Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.