Framework for log reconstruction and interpretation using latent representations and parameterized physical models

Abstract

Described herein are systems and techniques for reconstructing target well log measurements using machine learning. An example method can include receiving input data comprising one or more input logs; generating, using a machine learning model, a latent representation of the input data; estimating, based on the latent representation, one or more parameters of a reconstruction model associated with at least one target log, wherein the at least one target log corresponds to a log type that is not fully represented in the input data; and generating, using the one or more parameters, a reconstructed version of the at least one target log.