DRILLING CONTROL
    1.
    发明公开
    DRILLING CONTROL 审中-公开

    公开(公告)号:US20240018864A1

    公开(公告)日:2024-01-18

    申请号:US18477656

    申请日:2023-09-29

    CPC classification number: E21B44/00 E21B47/024 E21B7/04

    Abstract: A system and method that include receiving sensor data during drilling of a portion of a borehole in a geologic environment. The system and method also include selecting a drilling mode from a plurality of drilling modes based at least on a portion of the sensor data. The system and method additionally include simulating drilling of the borehole using the selected drilling mode in a multi-dimensional spatial environment to generate a simulated state of the borehole in the geologic environment. The system and method further include analyzing the simulated state of the borehole and generating a reward using the simulated state of the borehole and a planned borehole trajectory and using the reward to train an agent to provide automated directional drilling with transitions between at least one of: a plurality of drilling modes and a plurality of toolface settings.

    WELLSITE REPORT SYSTEM
    2.
    发明公开

    公开(公告)号:US20230376873A1

    公开(公告)日:2023-11-23

    申请号:US18361942

    申请日:2023-07-31

    CPC classification number: G06Q10/0633 E21B44/00 G06Q10/109 G06Q50/26 G06F40/40

    Abstract: A system and method that include receiving sensor data acquired during execution of a drilling operation workflow and generating state information of a wellsite system and receiving contextual information for a role associated with a workflow that includes one or more tasks of the workflow. The system and method also include generating a natural language report based at least in part on the state information and based at least in part on the contextual information to facilitate planning and execution of the one or more tasks of the workflow. The system and method further include transmitting the natural language report via a network interface based at least in part on an identifier associated with the role and presenting a graphical user interface that renders information as to the planning and execution of the one or more tasks of the workflow to achieve a desired state of the wellsite system.

    Image based system for drilling operations

    公开(公告)号:US10995571B2

    公开(公告)日:2021-05-04

    申请号:US16304330

    申请日:2017-05-24

    Abstract: A drilling rig site may include at least one tubular configured to be inserted into a wellbore at the drilling rig, at least one imaging device configured to detect a location of an end of the at least one tubular or a feature of the at least one tubular, and a processor receiving an input from the at least one imaging device and configured to calculate a distance between the end of the at least one tubular and another element, a diameter of the at least one tubular, or movement of the at least one tubular. A method for completing a drilling operation at a rig site, may include capturing an image of a tubular at a rig site, the tubular configured to be inserted into a wellbore at the rig site, detecting a location of an end of the tubular or a feature of the tubular from the image, and determining a diameter of the tubular, a distance between the detected end of the tubular and another element, or movement of the tubular.

    Drilling control
    10.
    发明授权

    公开(公告)号:US12252975B2

    公开(公告)日:2025-03-18

    申请号:US18331269

    申请日:2023-06-08

    Abstract: A system and method that include receiving sensor data during drilling of a portion of a borehole in a geologic environment. The system and method also include selecting a drilling mode from a plurality of drilling modes based at least on a portion of the sensor data. The system and method additionally include simulating drilling of the borehole using the selected drilling mode and generating a state of the borehole in the geologic environment based on the simulated drilling of the borehole. The system and method further include generating a reward using the state of the borehole and a planned borehole trajectory and using the reward through deep reinforcement learning to maximize future rewards for drilling actions.

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