AI/machine learning

Computer Vision Analytics Enables Determination of Rig State

This paper describes a method to determine rig state from camera footage using machine-learning-based vision-analytics approaches.

Optical flow equipment

While companies cannot agree on a standard definition of “rig state,” they can agree that, as further use is made of remote operations and automation, rig-state calculation is mandatory in some form. By use of a machine-learning model that relies exclusively on videos collected on the rig floor to infer rig states, overcoming the limitations of existing methods is possible as the industry moves into a future of rigs featuring advanced technologies.


The complete paper presents a machine-learning pipeline implemented to determine rig state from videos captured on the floor of an operating rig. The pipeline is composed of two parts. First, the annotation pipeline matches each frame of the video data set to a rig state.

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