Landmark Graphics Corporation

Halliburton Energy Services, Inc.

Chafaa Badis

Welton Danniel Souza

Sebastian Kroczka

John L Maida

Yoann Santin

Kashyap Navinchand Choksey

Kashyap Choksey

Muhammad Yasir

Perminder Sabharwal

A method for training a well model to predict material loss for a pipe string having a wall thickness and located within a borehole. The method may include measuring the wall thickness of a first pipe string at locations axially along the first pipe string with a logging tool at a first time. The method may also include measuring the wall thickness of the first pipe string at the locations with the logging tool at a second time. The method may further include training a first well model based on a machine learning ('ML') algorithm to predict a predicted amount of material loss in the future for the first pipe string at a selected location using the wall thickness measurements at the first and second times and well operating condition information related to the first pipe string.

Systems and methods for training a well model to predict material loss for a pipe string within a borehole

Systems and methods to perform an automated downhole inspection in real-time are disclosed. A method to perform the downhole inspection includes deploying a camera and a logging tool downhole. The method also includes obtaining real-time transmissions of images from the camera. The method further includes obtaining real-time transmissions of data from the logging tool. The method further includes determining a presence of a downhole anomaly based on the real-time transmissions of images and the real-time transmissions of data.

Systems and methods to perform a downhole inspection in real-time

A system is disclosed for detecting a problem associated with a drilling operation based on the properties of a formation cutting. The system can include a camera for generating an image of the formation cutting extracted from a subterranean formation. The system can include one or more sensors for detecting one or more characteristics of the subterranean formation or a well tool. The system can provide the image as input to a first model for determining one or more properties of the formation cutting based on the image. The system can provide the one or more properties and the one or more characteristics as input to a second model for detecting a downhole problem associated with the drilling operation. The system can transmit an alert indicating the downhole problem and optionally a recommended solution to a user.

Formation-cutting analysis system for detecting downhole problems during a drilling operation

A well system includes a fiber-optic cable positionable downhole along a length of a wellbore. The well system further includes an opto-electrical interface to communicatively couple to the fiber-optic cable to monitor a gas released from a well element within the wellbore. Further, the well system includes a processing device and a memory device that includes instructions executable by the processing device. The instructions cause the processing device to detect hydrogen absorption by the fiber-optic cable within the wellbore and determining a location of deterioration of the well element using the detected hydrogen absorption by the fiber-optic cable.

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Lons, France

Chafaa Badis