So much work has been done in recent years using geostatistics to solve practical problems that we no longer have to apologise for nor justify the method. The method is as good as the practitioner, which goes, after all, for any technical application. There have been enough case studies now to show that almost any orebody, simple or complex in structure, which has a definable spatial continuity, will be amenable to geostatistical evaluation given that it is suitably sampled.

This book is different from most books written about geostatistics. The focus here is not on providing an analytical and deductive understanding. It does not attempt to explain the inner workings of its algorithms or exactly how a variogram is calculated and modeled, nor does it provide an exhaustive list of geostatistical algorithms for seismic-data integration.

The aim of this paper is to demonstrate the importance of using variography for grade interpolation in multielement environments and to illustrate how variography can assist in the understanding of geological controls on mineralisation.
Variography codes mineralisation continuity numerically and it is one of the first links between geology and mine planning, since it guides the choice of the interpolation technique. Owing to advances in computer technology and new visualisation techniques, semi-variogram analysis is becoming more of a routine procedure during both feasibility studies and on operating mines.

The intention of this paper is to provide the user with a few essential and handy hints for variogram analysis. So often one is faced with the task of analysing the spatial continuity of a data set or with the task of generating a resource model using geostatistical techniques. However, practical guidelines for completing these tasks are few and far between and, even though one may attend a geostatistics course, time lapses between exposure to geostatistical techniques and actual application of the techniques to real situations is generally large enough for the handy hints of variography to be lost in the never-never land of memories. <...>

In August 1882, the Morgan brothers recognised a mineral deposit, now known as the Mount Morgan Gold-Copper Deposit. The final production figures for the mine were 250 tonnes of gold and 360,000 tonnes of copper from 50 million tonnes of ore, making the average grades 4.99g/t gold and 0.72% copper.

The main developments during four decades of geostatistical applications on the Witwatersrand-type gold deposits are reviewed and critically compared with a view to highlighting the progress made to date. The basic techniques - from the preliminary borehole valuation of mining properties to the block estimating of ore reserves and foreseeable recoveries are analysed and the prospects for methodological improvements are discussed.

Since October 1975 and the first NATO ASl "Geostat - Roma 1975", there has not been an advanced workshop on geostatistics where experts from throughout the world could meet, teach and debate without the pressure of an ordinary professional conference. This second NATO ASI "Geostat - Tahoe 1983" was intended as a high-level teaching activity yet opened to all new ideas and contributions to the discipline of geostatistics. It was expected that the institute would bridge the gap since "Geostat - Roma 1975" and establish the state of the art of the discipline as of 1983 <...>

Although geologists have used statistical analysis in their research for many years, only recently has geostatistics, as a creative tool in the geosciences, received the attention it deserves. Even now many geologists are unaware of the tremendous power statistical methods offer. Today earth scientists can use summary statistics for large data bases, frequency distributions, sampling designs and problems, and applications of stochastic models and use them in dynamic ways for research and developm·ent.