Overview of conventional ore reserve estimation methods and accuracy of the results. Data accumulation and storage, descriptions of drill hole samples, geological model and domaining. Exploration data analysis: statistical and graphical analysis of drilling data as a whole and per geological unit, correlation between variables, definition of selective unit of estimation (block), development of block model.
Non-parametric statistics of one, two or more Random Variables (RV). RV sequences, vector representation of RV. The concept of Random Function (RF), simplified RF models. Spatial correlation and variogram function, variogram models. The projection methods with known and unknown mean (simple and ordinary Kriging algorithms).
Structural analysis of the deposit: calculation of experimental variogram function, isotropy and analysis of its characteristics. Reserves estimation: determination of estimation neighborhood, application of kriging algorithm, calculation of content of each block, calculation of errors, cross – validation of the numerical model with graphical overview and statistical comparison, grade- tonnage curves. Classification of ore reserves according to the estimation errors.
