Training
Recoverable Resource Estimation by nonlinear geostatistics – Module 3: Simulations
Where this module sits
The “Recoverable Resource Estimation” course is delivered in four modules that you can take separately or in sequence.
Module 1 — Uniform Conditioning. Unbiased grade-tonnage curves from sparse drilling, localized to the SMU level.
Module 2 — Multiple Indicator Kriging and Conditional Expectation. Two nonlinear estimators and how to choose between them.
Module 3 — Simulations. Multiple realizations with Turning Bands, SGS, and direct block simulation, post-processed into grade-tonnage curves.
Module 4 — Advanced multivariate modeling. Trend, decorrelation by PCA, MAF and PPMT, imputation and ratio transforms.
Objectives
- Generate multiple equally probable realizations of your grades with Turning Bands Simulation and Sequential Gaussian Simulation.
- Choose between the two according to your deposit and your computing constraints.
- Simulate directly at block scale to save time and disk space, and know when that shortcut holds.
- Post-process a set of realizations into grade-tonnage curves, and read the spread across them as risk.
Target audience
Geologists, mining engineers, and professionals involved in feasibility studies or medium- to long-term planning who wish to deepen their theoretical and practical knowledge of mining geostatistics.
Content
Introduction
- Understand the fundamentals of recoverable resource estimation and its critical role in resource modeling and mine planning.
Simulations
- Master general simulation concepts. Learn the theory.
- Model the Gaussian anamorphosis: Transform any distributions into Gaussian ones, a necessary step for nonlinear modeling.
- Discover two widely used conditional simulation methods: Turning Bands Simulation (TBS) and Sequential Gaussian Simulation (SGS). Understand their theoretical foundations, practical applications, and where each method performs best.
- Unlock the power of Direct Block Simulations: Bypass the traditional point-scale modeling approach with this efficient technique that generates block-scale simulations directly, saving valuable time and disk space without compromising accuracy.
Post-processing of simulation results
- Produce robust grade-tonnage curves from simulations to support your resource evaluations.
What the course includes
- Balanced learning approach. Theory paired with practical applications, so you understand and apply the concepts.
- Hands-on software training. Computer exercises in Isatis.neo, on real datasets.
- Personalized feedback. Individual guidance from experienced trainers throughout the online sessions.
- Comprehensive resources. A temporary software license, course documentation, journal files, and datasets to keep and reuse after the course.
- Certificate of completion issued at the end of the session.
Prerequisites
- Basic knowledge of linear geostatistics is recommended. The Mineral Resource Estimation course, which covers the fundamental concepts of geostatistics for resource estimation, provides an ideal foundation for this advanced course.
- A basic understanding of resource concepts such as grade, tonnage, and cut-off is beneficial.
Register, or ask us first
This form handles all three: registration, a quote for yourself or your team, and questions about the content or the prerequisites.
Address
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