Integration of Grades, Tonnages, Number of Deposits, and Economic Effects

Singer, Donald; Menzie, W David

doi:10.1093/oso/9780195399592.003.0012

Chapter

1489 Integration of Grades, Tonnages, Number of Deposits, and Economic Effects

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https://doi.org/10.1093/oso/9780195399592.003.0012

Pages

148–158

Published:

August 2010

Abstract

Now that all of the fundamental parts of a quantitative mineral resource assessment have been discussed, it is useful to reflect on why all of the work has been done. As mentioned in chapter 1, it is quite easy to generate an assessment of the “potential” for undiscovered mineral resources. Aside from the question of what, if anything, “potential” means, there is the more serious question of whether a decision-maker has any use for it. The three-part form of assessment is part of a system designed to respond to the needs of decision-makers. Although many challenging ideas are presented in this book, it has a different purpose than most academic reports. This book has the same goal as Allais, (1957)—to provide information useful to decision makers. Unfortunately, handing a decision-maker a map with some tracts outlined and frequency distributions of some tonnages and grades along with estimates of the number of deposits that might exist along with their associated probabilities is not really being helpful—these need to be converted to a language understandable to others. This chapter summarizes how these various estimates can be combined and put in more useful forms. If assessments were conducted only to estimate amounts of undiscovered metals, we would need contained metal models and estimates of the number of undiscovered deposits. Grades are simply the ratio of contained metal to tons of ore (chapter 6), so contained metal estimates are available for each deposit. In the simplest of all cases, one could estimate the expected number of deposits with equation 8.1 (see chapter 8) and multiply it by the expected amount of metal per deposit, such as the 27,770 tons of copper in table 9.1, to make an estimate of the expected amount of undiscovered metal. As pointed out in chapter 1, expected amounts of resources or their values can be very misleading because they provide no information about how uncommon the expected value can be with skewed frequency distributions that are common in mineral resources; that is, uncertainty is ignored.

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Contents

1489 Integration of Grades, Tonnages, Number of Deposits, and Economic Effects

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