Engineering design for site remediation. Deterministic and stochastic methods for optimization in earth sciences and engineering. Linear and non-linear regression, classification and pattern recognition using neural networks, simulated annealing and genetic algorithms. Applications in petroleum engineering, geostatistics and geophysics. The course is intended to give an overview of the principles of optimization .
Optimization is probably the most important engineering problem.
Most optimization problems also involve some kind of inverse problem . The task is then to invert the medium from the measurements, for example what is porosity at each location given a particular 3D seismic survey, or what is the permeability distribution given a particular well test. I cover in the course the mathematical tools that are used to solve this problem. Data summaries, graphical display of data, measures of association, time series and trends, sampling, quantification of uncertainty, statistical models, statistical testing and prediction. The analysis of spatial information, introduction to geostatistical methods for estimating spatial phenomena.