Inverse Problems in Geophysics
An important aspect of geophysics is inversion, where we make inferences about physical parameters of the Earth from the recorded measurements. This course presents the mathematical formulation and design of inverse problems such as traveltime tomography, waveform inversion, surface wave tomography. Towards the end, emerging methods that use machine learning in geophysical inversion will also be discussed. A list of topics that are covered in this course: Linear Discrete Inverse Problems; The LeastSquares Problem; Preconditioning; Regularization; Nonlinear Inverse Problems; Monte Carlo Methods; Probabilistic Inference; Examples of Linear and Nonlinear Inverse Problems; Introducing Machine Learning for Inverse Problems.
References

Parameter Estimation and Inverse Problems, Richard Aster, Brian Borchers, Cliff Thurber

Inverse Problem Theory, Albert Tarantola

Geophysical Signal Analysis, Enders A. Robinson, Sven Treitel

Fundamentals of Geophysical Data Processing, John F Clarebout