This practical and highly-interactive course includes real-life case studies and exercises where participants will be engaged in a series of interactive small groups and class workshops. 

This course is designed to provide participants with a detailed and up-to-date overview of Modelling & Managing Uncertainty in the Subsurface. It covers the types of uncertainty in subsurface modelling comprising of statistical, spatial and model uncertainty; the principles of geostatistics including data acquisition and quality; the difference between deterministic and probabilistic modelling; the advanced geostatistical methods of stochastic modelling; the uncertainty of petrophysical properties; and the statistical sampling and distribution models and seismic data in stochastic models. 

 

During this interactive course, participants will learn the reservoir heterogeneity and uncertainty; the structural modelling, fluid distribution and flow uncertainty; the scenario analysis and sensitivity studies, well test data and machine learning in subsurface modelling; the Monte Carlo simulation and risk analysis; the condition models to dynamic data, history matching and model updating; the proper tools and methods for effective communication; the decision analysis under uncertainty; and the risk management strategies, economic aspects of uncertainty, emerging trends and future directions.