Correcting borehole images using machine-learning models

A method comprising:

• generating, by a processor, a training dataset using a three-dimensional model, the three-dimensional model being for simulating a tool in a geological subterranean formation;
• training, by the processor, a machine-learning model based on the training dataset to generate a trained machine-learning model, the machine-learning model being different than the three-dimensional model, the training dataset including a first set of borehole images correlated to a second set of borehole images, the second set of borehole images being less precise versions of the first set of borehole images;
• executing, by the processor, 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 being a visually corrected version of the input borehole image, wherein the input borehole image is a two-dimensional digital image that includes colored pixels representing a property of a subterranean formation into which a borehole is drilled for extracting hydrocarbons from the subterranean formation, and wherein the corrected borehole image is also a two-dimensional digital image;
• and
• generating, by the processor, a graphical user interface that includes the corrected borehole image for display on a display device.

A non-transitory computer-readable medium comprising program code that is executable by a processor for causing the processor to:

• generate a training dataset using a three-dimensional model, the three-dimensional model being for simulating a tool in a geological subterranean formation;
• train a machine-learning model based on the training dataset to generate a trained machine-learning model, the machine-learning model being different than the three-dimensional model, the training dataset including a first set of borehole images correlated to a second set of borehole images, the second set of borehole images being less precise versions of the first set of borehole images;
• execute the trained machine-learning model to generate a corrected borehole image based on an input borehole image, the corrected borehole image being visually corrected in at least one way relative to the input borehole image, wherein the input borehole image is a two-dimensional digital image that includes colored pixels representing a property of a subterranean formation into which a borehole is drilled for extracting hydrocarbons from the subterranean formation, and wherein the corrected borehole image is also a two-dimensional digital image;
• and
• execute one or more operations based on the corrected borehole image.