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    A Lognormal Distribution of Metal Resources

    Singer Donald A.

    Singer Donald A., 2011. A Lognormal Distribution of Metal Resources. Earth Science, 36(2): 201-208. doi: 10.3799/dqkx.2011.021
    Citation: Singer Donald A., 2011. A Lognormal Distribution of Metal Resources. Earth Science, 36(2): 201-208. doi: 10.3799/dqkx.2011.021

    doi: 10.3799/dqkx.2011.021

    A Lognormal Distribution of Metal Resources

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    • Fig.  1.  The copper content of porphyry Cu, reduced facies Cu, carbonate-hosted igneous related, volcanic-hosted massive sulfide felsic-related, and volcanic-hosted massive sulfide mafic-related deposits plotted against each type's straight line representing its standard normal distribution

      Table  1.   Copper content distributions by deposit type and tests of lognormality. Mean metric tons of contained copper (log10 data), standard deviation (log10 data), median observed copper content of all deposits, Shapiro-Wilk goodness-of-fit probability of lognormal distribution, number of deposits with reported grade, and total number of deposits with reported tonnage (in thousands t)

      Deposit type Mean St. dev. Median Cu (kt) Prob. Number deposits Total number deposits
      CAam 4.355 1 0.941 2 0 0.797 9 132
      CAig 4.315 4 0.876 4 0 0.892 86 187
      FeOxideCuAu 5.644 4 0.779 4 376 0.819 32 36
      Kipushi 5.438 5 0.894 1 480 0.668 8 8
      MLig 4.854 3 0.735 3 0 0.587 12 38
      MLme 4.207 3 0.761 1 0 0.296 5 12
      PorCu 6.008 6 0.703 1 1 030 0.391 422 422
      RedbedCu 4.494 0 0.804 0 21 0.030 33 33
      Reduced Cu 5.819 9 0.898 3 500 0.647 62 62
      Revett Cu 5.224 0 0.931 5 125 0.934 14 14
      SedHstCu 5.076 4 0.920 1 120 0.952 31 31
      SHam 5.107 2 1.133 5 0 0.983 7 25
      SHig 4.503 4 0.822 4 0 0.487 13 32
      SSPb 3.830 8 1.625 7 0 0.042 5 22
      VMSBimodal 4.376 7 0.929 2 26 0.666 267 272
      VMSFelsic 4.480 2 0.920 0 36 0.001 411 421
      VMSMafic 4.061 3 0.983 6 11 0.066 174 175
      下载: 导出CSV

      Table  2.   Zinc content distributions by deposit type and tests of lognormality. Mean metric tons of contained zinc (log10 data), standard deviation (log10 data), median observed zinc content of all deposits, Shapiro-Wilk goodness-of-fit probability of lognormal distribution, number of deposits with reported grade, and total number of deposits with reported tonnage (in thousands t)

      Deposit type Mean St. dev. Median Zn (kt) Prob. Number deposits Total number deposits
      CAam 5.648 1 0.756 7 498 0.338 128 132
      CAig 5.359 4 0.917 6 308 0.002 185 187
      CAme 5.372 5 0.744 5 128 0.378 7 7
      Kipushi 5.765 9 1.226 1 5 0.335 4 8
      MLig 5.609 9 0.876 0 354 0.926 38 38
      MLme 5.169 1 1.025 0 96 0.888 12 12
      SHam 6.334 1 0.674 9 1 600 0.924 25 25
      SHig 5.757 5 0.994 9 644 0.511 30 32
      SSPb 4.628 2 1.543 8 8 0.264 16 22
      VMSBimodal 4.716 6 0.923 1 30.5 0.407 217 272
      VMSFelsic 5.043 7 0.892 7 75 0.000 349 421
      VMSMafic 4.325 7 0.733 8 0 0.383 58 175
      下载: 导出CSV

      Table  3.   Lead content distributions by deposit type and tests of lognormality. Mean metric tons of contained lead (log10 data), standard deviation (log10 data), median observed lead content of all deposits, Shapiro-Wilk goodness-of-fit probability of lognormal distribution, number of deposits with reported grade, and total number of deposits with reported tonnage (in thousands t)

      Deposit type Mean St. dev. Median Pb (kt) Prob. Number deposits Total number deposits
      CAam 5.176 4 0.822 2 146 0.647 121 132
      CAig 5.181 3 0.857 3 130 0.230 166 187
      CAme 5.044 8 0.801 0 30 0.243 6 7
      Kipushi 5.291 9 1.161 9 275 0.123 6 8
      MLig 5.372 9 0.885 2 169 0.838 34 38
      MLme 4.852 3 0.830 0 45 0.420 11 12
      SHam 5.823 6 0.718 4 592 0.482 25 25
      SHig 5.428 0 1.041 9 721 0.066 32 32
      SSPb 5.167 4 0.852 6 204 0.691 22 22
      VMSBimodal 4.058 6 0.844 2 0 0.006 77 272
      VMSFelsic 4.497 6 0.982 0 7 0.005 273 421
      VMSMafic 3.564 9 1.018 0 0 0.636 6 13 175
      下载: 导出CSV

      Table  4.   Silver content distributions by deposit type and tests of lognormality. Mean metric tons of contained silver (log10 data), standard deviation (log10 data), median observed silver content of all deposits, Shapiro-Wilk goodness-of-fit probability of lognormal distribution, number of deposits with reported grade, and total number of deposits with reported tonnage (in t)

      Deposit type Mean St. dev. Median Ag (t) Prob. Number deposits Total number deposits
      CAam 2.275 0 0.759 8 0 0.875 58 132
      CAig 2.651 2 0.939 1 144 0.147 138 187
      CAme 2.045 0 0.927 6 26 0.210 5 7
      FeOxideCuAu 1.918 2 1.155 2 0 0.621 10 36
      Kipushi 2.692 5 0.968 3 193 0.970 6 8
      MLig 2.688 5 0.951 3 106 0.928 26 38
      MLme 2.588 2 0.702 0 32 0.565 6 12
      PorCu 2.897 5 0.692 6 0 0.584 172 422
      RedbedCu 1.544 1 1.142 0 0 0.698 10 33
      Reduced Cu 2.678 0 1.053 5 0 0.274 16 62
      Revett Cu 2.807 3 0.756 3 140 0.097 8 14
      SedHstCu 1.797 9 0.988 4 0 0.153 7 31
      SHam 3.067 3 0.783 8 277 0.540 18 25
      SHig 2.760 3 0.999 9 786 0.056 28 32
      SSPb 2.041 5 0.904 8 2 0.344 11 22
      VMSBimodal 1.754 9 0.936 8 10 0.816 172 272
      VMSFelsic 2.051 3 0.958 1 32 0.003 300 421
      VMSMafic 1.442 0 1.058 8 0 0.399 70 175
      下载: 导出CSV

      Table  5.   Gold content distributions by deposit type and tests of lognormality. Mean metric tons of contained gold (log10 data), standard deviation (log10 data), median observed gold content of all deposits, Shapiro-Wilk goodness-of-fit probability of lognormal distribution, number of deposits with reported grade, and total number of deposits with reported tonnage (in t)

      Deposit type Mean St. dev. Median Au (t) Prob. Number deposits Total number deposits
      CAam 0.985 7 0.402 7 0 0.424 3 132
      CAig 0.676 6 1.026 3 0 0.002 70 187
      FeOxideCuAu 1.313 5 0.797 8 12 0.563 27 36
      MLig 0.408 9 0.766 9 0 0.039 7 38
      PorCu 1.678 6 0.712 5 12 0.631 256 422
      SHam 0.755 8 0.444 6 0 0.695 4 25
      SHig 0.662 0 1.190 3 0 0.135 14 32
      VMSBimodal 0.309 1 0.956 7 0 0.093 158 272
      VMSFelsic 0.430 6 0.980 7 1 0.000 279 421
      VMSMafic 0.058 6 1.042 8 0 0.121 72 175
      下载: 导出CSV

      Table  6.   Molybdenum, cobalt, Nb2O5, and REE2O3 content distributions by deposit type and tests of lognormality. Mean metric tons of contained molybdenum (median observed Mo content in all deposits), cobalt (median observed cobalt content in all deposits), Nb2O5, and REE2O3 (log10 data), standard deviation (log10 data), Shapiro-Wilk goodness-of-fit probability of lognormal distribution, number of deposits with reported grade, and total number of deposits with reported tonnage (in thousands t)

      Deposit type Mean Mo
      (median Mo (kt))
      Mean Co
      (median Co (kt))
      Mean Nb2O3
      (median Nb2O3 (kt))
      Mean REE2O3
      (median REE2O3 (kt))
      St. dev. Prob. Number deposits Total number deposits
      PorCu 4.618
      (28)
      0.765 4 0.592 228 422
      Reduced Cu 5.088 1
      (0)
      0.800 4 0.633 15 62
      Carbonatite 5.325 8
      (0)
      1.102 5 0.737 39 55
      Carbonatite 5.558 9
      (68)
      1.079 3 0.925 35 55
      下载: 导出CSV
    • Ahrens, L.H., 1954. The log-normal distribution of the elements (a fundamental law of geochemistry and its subsidiary). Geochimica et Cosmochimica Acta, 5: 49-73. doi: 10.1016/0016-7037(54)90040-X
      Aitchison, J., Brown, J.A.C., 1963. The lognormal distribution. Cambridge University Press, London, 177.
      Allais, M., 1957. Method of appraising economic prospects of mining exploration over large territories—Algerian Sahara case study. Management Science, 3(4): 285-347. doi: 10.1287/mnsc.3.4.285
      Berger, V.I., Singer, D.A., Orris, G.J., 2009. Carbonatites of the world, explored deposits of Nb and REE: database and grade and tonnage models. U.S. Geological Survey Open-File Report 2009-1139, 17 and database. http://pubs.usgs.gov/of/2009/1139/.
      Cox, D.P., Lindsey, D.A., Singer, D.A., et al., 2003. Sediment-hosted copper deposits of the world—deposit models and database. Revised 2007. U.S. Geological Survey Open-File Report 2003-107, v. 1.3. http://pubs.usgs.gov/of/2003/of03-107/.
      Cox, D.P., Singer, D.A., 2007. Descriptive and grade-tonnage models and database for iron oxide Cu-Au deposits. U.S. Geological Survey Open-File Report 2007-1155. http://pubs.usgs.gov/of/2007/1155/.
      Griffiths, J.C., Singer, D.A., 1973. Size, shape, and arrangement of some uranium ore bodies. 11th International Symposium on Computer Applications in the Mineral Industry, B82-B110.
      Matheron, G., 1959. Remarques sur la loi de Lasky. Chronique des Mines d'Outre-Mer et de la Recherche Miniere, 27e annee, (282): 463-465.
      Mosier, D.L., Berger, V.I., Singer, D.A., 2009. Volcanogenic massive sulfide deposits of the world—database and grade and tonnage models. U.S. Geological Survey Open-File Report 2009-1034. http://pubs.usgs.gov/of/2009/1034/.
      Rasumovsky, N.K., 1940. Distribution of metal values in ore deposits. Acad. Sci. Comptes Rendus (Doklady) U.R.S.S., 28: 814-816. http://www.researchgate.net/publication/312448454_Distribution_of_metal_values_in_ore_deposits
      Sharp, W.E., 1976. A log-normal distribution of alluvial diamonds with an economic cutoff. Economic Geology, 71: 648-655. doi: 10.2113/gsecongeo.71.3.648
      Singer, D.A., 1993. Basic concepts in three-part quantitative assessments of undiscovered mineral resources. Nonrenewable Resources, 2(2): 69-81. doi: 10.1007/BF02272804
      Singer, D.A., Berger, V.I., Moring, B.C., 2008. Porphyry copper deposits of the world: database, map, and grade and tonnage models, 2008. U.S. Geological Survey Open-File Report 2008-1155. http://pubs.usgs.gov/of/2008/1155/.
      Singer, D.A., Berger, V.I., Moring, B.C., 2009. Sediment-hosted zinc-lead deposits of the world: database and grade and tonnage models. U.S. Geological Survey Open-File Report 2009-1252. http://pubs.usgs.gov/of/2009/1252/.
      Singer, D.A., Menzie, W.D., 2010. Quantitative mineral resource assessments—an integrated approach. Oxford University Press, New York, 232.
      Slichter, L.B., Dixon, W.J., Meyer, G.H., 1962. Statistics as a guide to prospecting. In: Proc. Symposium Mathematical and Computer Applications in Mining and Exploration. College of Mines, University of Arizona, Tucson, AZ, F1-1-F-1-27.
      Stuart, A., Ord, J.K., 1991. Kendall's advanced theory of statistics, v. 2, 5th ed. . Oxford University Press, New York, 1323.
      Zhang, Q.L., Shoji, Tetsuya, Kaneda, Hiroaki, 2004. Grade-tonnage models of copper deposits in China. Shigen-to-Sozai, The Mining and Materials Processing Institute of Japan, 120: 19-24.
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    出版历程
    • 收稿日期:  2010-07-15
    • 刊出日期:  2011-03-01

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