This course provides theories and concepts of geophysical modeling including forward modeling and modern inversion, as well as their application to geophysical problems. This course studies the estimation of parameter models, linear and non-linear inversion methods and their solutions, the use of a priori information, and the use of damping parameters.

1. Students are able to explain the concepts of geophysical modeling, forward modeling and inversion modeling
2. Students are able to formulate linear inversion problems and their general solutions through matrix equations
   
3. Students are able to solve simple linear inversion problems (straight-line regression, polynomial regression)
4. Students are able to demonstrate the effect of data uncertainty on linear inversion solutions and solution uncertainty in the form of a co-variant matrix model
5. Students are able to apply damped linear inversion to geophysical data
6. Students are able to formulate non-linear inversion problems with a linear approach
7. Students are able to apply non-linear inversion with a linear approach to geophysical data
8. Students are able to explain the characteristics of a linear approach to non-linear problems and formulate grid search and random search techniques
9. Students are able to explain the concept of guided random search and the simulated annealing method
10. Students are able to explain the concept of genetic algorithm
11. Students are able to explain the concept of Particle Swarm Optimization (PSO)
    
    

1. Menke, W., Geophysical Data Analysis: Discrete Inverse Theory, Academic Press, 1989.
2. Tarantola, A., Inverse Problem Theory: Methods for Data Fitting and Model Parameter Estimation, Elsevier, 1987.
3. Sen, MK, Stoffa, PL, Global Optimization Methods in Geophysical Inversion, Elsevier, 1995
4. Grandis, H., Introduction to Geophysical Inversion, HAGI, 2009.