This dataset tabulates aggregated data for simulations of undiscovered copper resources in porphyry copper deposits that were done using the EMINERS computer program (Duval, J.S., 2012, Version 3.0 of EMINERS—Economic Mineral Resource Simulator: U.S. Geological Survey Open-File Report 2004–1344, http://pubs.usgs.gov/of/2004/1344) as part of a global mineral resource assessment. The data in this table are the regional totals of the 4,999 sorted and randomized totals from the child entities Simulation results_sorted and Simulation results_randomized. These data are used as input for the Summary statistics by region.csv child item..

This dataset tabulates sorted simulation results for amounts of copper in metric tons. The data are output from the EMINERS computer program (Duval, J.S., 2012, Version 3.0 of EMINERS—Economic Mineral Resource Simulator: U.S. Geological Survey Open-File Report 2004–1344, http://pubs.usgs.gov/of/2004/1344) that were copied into a worksheet. The program was run with the input tabulated in the related worksheet Permissive tracts and input data

This dataset tabulates sorted simulation results for amounts of copper in metric tons. The data are output from the EMINERS computer program (Duval, J.S., 2012, Version 3.0 of EMINERS—Economic Mineral Resource Simulator: U.S. Geological Survey Open-File Report 2004–1344, http://pubs.usgs.gov/of/2004/1344) that were copied into a worksheet. The program was run with the input tabulated in the related worksheet Permissive tracts and input data

This dataset tabulates input data for simulations of undiscovered copper resources in porphyry copper deposits that were done using the EMINERS computer program (Duval, J.S., 2012, Version 3.0 of EMINERS—Economic Mineral Resource Simulator: U.S. Geological Survey Open-File Report 2004–1344, http://pubs.usgs.gov/of/2004/1344) as part of a global mineral resource assessment. The input data consist of information for 163 permissive tracts for porphyry copper deposits in 7 world regions. A GIS of the permissive tracts and selected data are available in Dicken, C.L., Dunlap, Pamela, Parks, H.L., Hammarstrom, J.M., and Zientek, M.L., 2016, Spatial database for a global assessment of undiscovered copper resources: U.S. Geological Survey Scientific Investigations Report 2010–5090–Z, 29 p., and GIS data, available at http://dx.doi.org/10.3133/sir20105090Z. EMINERS input consists of an identifier for each run, estimates of numbers of undiscovered mineral deposits, and selection of an appropriate grade and tonnage model.

This dataset tabulates input data for simulations of undiscovered copper resources in porphyry copper deposits that were done using the EMINERS computer program (Duval, J.S., 2012, Version 3.0 of EMINERS—Economic Mineral Resource Simulator: U.S. Geological Survey Open-File Report 2004–1344, http://pubs.usgs.gov/of/2004/1344) as part of a global mineral resource assessment. The input data consist of information for 163 permissive tracts for porphyry copper deposits in 7 world regions. A GIS of the permissive tracts and selected data are available in Dicken, C.L., Dunlap, Pamela, Parks, H.L., Hammarstrom, J.M., and Zientek, M.L., 2016, Spatial database for a global assessment of undiscovered copper resources: U.S. Geological Survey Scientific Investigations Report 2010–5090–Z, 29 p., and GIS data, available at http://dx.doi.org/10.3133/sir20105090Z. EMINERS input consists of an identifier for each run, estimates of numbers of undiscovered mineral deposits, and selection of an appropriate grade and tonnage model.

This dataset tabulates randomized simulation results for amounts of copper in metric tons in 163 permissive tracts for undiscovered porphyry copper deposits. The data from the child item Simulation results_sorted.csv for each permissive are randomized to allow aggregation of regional and global data using an assumption of statistical independence. This was done by generating a column of 4,999 random numbers and resorting the 4,999 sorted simulations by those random numbers. The randomized distributions for each permissive tract in a region were then summed to compute regional and global totals. For an explanation of aggregation assumptions and underlying mathematics, see Schuenemeyer, J.H., Zientek, M.L, and Box, S.E., 2011, Global mineral resource assessment – Aggregation of estimated numbers of undiscovered deposits – an R-script with an example from the Chu Sarysu Basin, Kazakhstan: U.S. Geological Survey Scientific Investigations Report 2010-5090-B, 13 p., accessed October 10, 2011, at https://pubs.usgs.gov/sir/2010/5090/b/.

This dataset tabulates randomized simulation results for amounts of copper in metric tons in 163 permissive tracts for undiscovered porphyry copper deposits. The data from the child item Simulation results_sorted.csv for each permissive are randomized to allow aggregation of regional and global data using an assumption of statistical independence. This was done by generating a column of 4,999 random numbers and resorting the 4,999 sorted simulations by those random numbers. The randomized distributions for each permissive tract in a region were then summed to compute regional and global totals. For an explanation of aggregation assumptions and underlying mathematics, see Schuenemeyer, J.H., Zientek, M.L, and Box, S.E., 2011, Global mineral resource assessment – Aggregation of estimated numbers of undiscovered deposits – an R-script with an example from the Chu Sarysu Basin, Kazakhstan: U.S. Geological Survey Scientific Investigations Report 2010-5090-B, 13 p., accessed October 10, 2011, at https://pubs.usgs.gov/sir/2010/5090/b/.

Porphyry copper deposits are the world's primary source of copper and can also host a variety of secondary commodities identified as critical by the U.S. Geological Survey (U.S. Geological Survey, 2022). These deposits occur primarily along convergent plate margins, and their metal association and geochemical characteristics are reflective of whether the deposit formed in continental/island arc, back-arc, or syn- to post-collisional environments (e.g., Hofstra and others, 2021). Based on this association, understanding the location, age, and endowment of global porphyry deposits can be leveraged to identify prospective regions for discovery of new porphyry deposits along these ancient margins. This data release is a compilation and update from previously published global and regional datasets of porphyry copper deposits and prospects. The data sheet includes deposit names and their location, age (if known, and including analytical method), deposit classification based on Hofstra and others (2021), interpreted tectonic origin, and grade-tonnage compiled from public databases where available. The final spreadsheet represents the most up-to-date published information of global porphyry copper deposits and prospects as of Spring 2024. References Hofstra, A., Lisitsin, V., Corriveau, L., Paradis, S., Peter, J., Lauzière, K., Lawley, C., Gadd, M., Pilote, J., Honsberger, I., Bastrakov, E., Champion, D., Czarnota, K., Doublier, M., Huston, D., Raymond, O., VanDerWielen, S., Emsbo, P., Granitto, M., and Kreiner, D., 2021, Deposit classification scheme for the Critical Minerals Mapping Initiative Global Geochemical Database: U.S. Geological Survey Open-File Report 2021–1049, 60 p., https://doi.org/ 10.3133/ ofr20211049. U.S. Geological Survey, 2022, 2022 Final List of Critical Minerals: Federal Register Document 2022-04027, p. 10381-10382. (available at https://www.federalregister.gov/documents/2022/02/24/2022-04027/2022-final-list-of-critical-minerals).

This dataset tabulates summary statistics for estimates of amounts of copper in undiscovered porphyry copper deposits by world region and for the globe. Data re reported by region, by aggregation method (randomized and sorted), and by selected statistics. These include quantiles, means, standard deviations, standard error of the mean , and Upper and Lower 95% of the mean.

This dataset tabulates summary statistics for estimates of amounts of copper in undiscovered porphyry copper deposits by world region and for the globe. Data re reported by region, by aggregation method (randomized and sorted), and by selected statistics. These include quantiles, means, standard deviations, standard error of the mean , and Upper and Lower 95% of the mean.