Distribution related problems. Variogram related problems. Block variances. Estimation variance. Kriging. Recoverable reserves. Applied simulation. Classification of ore reserves. Check samples and duplicates.

Presents an applied approach to the estimation of mineral resources/reserves. It is suitable for any university or mining school that offers courses on mineral resource/reserve estimation. It will also be valuable for professional mining and geological engineers and geologists working with mineral exploration companies.

This book addresses the practice of geostatistical simulation to evaluation of mineral reserves, prediction of recovered tonnages and mineral grades and the impact of mining dilution. Such prediction is absolutely critical for mine planning and investment decisions, yet it cannot be made on maps directly interpolated from present data. Various dilution factors need to be introduced to account for · the support effect: mining unit volumes are vastly different from composite data unit volumes · the information effect: future selection of ore/waste will be based on vastly different data than that presently available. Geostatistical simulations allow a rigorous evaluation of these effects on reserves recovery. These stochastic simulations have the potential to be for the mining industry what a wind tunnel is for aircraft design. This book is written by two expert geostatisticians--Journel is the pioneer of mining geostatistics--and established academics.

Developments in Geomathematics, 2: Geostatistical Ore Reserve Estimation focuses on the methodologies, processes, and principles involved in geostatistical ore reserve estimation, including the use of variogram, sampling, theoretical models, and variances and covariances. The publication first takes a look at elementary statistical theory and applications; contribution of distributions to mineral reserves problems; and evaluation of methods used in ore reserve calculations. Concerns cover estimation problems during a mine life, origin and credentials of geostatistics, precision of a sampling campaign and prediction of the effect of further sampling, exercises on grade-tonnage curves, theoretical models of distributions, and computational remarks on variances and covariances. The text then examines variogram and the practice of variogram modeling. Discussions focus on solving problems in one dimension, linear combinations and average values, theoretical models of isotropic variograms, the variogram as a geological features descriptor, and the variogram as the fundamental function in error computations. The manuscript ponders on statistical problems in sample preparation, orebody modeling, grade-tonnage curves, ore-waste selection, and planning problems, the practice of kriging, and the effective computation of block variances. The text is a valuable source of data for researchers interested in geostatistical ore reserve estimation.