Mineral resource estimation by linear geostatistics | Module 1

Learn the fundamental concepts of geostatistics to estimate your mineral resources confidently.

Learn and practice the standard workflow for resource estimation in a univariate context. This module covers in-depth data analysis, detailed variographic analyses, block modeling, grade distribution interpolation using kriging, estimation validation and unbiased grade-tonnage curves for short-term resources.

The techniques you will learn apply to:

• Primary estimation of long-term resources.
• Estimation of short-term resources.
• Production of resource models for mine design.
• Spatial analysis of drillhole data.

Note this course consists of two modules. The second module focuses on multivariate geostatistics.

Outlines

• The course is structured into two parts, Module 1 and Module 2, each lasting two days. Depending on your needs, you can attend either module independently.
• It combines methodological presentations and practical exercises using a real data set to enhance the understanding of key concepts.
• Participants will engage in computer exercises with Isatis.neo.
• Course material and a temporary software license will be provided.

Course content

• The importance of geostatistics in Mineral Resource Estimation.
• Extrapolatory Data Analysis (EDA) and spatial analysis of data.
• Data stationarity analysis.
• Data regularization: compositing and declustering.
• Variographical analysis: variogram cloud and parameters of experimental variogram, directional variogram.
• Variogram modeling: automatic, semi-automatic, manual and interactive.
• Theory of kriging and mining-related variants: ordinary and block kriging, weight distribution analysis.
• Building a sound sample neighborhood: Kriging Neighbourhood Analysis (KNA)
• Cross-validation
• Estimation validation
• Grade-tonnage table and curves

Prerequistes

• A basic understanding of resource concepts such as grade, tonnage, and cut-off is recommended.
• We recommend attending the complementary advanced short course Recoverable Resource Estimation to extend your knowledge.

Who should join?

Professionals seeking a sound theoretical and practical knowledge of mining geostatistics.