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Training
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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 virtual 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. In-person workshops are also being held in Calgary, Alberta, Canada for 2024 on advanced topics and will run all day. Registration is now open for 2024 courses.
Public Course Schedule
May 17
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.
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 31
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.
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.
June 14
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.
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.
July 12
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.
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.
August 2
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.
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.
Sept. 30
8:45 AM MDT
Practical Simulation
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 second half of the module will focus on checking simulated realizations including the assessment of accuracy and precision. This is an in-person course held in Calgary, Alberta and will not be streamed or recorded.
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 second half of the module will focus on checking simulated realizations including the assessment of accuracy and precision. This is an in-person course held in Calgary, Alberta and will not be streamed or recorded.
Oct. 1
8:45 AM MDT
Advanced Modeling Workflows
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 steps of EDA, trend modeling, model construction, model validation, classification, and post processing through to probabilistic resources. This is an in-person course held in Calgary, Alberta and will not be streamed or recorded.
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 steps of EDA, trend modeling, model construction, model validation, classification, and post processing through to probabilistic resources. This is an in-person course held in Calgary, Alberta and will not be streamed or recorded.
Oct. 2
8:45 AM MDT
Classification and Drillhole Spacing Workflows
The practice and a full worked case study to optimize drill hole spacing (and placement) considering local factors and value of information are presented with examples. The solution will include all steps of resampling and resimulation, model construction, model validation and analysis of uncertainty versus drill hole spacing. This is an in-person course held in Calgary, Alberta, and will not be streamed or recorded.
The practice and a full worked case study to optimize drill hole spacing (and placement) considering local factors and value of information are presented with examples. The solution will include all steps of resampling and resimulation, model construction, model validation and analysis of uncertainty versus drill hole spacing. This is an in-person course held in Calgary, Alberta, and will not be streamed or recorded.
Oct. 3
8:45 AM MDT
Machine Learning for Geometallurgical Modeling
Practical techniques and applications for machine learning applied to metallurgical property modeling are covered with an emphasis on regression using many data types (assays, scans, geochemistry, geologic logs). The majority of this day does not require a background in geostatistics and is suitable for geoscientists, metallurgists, and engineers engaged in analyzing geometallurgical data. This is an in-person course held in Calgary, Alberta, and will not be streamed or recorded.
Practical techniques and applications for machine learning applied to metallurgical property modeling are covered with an emphasis on regression using many data types (assays, scans, geochemistry, geologic logs). The majority of this day does not require a background in geostatistics and is suitable for geoscientists, metallurgists, and engineers engaged in analyzing geometallurgical data. This is an in-person course held in Calgary, Alberta, and will not be streamed or recorded.
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