Abstract: A method for forming a model of a bottom hole assembly (BHA) in a borehole, wherein the BHA is connected to a drill string. The method may further comprise segmenting the model into one or more segments and solving a multipoint boundary value problem (BVP) based at least in part on the one or more segments.

Abstract: The disclosure presents processes to determine one or more recommendations to well construction operations, generated by analyzing impacts on well construction operations. The impacts can include impacts to the drilling assembly, impacts of the subterranean formation characteristics, impacts on cost, time and performance of the well construction operation, impacts on the service quality, impacts to system integrity, impacts to surface equipment, as well as other impact types, such as geological surveys, seismic surveys, stratigraphic analysis, or reservoir estimations. Each impact can be analyzed using an impact parameter and a softness parameter. An impact map can be computed for each of the parameters, and then the impact maps can be combined to compute one or more integrated impact maps from which the recommendations can be determined. The recommendations can be communicated to a well construction system, such as a geo-steering system, a user system, a well site controller, or other systems.

Abstract: A video clip showing a wellsite activity can be extracted from a video and then labeled for use in training a machine-learning model in some examples described herein. In one such example, a system can train a model with a set of training data to identify an object and a corresponding spatial location of the object in each image frame in a video depicting a wellsite activity. The system can analyze image frames in the video using the trained model to identify a target image frame in which the object is present in a predefined spatial area thereof, where the predefined spatial area is associated with the wellsite activity. The system can then generate a video clip that includes only a subpart of the video based on the target image frame, where the subpart includes a series of consecutive image frames containing the target image frame.

Abstract: The disclosure presents processes to determine one or more recommendations to well construction operations, generated by analyzing impacts on well construction operations. The impacts can include impacts to the drilling assembly, impacts of the subterranean formation characteristics, impacts on cost, time and performance of the well construction operation, impacts on the service quality, impacts to system integrity, impacts to surface equipment, as well as other impact types, such as geological surveys, seismic surveys, stratigraphic analysis, or reservoir estimations. Each impact can be analyzed using an impact parameter and a softness parameter. An impact map can be computed for each of the parameters, and then the impact maps can be combined to compute one or more integrated impact maps from which the recommendations can be determined. The recommendations can be communicated to a well construction system, such as a geo-steering system, a user system, a well site controller, or other systems.

Abstract: Methods and compositions for estimating one or more downhole qualities of a drilling apparatus by obtaining axial acceleration data. The axial acceleration data may be acquired by measuring an axial acceleration of a bottom hole assembly. The axial acceleration may then be used to estimate one or more of a downward weight on a drill bit of the drilling apparatus or a rate of penetration of the drill bit.

Abstract: Systems and methods to determine an activity associated with an object of interest are presented. The method includes receiving a sequence of a plurality of frames that capture an area of interest during a threshold period of time, wherein an object of interest is present in the area of interest during the threshold period of time. The method also includes analyzing the plurality of frames to detect the object of interest. The method also includes tracking the object of interest in the area of interest during the threshold period of time. The method also includes extracting data indicative of the object of interest. The method also includes predicting, based on the data indicative of the object of interest, an activity associated with the object of interest.

Abstract: The disclosure provides for a method for identifying a mud motor drilling mode. The method comprises accessing historical run information stored in a memory of a controller and determining drilling measurements based on the historical run information. The method further comprises training at least one initial model with a machine learning method using the determined drilling measurements, wherein the at least one initial model comprises one or more inputs selected from a group consisting of revolutions per minute, tool-face, torque, flowrate, weight on bit, rate of penetration, differential pressure, a derivative thereof, and any combination thereof. The method further comprises utilizing the trained at least one initial model to determine the mud motor drilling mode for a mud motor.

Abstract: A video clip showing a wellsite activity can be extracted from a video and then labeled for use in training a machine-learning model in some examples described herein. In one such example, a system can train a model with a set of training data to identify an object and a corresponding spatial location of the object in each image frame in a video depicting a wellsite activity. The system can analyze image frames in the video using the trained model to identify a target image frame in which the object is present in a predefined spatial area thereof, where the predefined spatial area is associated with the wellsite activity. The system can then generate a video clip that includes only a subpart of the video based on the target image frame, where the subpart includes a series of consecutive image frames containing the target image frame.