This report presents an updated grade and tonnage model for tungsten skarn deposits. As a critical component of the U.S. Geological Survey’s three-part form of quantitative mineral resource assessment, robust grade and tonnage models are essential to transforming mineral resource assessments into effective tools for decision makers. Using the best data available at the time of publication, this represents the first attempt in nearly 30 years to capture current mineral inventory and cumulative production data for worldwide tungsten skarn deposits. The accuracy of modern assessments of undiscovered tungsten skarn resources is highly influenced by the use of current data on the distribution of the grades and tonnages of well-explored tungsten skarn deposits. Primary factors affecting the changes to these distributions in the model presented here compared with those of previous models are the inclusion of important deposits, especially those in China that had been omitted in previous models; expanded mineral inventories resulting from increased exploration; and changes to international reporting standards. These factors have resulted in dramatic increases in average ore tonnage and slight decreases in the average grade of tungsten skarn deposits compared with previous models. Large increases in contained metal are observed among many of the individual deposits incorporated within this model that were also included in previous tungsten skarn grade and tonnage models. This report also provides recommendations for input parameters related to grade and tonnage models to use with software tools designed to facilitate the three-part form of quantitative mineral resource assessments.
|Title||Grade and tonnage model for tungsten skarn deposits—2020 update|
|Authors||Carlin J. Green, Graham W. Lederer, Heather L. Parks, Michael L. Zientek|
|Publication Subtype||USGS Numbered Series|
|Series Title||Scientific Investigations Report|
|Record Source||USGS Publications Warehouse|
|USGS Organization||Eastern Mineral and Environmental Resources Science Center|