Abstract: An automated method for categorising and describing rock samples includes: (i) capturing images of samples to generate image data; (ii) classifying the samples by applying convolutional neural network processing to the image data to identify attributes of the samples; (iii) extracting, using a module based on a trained convolution deconvolution neural network, salient features from the attributes to generate salient feature data; (iv) applying, using a module based on a trained recurrent neural network generated from supervised learning, semantic text processing to the salient feature data to generate sample text data indicative of the attributes; (v) storing the sample text data; (vi) searching an image database for categorised images that are similar to the captured images; and (vii) generating output data dependent upon a degree of similarity between the sample text data and the database text data to indicate petrophysical properties of the rocks.