US 11,719,089 B2
Analysis of drilling slurry solids by image processing
Michael Affleck, Aberdeenshire (GB); Arturo Magana Mora, Dhahran (SA); Chinthaka Pasan Gooneratne, Dhahran (SA); William Contreras Otalvora, Dhahran (SA); and Pratyush Singh, Dhahran (SA)
Assigned to Saudi Arabian Oil Company, Dhahran (SA)
Filed by Saudi Arabian Oil Company, Dhahran (SA)
Filed on Jul. 15, 2020, as Appl. No. 16/930,014.
Prior Publication US 2022/0018241 A1, Jan. 20, 2022
Int. Cl. E21B 47/002 (2012.01); E21B 21/06 (2006.01); E21B 49/00 (2006.01); G06N 3/02 (2006.01); G06F 18/24 (2023.01)
CPC E21B 47/0025 (2020.05) [E21B 21/066 (2013.01); E21B 49/003 (2013.01); G06F 18/24 (2023.01); G06N 3/02 (2013.01); E21B 21/06 (2013.01)] 16 Claims
OG exemplary drawing
 
1. A system comprising:
a digital imaging device mounted to a non-vibrating member of a shale shaker of a wellbore drilling assembly, the shale shaker positioned at a surface of the Earth adjacent a wellbore and configured to receive a solid slurry comprising a mixture of wellbore drilling mud and solid objects found in the wellbore while drilling the wellbore through a subterranean zone, the solid objects comprising drill cuttings and non-drilled solids, the digital imaging device oriented to face a portion of the shale shaker that receives the solid slurry, the digital imaging device configured to capture digital images of the solid objects while the solid slurry is received by the shale shaker; and
a computer system operatively coupled to the digital imaging device, the computer system comprising:
one or more processors; and
a computer-readable medium storing instructions executable by the one or more processors to perform operations comprising:
receiving the images captured by the digital imaging device; and
by implementing image processing techniques on the images, classifying a first solid object captured in a first image as a drill cutting and a second solid object captured in a second image as a non-drilled solid, wherein, to implement the image processing techniques, the computer system is configured to perform operations comprising deploying deep learning techniques comprising deploying a convolutional neural network (CNN) model for pattern recognition and image classification of the digital images captured by the digital imaging device,
wherein the operations further comprise:
receiving drilling parameters applied to the wellbore drilling assembly to drill the wellbore;
applying the received drilling parameters as inputs to the CNN model, wherein the drilling parameters comprise a rate of penetration, a weight on bit, and wellbore drilling mud flow rate; and
deploying the CNN model including the received drilling parameters as inputs for the pattern recognition and the image classification of the digital images.