Classification of ore reserves/resources based on geostatistical methods

"As shortage in the supply of mineral commodities become more probable, there is an increasing need for reliable and comparable reserve/resource data. It is therefore necessary to standardize the traditional classification procedure by quantifying the three basic criteria in resource evaluation: economic feasibility, geologic assurance and recovery. For the portion of fairly well documented deposits and as far as their geologic parameters are concerned, geostatistical methods can considerably improve the quality of ore classification. In respect of economic feasibility and recovery, approved geostatistical methods can be introduced directly into the classification procedure. The concept of geologic assurance, however, requires a new interpretation in terms of geostatistical error spread. As the ""risk"" in estimating an ore parameter is also a function of the respective block size, it is reasonable to define not only upper limits for the risk intervals for each class of uncertainty, but also block dimensions which reflect the typical stage of planning associated with the different ore categories. An algorithm has been developed to block out areas inside a mine or a large panel which satisfies the constraints of an ore category in respect of the risk intervals of a parameter and in respect of their size. The method has been computerized and is demonstrated on a massive copper-nickel deposit.IntroductionFacing an uncertain future with respect to the demand and supply of mineral commodities, both governmental authorities and the mining industries show an increasing interest in a useful framework for the assessment and classification of the remaining mineral resources"". This is reflected by the recently published appraisal and classification scheme of the United Nations as well as by the new or revised classification systems of the USA; Canada or Australia. Moreover there are various classification schemes which are currently discussed in major mining companies."