Patent 11443149 was granted and assigned to Schlumberger on September, 2022 by the United States Patent and Trademark Office.
Apparatus and methods for ascribing one of multiple predetermined sub-classes to multiple pixels of an image of an unknown rock sample retrieved from a geological formation. The ascription utilizes a deep learning model trained with an annotated training dataset. The annotated training dataset includes multi-pixel images of known rock samples and, for each known rock sample image, which sub-class corresponds to at least a subset of pixels of that image. For each pixel of the unknown rock sample image having an ascribed sub-class, which one of predetermined meta-classes is associated with that pixel is derived based on the sub-class ascribed to that pixel. The meta-classes represent different predetermined rock types. At least one property of the formation is predicted utilizing the ascription-derived meta-classes, including which rock type(s) are present in the formation.