2017 IAMG Distinguished Lecturer
Clayton V. Deutsch
Dr. Deutsch is a Professor in the School of Mining and Petroleum Engineering at the University of Alberta. He teaches and conducts research into better ways to model heterogeneity and uncertainty in petroleum reservoirs and mineral deposits. Prior to joining the University of Alberta, Dr. Deutsch was an Associate Professor (Research) in the Department of Petroleum Engineering at Stanford University, a researcher at Exxon Production Research Company and a geostatistician with Placer Dome Inc. He has published eight books and over 250 research papers. Dr. Deutsch holds the Alberta Chamber of Resources Industry Chair in Mining Engineering and the Canada Research Chair in Natural Resources Uncertainty Characterization.
All Realizations All the Time
Sparse sampling combined with geological heterogeneity at all scales leads to inevitable uncertainty. The quantification of joint uncertainty in high dimensional spatial problems requires multiple realizations. Managing all realizations through decision making is problematic. Theory, implementation details and the practice of creating and managing realizations will be shown. Active uncertainty management versus passive observation of uncertainty will be emphasized.
Geometallurgy from a Geostatistical Perspective
High-resolution spatial numerical models of metallurgical properties constitute an important part of geometallurgy. Geostatistical and other numerical techniques are reviewed and illustrated for geometallurgical modeling. Important considerations include the data scale, non-linear averaging, incomplete and censored sampling, and the appropriate modeling workflow. Theory, implementation and glimpses of case studies will be shown.
Millimeter to Kilometer Scale Reservoir Modeling
Geostatistical models of reservoir rock are constructed at many scales for different purposes. Millimeter scale models are used with high resolution image logs for improved permeability prediction. Kilometer scale models are created for regional exploration. There are many models in between. The techniques and practice of constructing different models for different purposes will be reviewed with examples.
Developments in Multivariate Geostatistics
Simultaneous modeling of 10s to 100s of related properties is required in many geostatistical studies. Novel developments in understanding multivariate dependencies and spatial prediction of many dependent variables will be presented. A taxonomy of multivariate techniques and workflows are presented to show the breadth and variety required for modern geostatistical modeling. Examples will be shown.
Dr. Deutsch has taught nearly 200 short courses internationally. Popular courses include:
Fundamentals of Geostatistics (2 to 4 days)
Mineral Resource Estimation (3 to 5 days)
Geostatistical Reservoir Modeling (3 to 5 days)
Advanced Multivariate Geostatistics (3 to 5 days)
last updated 2016-11-20