Linear and non-linear inverse problem formulation. Local, global and ensemble-based optimization methods. Regularization techniques. Assessment of solution quality. Error and uncertainty analysis. Data integration. Subsurface engineering applications: model parameter estimation, production history matching, machine learning. Primary focus is on the application of various solution methods. Prerequisite: STAT 235 and CH E 374 or consent of instructor.