Abstract: A method for generating a depth log of cuttings obtained during a subterranean drilling operation includes acquiring images of the cuttings and labeling the images with a lagged depth at a rig site; generating a clustering of lithology types in the acquired images at a rig the site; transferring the images and the clustering of lithology types from the rig site to an offsite location; evaluating the images and the clustering of lithology types to label each of the lithology types at the offsite location; and generating a description and/or depth log of the labeled lithology types at the offsite location.

Abstract: Systems and methods are provided for analyzing sample images, such as for rock particles obtained during drilling of a geologic formation. The system and techniques utilize a Large Foundation Model (LFM) in the segmentation of rock particles. The LFM can receive an image (or image data) of rock particles as an input and generates segmentation of the image at a pixel level (i.e., each pixel of the image is classified) as a segmented image. Additionally, active annotation can be provided in conjunction with a graphics user interface (GUI) to allows for user interaction with images as well as selective segmentation of the images.

Abstract: Systems and methods are provided for imaging drill cuttings, which employ a UV source including a UV LED, which is configured to illuminate a sample volume with UV radiation that interacts with oil-bearing cuttings to cause fluorescence emission. A camera system is configured to capture at least one image of the cuttings based on fluorescence emission. In another aspect, methods are provided for characterizing oil content in drill cuttings that involve capturing at least one WE image of the cuttings illuminated by white light, capturing at least one UV image of the cuttings based on fluorescence emission from UV radiation, processing the at least one WE image to determine a first pixel count for all cuttings, processing the at least one UV image to determine a second pixel count for oil-bearing cuttings, and determining a parameter representing oil content of the cuttings based on the first and second pixel counts.

Abstract: A method for evaluating drill cuttings includes acquiring a first digital image and processing the first digital image with a trained neural network (NN) to generate a first segmented image including a plurality of labeled segments in which at least one label includes a lithology type. The segmented image and the acquired first digital image are processed to retrain the NN. A second digital image is then be processed with the retrained NN to generate a second segmented image including a plurality of labeled segments in which at least one label includes a lithology type.

Abstract: 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.

Abstract: 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.

Abstract: A method for determining a property of a geological formation based on an optical image of rock samples taken from the formation is presented therein. The image comprises a plurality of pixels and the method comprises defining windows in the image, each window comprising predetermined number of pixels and being of a predetermined shape. The method also includes, for each window, extracting a rockprint value representative of the window. A rockprint comprises indicators for characterizing a texture of the window. The method also includes classifying the windows into categories of a predetermined set. Each category is representative of one type of rock and the classification is based on a comparison of the rockprint value of each window with rockprint values of images of reference rock samples for each category. Based on the classification, the method then includes determining the at least one property of the geological formation, ie the quantification of each type of rock in the sample.

Abstract: The disclosure relates to a method for analysing cuttings exiting a borehole. The method comprises taking at least an image of a sample of cuttings on a background surface, obtaining spectra representative of the image in the (hue, saturation, brightness) coordinate space, wherein each spectrum is associated to a coordinate and is representative of the distribution of the values of the pixels for the coordinate. Based on the spectrum and the values of each pixel for the associated coordinate, classifying the pixel in one of a plurality of groups, wherein each group is representative of a type of objects within the image, i.e. cuttings and background surface. The method also comprises determining at least a cuttings zone in the image based on the classification of the pixels.

Abstract: A method for determining a property of a geological formation based on an optical image of rock samples taken from the formation is presented therein. The image comprises a plurality of pixels and the method comprises defining windows in the image, each window comprising predetermined number of pixels and being of a predetermined shape. The method also includes, for each window, extracting a rockprint value representative of the window. A rockprint comprises indicators for characterizing a texture of the window. The method also includes classifying the windows into categories of a predetermined set. Each category is representative of one type of rock and the classification is based on a comparison of the rockprint value of each window with rockprint values of images of reference rock samples for each category. Based on the classification, the method then includes determining the at least one property of the geological formation, ie the quantification of each type of rock in the sample.

Abstract: The present disclosure concerns a method for detecting gain or loss of drilling fluid in a drilling installation, said drilling installation comprising a drilling pipe, drilling fluid pits and a hydraulic connection between the pits and the drilling pipe.

Abstract: The disclosure relates to a method for analysing cuttings exiting a borehole. The method comprises taking at least an image of a sample of cuttings on a background surface, obtaining spectra representative of the image in the (hue, saturation, brightness) coordinate space, wherein each spectrum is associated to a coordinate and is representative of the distribution of the values of the pixels for the coordinate. Based on the spectrum and the values of each pixel for the associated coordinate, classifying the pixel in one of a plurality of groups, wherein each group is representative of a type of objects within the image, i.e. cuttings and background surface. The method also comprises determining at least a cuttings zone in the image based on the classification of the pixels.

Abstract: The present disclosure concerns a method for detecting gain or loss of drilling fluid in a drilling installation, said drilling installation comprising a drilling pipe, drilling fluid pits and a hydraulic connection between the pits and the drilling pipe.