Method for predicting geological features from images of geologic cores using a deep learning segmentation process

A method for predicting an occurrence of a geological feature in a geologic core image, the method comprising the steps of:

• (a) providing a trained backpropagation-enabled segmentation process, wherein a backpropagation-enabled segmentation process trained by
• i. inputting a training geologic core image with an image input dimension of at least two into a backpropagation-enabled segmentation process;
• ii. inputting a set of labels of geological features associated with the training geologic core image into the backpropagation-enabled segmentation process, wherein the set of labels has a label input dimension equal to or less than the image input dimension;
• and
• iii. iteratively computing a prediction of the probability of occurrence of the geological feature for the training geologic core image and adjusting of the parameters in the backpropagation-enabled segmentation model, thereby producing the trained backpropagation-enabled segmentation process;
• and
• (b) using the trained backpropagation-enabled segmentation process to predict the occurrence of the geological feature in a non-training geologic core image of input dimension of at least two.