MRE – Mineral Resource Estimation by linear geostatistics | Training course

• MODULE 1: UNIVARIATE GEOSTATISTICS
  – Analyse mineral and metal grade statistics and stationarity.
  – Understand the theory of variographical analysis.
  – Perform directional variogram modelling on the drillhole data.
  – Interpolate grade to the block space by block ordinary kriging.
  – Gain some insights about the weight distribution by kriging.
  – Learn how to define a sound neighbourhood for interpolation.
  – Learn and practice the validation tools for estimated grades.
  – Generate grade-tonnage curves and tables.
  – Create a basic workflow of mineral resource estimation in Isatis.neo.

• MODULE 2: MULTIVARIATE GEOSTATISTICS
  – Learn the application of Principal Component Analysis in mineral resource estimation.
  – Learn to model a non-stationary grade variable in 3D by trend-based variants of kriging.
  – Perform cross-variogram modelling on the correlated grades.
  – Perform cross-covariance modelling on the correlated grades (purely heterotopic datasets).
  – Jointly interpolate the correlated grades to the block space by ordinary cokriging, collocated cokriging, and rescaled cokriging, implemented in Isatis.neo.

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

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

• MODULE 1: UNIVARIATE GEOSTATISTICS
  – The importance of geostatistics in Mineral Resource Estimation
  – Extrapolatory Data Analysis (EDA) and spatial analysis of data
  – Stationarity analysis
  – Regularizing data: compositing and declustering
  – Variographical analysis: variogram cloud and parameters of experimental variogram
  – Variogram modelling: automatic, semi-automatic, manual and interactive
  – Theory of kriging and mining-related variants: ordinary and block kriging
  – Kriging Neighbourhood Analysis (KNA)
  – Cross-validation
  – Validation of estimation
  – Grade-tonnage table and curves 
• MODULE 2: MULTIVARIATE GEOSTATISTICS
  – Principal Component Analysis (PCA)
  – Kriging non-stationary variable: kriging with external drift or universal kriging
  – Cross-variogram and cross-covariance
  – Ordinary cokriging
  – Collocated cokriging
  – Rescaled cokriging

• Theory: slides will be provided.
• Practice: A training license for Isatis.neo geostatistical software will be attributed to the participants as well as a typical mining dataset.

• This training is designed for geologists who want to discover geostatistical tools frequently used in mineral resource estimation. 
• Basic knowledge of resource concepts such as grade, tonnage, and cut-off is recommended.
• To extend your knowledge, we recommend that you also attend the complementary advanced short course Recoverable Resource Estimation