Effect of size-biased sampling on resource predictions from the three-part method for quantitative mineral resource assessment—A case study of the gold mines in the Timmins-Kirkland Lake area of the Abitibi greenstone belt, Canada:

Abstract

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Predicting grade-tonnage characteristics of undiscovered mineralisation: application of the USGS Three-part Undiscovered Mineral Resource Assessment to the Sandstone Greenstone Belt of the Yilgarn Block, Western Australia

“…This model is deemed to now be dated due to significant new discoveries and additional brownfields resource growth that have taken place between the early 1980s and present day. This period resulted in a suite of new discoveries within the Yilgarn Block (Figure 9), as well as much of the rest of the world; including Canada (Ellefsen 2019) and China (Zhang et al 2015). As a result, this study utilises several updated Yilgarn-specific grade-tonnage models, based on data from 346 deposits compiled by MinEx Consulting as part of a larger global deposit database.…”

“…That is, aggregation of deposits within 1.6 km was conducted in line with Singer and Menzie (2010), under the assumption that these deposits likely belong to the same system and Although the MinEx database represents a thorough review of historic production, resources and reserves, many of the gold deposits featured in the grade-tonnage models remain uneconomic to mine. These deposits are included to provide a comprehensive distribution of potential deposit sizes, since many factors beyond grade and tonnage can influence whether a deposit is developed into a mine (such as depth, commodity price, mineral policy and land access), meaning total historic production of mines is not necessarily equal or representative of future production (Ellefsen 2019). At times, deposits are reported under different names and occasionally production has been aggregated into a broad mining camp.…”