EOSC 556 · Studies in Applied Geophysics

Being offered as EOSC 556B

Combining physics driven and data driven methods for using geophysical and remote sensing data to solve problems in the geosciences. Case histories related to societal challenges due to climate change, environmental problems, and natural resources motivate the methods covered. This course emphasizes practical application of quantitative methods in numerical modelling, inverse theory, and machine learning; a course project provides the opportunity for students to select a topic of interest to explore in more depth. 

key concepts 

  • numerical modelling: considerations for running numerical simulations including: how to design a mesh for a simulation, understanding boundary conditions and how to test the setup of a numerical simulation 
  • inversion: fitting a physics-based model to observed data. Non-uniqueness of the inverse problem, the use of regularization, and avenues for bringing additional data and information into an inversion
  • survey design: the use of numerical modelling and inversion to assess if a survey should be capable of detecting a target of interest,
  • machine learning and advanced topics: use of machine learning for integrating data sets, areas of research in combining physics-driven and data-driven approaches 

This course is not eligible for Credit/D/Fail grading.

Course Availability & Schedule