Introduction to Matheronian Geostatistics

INTRODUCTION The preceding chapters have brought us to a point in the mineral appraisal process where the composited sample values can now be used to estimate the grade and tonnage of the total mineral deposit. There are many techniques whereby drill hole composites and/or other sample data are used to assign grade and estimates to the surrounding rock. Matheron and his students have properly called such techniques extension functions. Before embarking upon a detailed discussion of extension functions, it is necessary that we take time to consider the concept of geostatistics as advocated by George Matheron who developed the "Theory of Regionalized Variables," which he published in 1962 (Matheron, 1971). The concept of regionalized variables has important application in the techniques of mineral appraisal. The position or location of a mineral sample within a deposit can be almost as important as its value. Geostatistics, when defined as "the application of the theory of regionalized variables* to the study of mineralized volumes of rock," takes into consideration the position as well as the magnitude of the value of the sample. The principles of geostatistics, as outlined by Matheron, represent a major step forward in the mineral evaluation process, because they provide a sound theoretical and practical basis for quantifying the geological concepts of (1) area of influence of a sample, (2) the continuity or lack of continuity of mineralization within the ore body, and (3) the lateral changes in mineralization according to the trend direction of an ore body and its orthogonal components; or in other words, a measure of the anisotropy of the deposit. Royle (1971) has defined the objects of geostatistic as being: "1. To estimate the most likely value of blocks of ore, or the values of the whole deposit; and 2. to estimate the errors of such estimates. This latter is important as, in addition to providing a check on unwarranted optimism, it shows where more valuation work may be needed." Because of the great importance of these concepts in mineral evaluation, an introduction into the theory of regionalized variables, and the study of a practical approach to its application is outlined here. REGIONALIZED VARIABLES VS. RANDOM VARIABLES Classical statistics, as discussed in earlier chapters, grew out of the study and application of probability theory. Probability is concerned with the outcome of random events and therefore classical statistics is built upon the theory of random variables, i.e., the probability of independent events. The validity of most statistical inferences depends upon sample randomness being assured for unbiased results. Where independent events cannot be assumed the results of statistical inference becomes suspect. On the other hand, geostatistics is concerned with variables that have position in space as well as magnitude, hence the term regionalized variables. Mineral deposits are not the only field to which the theory of regionalized variables is applicable. Many natural phenomena that demonstrate a relationship between change in magnitude and position in space are amenable to application of geostatistical techniques. Mineral deposits vary greatly in their geosta-