DATA AVAILABILITY AND QUALITY – A TALE OF TWO ASSESSMENTS

The Pacific margins of Russia and Canada were quantitatively assessed for porphyry Cu resources using the USGS three-part form of assessment. These regions represent assessment “end members” that illustrate how data availability and quality affect mineral resource assessment results. Small-scale data compilations of mineral occurrences, geology, and geodynamics were available for the Russian assessment. A wide variety of large-scale, high-quality data, readily accessible in the literature and online, were available for the Canadian assessment.

Data for the Russian Far East indicate the presence of 2 non-producing deposits and at least 70 prospects, the most significant of which are hosted by Late Jurassic through late Tertiary continental- margin-arc and island-arc terranes of the Uda-Murgal, Okhotsk-Chukotka, Khingan-Okhotsk, East Sikhote-Alin, and Kamchatka magmatic belts. Data for the Canadian Cordillera indicate the presence of 50 past- and presently-producing deposits and at least 280 prospects that are hosted by Middle Triassic to late Tertiary continental- margin-arc, island-arc, and mixed-arc terranes of the Intermontane, Coast, Insular tectonic belts.

Data availability and quality produced markedly different assessment results for the two regions. The Russian assessment is characterized by permissive tracts that are both spatially and temporally coarse, which may include questionable geologic settings, and non-permissive rocks that could not be discriminated from otherwise permissive map units. Deposits and prospects could not be classified into sub-types and were difficult to rank. Estimates of undiscovered resources have relatively higher uncertainties. Conversely, the Canadian assessment is generally of higher resolution, characterized by finer tracts that are based on well-described and precisely dated permissive rocks. Deposits and prospects were classified into subtypes and ranked, permitting the identification and assessment of calc-alkaline and alkaline deposit subtypes using custom grade and tonnage models. Estimates of undiscovered resources have relatively lower uncertainties.