Correcting borehole images using machine-learning models

Abstract

Borehole images can be corrected using machine-learning models. For example, a system can train a machine-learning model based on a training dataset. The training dataset can include a first set of borehole images correlated to a second set of borehole images, where the second set of borehole images are less precise versions of the first set of borehole images. The system can then execute the trained machine-learning model in relation to an input borehole image to receive a corrected borehole image as output from the trained machine-learning model. The corrected borehole image can be a visually corrected version of the input borehole image. The system may then perform one or more operations based on the corrected borehole image, such as generating a graphical user interface that includes the corrected borehole image for display on a display device.