Supporting codes, data, and outputs to identify a type of lithofacies from rock-core digital photographs and to classify the lithofacies from well-log data

This repository contains the codes and the data used in the study “Interpreting the Subsurface Lithofacies at High Lithological Resolution by Integrating Information from Well-log Data and Rock-core Digital Photographs”. The codes are used to identify the lithofacies type from rock-core digital photographs (clustering) and to predict the lithofacies from geophysical well-log data (classification). The lithofacies identification process, including feature extraction and clustering, was encoded by MATLAB, and the classification model was encoded by TensorFlow to construct a neural network-based classification model.