliminary identification, the facies transition matrix, and the confusion matrix, to iteratively calculate updated facies identifications, wherein the facies identifications are used for selection of a location for drilling in the subterranean formation for hydrocarbon resources.