We offer a series of introductory, advanced, and workflow geostatistical modeling classes. Learn how to successfully leverage the geostatistical toolkit available today.
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Choose from a wide selection of geostatistical modeling classes hosted in partnership with the Centre of Computational Geostatistics. Courses range from conventional estimation to advanced simulation, data spacing studies and more. Public courses included pre-course material, three hours of lectures, and post course material including data and complete solutions for each module completed in RMSP for reference and experimentation. Registration is now open for 2023 courses.
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Public Course Schedule
May 12
8:30 AM MDT
Introduction to Modern Geostatistics
Provides a high level overview of modern geostatistics including workflows for long range resources, drill hole spacing and classification, grade control and geometallurgical modeling. This is suitable to a wide audience including managers, staff from other disciplines who want to know about geostatistics and those that want a refresher.
May 19
8:30 AM MDT
Exploratory Data Analysis and Outlier Management
Covers exploratory data analysis including multivariate and outlier management, statistical displays and summary statistics for univariate and multivariate continuous and categorical variables. Outlier management by visual, statistical and geostatistical-simulation based methods are presented with examples.
May 26
8:30 AM MDT
Variogram Inference
Focused on the calculation, interpretation and modeling of variograms for continuous and categorical variables. The practical steps to obtain a geologically realistic and suitable variogram for all required variables are covered. Combining general geological knowledge with sparse drill data for the best possible variogram is reviewed. Change of support will be summarized.
June 9
8:30 AM MDT
Estimation and Kriging
Fundamental aspects of estimation including validation and setup for different model applications (implicit modeling/visualization, final estimates, interim estimates and probabilistic prediction). The theory will be developed. Attention will be given to practical application, parameter selection and validation of the results. Measures of performance are reviewed.
June 16
8:30 AM MDT
Simulation Fundamentals
The fundamental principles of simulation and, in particular, Gaussian simulation are covered including prerequisite steps such as the normal score transform. Unconditional simulation and conditioning by kriging are presented. Alternative implementations such as turning bands will be reviewed.
June 23
8:30 AM MDT
Simulation with a Trend
Trend modeling and removal for the simulation of non-stationary variables has emerged as a staple of modern geostatistics. The theory, implementation details and examples of optimizing trend models and modeling with a trend will be covered. The use of Gaussian mixture models and stepwise conditional transform is presented
July 7
8:30 AM MDT
Parameter Uncertainty and Checking
The multivariate spatial bootstrap will be presented for quantifying and transferring parameter uncertainty. The second half of the module will focus on checking simulated realizations including the assessment of accuracy and precision. Other checks such as statistical reproduction and swath plots are reviewed.
July 14
8:30 AM MDT
Hierarchical truncated Plurigaussian
The hierarchical truncated plurigaussian methodology will be presented for quantifying and transferring uncertainty in categorical geologic attributes (domains, lithologies, alterations, mineralization zones). Developing the truncation strategy and checks such as statistical reproduction are reviewed.
July 21
8:30 AM MDT
Multivariate Decorrelation
The theory and implementation of principal component analysis and variants such as sphering, minimum/maximum autocorrelation factors and projection pursuit multivariate transformation (PPMT) are presented for multivariate model building. Guidance on technique selection will be given and examples shown.
Sept. 8
8:30 AM MDT
Probabilistic Porphyry Modeling Workflow
The practice and a full worked case study will be presented for categorical and continuous simulation of a porphyry deposit with HTPG and PPMT. The solution will include all prerequisite steps, trend modeling, model construction, model validation, classification and post processing through to probabilistic resources.
Sept. 15
8:30 AM MDT
Data Imputation
The theory and workflows for the management of missing multivariate data are presented with examples. The treatment of biased data and data of differing quality will also be addressed with examples. Alternative techniques will be reviewed and guidance presented on current best practice.
Sept. 22
8:30 AM MDT
Probabilistic Tabular and Vein Modeling Workflow
The practice and a full worked case study will be presented for geometric and continuous property simulation with flattening transformations. The solution will include all prerequisite steps, surface and geometry modeling, boundary modeling, model construction, model validation, classification and resource calculation.
Nov. 3
8:30 AM MDT
Machine Learning for Geometallurgical Modeling
Practical techniques and applications for machine learning of metallurgical properties is covered. Techniques to manage non additive variables, unequally sampled data, limited test work are presented. Appropriate workflows are developed and presented.
Nov. 17
8:30 AM MST
Drillhole Spacing Workflow
The concepts, practice and a full worked case study to optimize drill hole spacing (and placement) considering local factors and value of information are presented. The solution will include all steps of resampling and resimulation, model construction, model validation and analysis of uncertainty versus drill hole spacing.
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