Abstract: A method for monitoring solids content during drilling operations may include collecting real-time cuttings image data at a surface outlet of a natural resource well, determining cuttings characteristics data based on the real-time cuttings image data, collecting real-time surface mud data, and determining real-time, one-dimensional downhole cuttings information based on a multi-dimensional computational fluid dynamics model. The cuttings characteristics data may include cuttings size distribution, cuttings volume, cuttings velocity, cuttings orientation, cuttings area, or combinations thereof. The real-time surface mud data may include inlet mud parameters, drilling operational parameters, well planning parameters, or combinations thereof.

Abstract: The present disclosure pertains to a circuitry for processing a target region configured to: determine a deviation in a scene based on background model data and current image data of the scene: determine a movement in the scene based on Doppler radar data of the scene; and determine a target region in the scene based on at least one of the determined deviation and the determined movement.

Abstract: Methods and systems for drilling a well into a subsurface formation are configured for performing a downhole measurement to generate measurement-while-drilling (MWD) data; retrieving a machine learning model that is trained using labeled surface or subsurface data, the labeled surface or subsurface data representing one or more unplanned drilling incidents each causing a respective data signature in the surface or subsurface data, each respective data signature being associated with a corresponding label identifying the unplanned drilling incident; inputting the surface or subsurface data, generated based on the downhole measurement, into the machine learning model; generating, by the machine learning model based on the inputting, a classification output representing at least one unplanned drilling incident represented in the surface or subsurface data; and generating, based on the classification output, output data predicting at least one future unplanned drilling event.

Abstract: A method for monitoring solids content during drilling operations may include collecting real-time cuttings image data at a surface outlet of a natural resource well, determining cuttings characteristics data based on the real-time cuttings image data, collecting real-time surface mud data, and determining real-time, one-dimensional downhole cuttings information based on a multi-dimensional computational fluid dynamics model. The cuttings characteristics data may include cuttings size distribution, cuttings volume, cuttings velocity, cuttings orientation, cuttings area, or combinations thereof. The real-time surface mud data may include inlet mud parameters, drilling operational parameters, well planning parameters, or combinations thereof.