Mineral resource estimation by linear geostatistics | Module 2

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

Advance into the multivariate context by exploring multivariate statistical tools like Principal Component Analysis, applying kriging and co-kriging methods for estimating multi-element orebodies, and obtaining multivariate models respecting the ratio between main metals, oxides, and elements.

Note this course consists of two modules. The first module focuses on univariate 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

• Principal Component Analysis (PCA).
• Kriging non-stationary variable: kriging with external drift or universal kriging.
• Grade correlation analysis.
• Cross-variogram and cross-covariance on purely heterotopic datasets.
• Correlated grades interpolation by Ordinary cokriging, Collocated cokriging and Rescaled cokriging.

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.