Theory guided machine learning in geophysics

Zhan Niu

Machine learning has become a popular topic in the past decade thanks to the booming in computer hardware and the tools invented. Many successful applications have been made in various subjects in geophysics, including salt body detection, facies recognition and inversion etc. However, the fact that most geophysical theory is well-established sometimes contradicts the black box theory in machine learning when combining methods in the two fields. This thesis will discuss several ways of incorporating well-established knowledge into machine learning by giving a few applications and experiments in geophysics. We will also discuss the limitations and challenges machine learning is facing.