Baker Hughes Corporation

Baker Hughes Holdings LLC

Jeffrey R Potts

Anil Sadana

Sayantan Roy

Braden Starcher

Dustin Michael Sharber

Xiaoqing Ge

Michael H Johnson

Bennett M Richard

Anil K Sadana

An inspection method includes receiving a plurality of training images and an image of a target object obtained from inspection of the target object. The method further includes generating, by one or more training codes, a plurality of inference codes. The one or more training codes are configured to receive the plurality of training images as input and output the plurality of inference codes. The one or more training codes and the plurality of inference codes includes computer executable instructions. The method further includes selecting one or more inference codes from the plurality inference codes based on a user input and/or one or more characteristics of at least a portion of the received plurality of training images. The method also includes inspecting the received image using the one or more inference codes of the plurality of inference codes.

Automatic inspection using artificial intelligence models

A method of data preparation for artificial intelligence models includes receiving data characterizing a first plurality of images. The method further includes annotating a first subset of images of the first plurality of images based at least in part on a first user input to generate annotated first subset of images. The annotating includes labelling one or more features of the first subset of images. The method also includes generating, by a training code, an annotation code, the training code configured to receive the annotated first subset of images as input and output the annotation code. The training and the annotation code includes computer executable instructions. The method also includes annotating, by the annotation code, a second subset of images of the first plurality of images to generate annotated second subset of images, wherein the annotating includes labelling one or more features of the second subset of images.

Data preparation for artificial intelligence models

A method of forming a structure for a downhole application comprises forming an interfacial material comprising at least one of self-reinforced polyphenylene, polyphenylene sulfide, polysulfone, and polyphenylsulfone between opposing surfaces of a first substrate and a second substrate. A downhole structure and a downhole assembly are also described.

Methods of forming structures for downhole applications

Methods of using a component in a subterranean wellbore include positioning a component including a degradable thermoset polymer material in a wellbore location, obstructing flow with the component, exposing the component to an acidic solution to degrade the selectively degradable thermoset polymer material and to remove the component from the wellbore location, and flowing a fluid through the wellbore location where the component was positioned. Methods of forming a component of a wellbore system include forming at least a portion of the component to comprise a degradable thermoset polymer material. Wellbore systems include at least one component including a selectively degradable thermoset polymer material. The selectively degradable thermoset polymer material may be a polyhexahydrotriazine ('PHT') material.

Methods of forming a degradable component

Methods of using a degradable component in a wellbore and related systems and methods of forming such components

A composition contains a polymer component comprising a crosslinked product of a polyarylene, a crosslinked product of a substituted polyphenylene, a crosslinked product of a polyphenylene sulfide and a polyphenylsulfone, or a combination comprising at least one of the foregoing; and a mesoporous silicate having an average pore size of about 5 nanometers to about 50 nanometers. The composition has high-temperature elastomeric properties and excellent mechanical strength. The compositions are useful in oil and gas downhole applications. Methods for the manufacture of the composition and articles comprising the composition are also disclosed.

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Houston, TX, United States of America

Jeffrey R Potts