Title: Geostatistics for mineral deposit grade assessment

Abstract

Geostatistics aims at providing quantitative descriptions of regionalized variables distributed in space or in time and space. It is one important tool where spatial correlation is the basis for mineral deposit modelling and evaluation. It quantifies geological interpretation and reinforces it when used in estimation. Over the years, the subject of geostatistics has progressed from linear, nonlinear, non-parametric, conditional simulation, multi-point to machine learning. Parallel to these advancements, a need has been felt for an appropriate link between geology and geostatistics in geostatistical modelling study. Mode of incorporating geology into geostatistics is to perform geostatistical modelling with respect to deposit geology, controls of mineralisation, and geological domains. It must be emphasized that it is geology that governs the distribution of geologically complex grades and thus should guide the estimation modelling and not the reverse. Despite wide dissemination of geostatistics and its growing acceptance in exploration and mining, there are certain issues that need careful attention, namely, (i) considerable increase in the assumptions of underlying theories; (ii) growing complexity in the mathematical treatment of these theories; and (iii) less geological considerations in the estimation procedure. From 1960 to the present, two key issues that influenced the progress of geostatistics in mineral grade assessment include (i) clarification and dissemination of geostatistical concepts and theories to the practitioners; and (ii) identification and definition of unsolved problems in evolving geo-mathematical modelling techniques. Five live Iron ore deposits located in the western limb of the Singhbhum-Keonjhar-Bonai iron ore belt, India have been studied. Spatially distributed estimation maps generated retain nonlinearity and spatial heterogeneity of the original Fe data values. Geostatistics, thus, provide an improved dimension in mineral grade assessment and should be used invariably by all exploration agencies, mining and mineral industries.