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 Least-Squares Problem; Preconditioning; Regularization; Non-linear Inverse Problems; Monte Carlo Methods; Probabilistic Inference; Examples of Linear and Non-linear 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