US 11,727,555 B2
Rig power system efficiency optimization through image processing
Michael Affleck, Aberdeenshire (GB); Arturo Magana Mora, Dhahran (SA); Chinthaka Pasan Gooneratne, Dhahran (SA); and William Contreras Otalvora, Dhahran (SA)
Assigned to Saudi Arabian Oil Company, Dhahran (SA)
Filed by Saudi Arabian Oil Company, Dhahran (SA)
Filed on Feb. 25, 2021, as Appl. No. 17/185,688.
Prior Publication US 2022/0270227 A1, Aug. 25, 2022
Int. Cl. G06T 7/00 (2017.01); G06N 3/08 (2023.01); H04N 5/38 (2006.01); E21B 41/00 (2006.01)
CPC G06T 7/001 (2013.01) [G06N 3/08 (2013.01); H04N 5/38 (2013.01); E21B 41/00 (2013.01); G06T 2200/24 (2013.01); G06T 2207/10016 (2013.01); G06T 2207/20081 (2013.01); G06T 2207/30164 (2013.01)] 23 Claims
OG exemplary drawing
 
1. A method comprising:
receiving, by a computer system configured to implement a machine learning model, a video of a visible state of a component of a generator, the generator powering at least a portion of a rig equipment system at a wellsite;
determining, by the computer system, an operational parameter based on the visible state of the component of the generator imaged in the video, the determining the operational parameter comprises:
receiving, by the machine learning model, training data comprising historical images of the visible state of the component of the generator and historical measured operational parameters;
correlating, by the machine learning model, the historical images with corresponding historical measured operational parameters; and
determining, by the machine learning model, the operational parameter based on a comparison of the video of the visible state with the historical images; and
transmitting, by the computer system, the operational parameter to an output device.