• 中国出版政府奖提名奖

    中国百强科技报刊

    湖北出版政府奖

    中国高校百佳科技期刊

    中国最美期刊

    Volume 26 Issue 2
    Mar.  2001
    Turn off MathJax
    Article Contents
    Donald A. Singer, 2001. SOME SUGGESTED FUTURE DIRECTIONS OF QUANTITATIVE RESOURCE ASSESSMENTS. Earth Science, 26(2): 152-156.
    Citation: Donald A. Singer, 2001. SOME SUGGESTED FUTURE DIRECTIONS OF QUANTITATIVE RESOURCE ASSESSMENTS. Earth Science, 26(2): 152-156.

    SOME SUGGESTED FUTURE DIRECTIONS OF QUANTITATIVE RESOURCE ASSESSMENTS

    • Received Date: 2001-02-15
    • Publish Date: 2001-04-25
    • Future quantitative assessments will be expected to estimate quantities, values, and locations of undiscovered mineral resources in a form that conveys both economic viability and uncertainty associated with the resources. Historically, declining metal prices point to the need for larger deposits over time. Sensitivity analysis demonstrates that the greatest opportunity for reducing uncertainty in assessments lies in lowering uncertainty associated with tonnage estimates. Of all errors possible in assessments, those affecting tonnage estimates are by far the most important. Selecting the correct deposit model is the most important way of controlling errors because the dominance of tonnage-deposit models are the best known predictor of tonnage. Much of the surface is covered with apparently barren rocks and sediments in many large regions. Because many exposed mineral deposits are believed to have been found, a prime concern is the presence of possible mineralized rock under cover. Assessments of areas with resources under cover must rely on extrapolation from surrounding areas, new geologic maps of rocks under cover, or analogy with other well-explored areas that can be considered training tracts. Cover has a profound effect on uncertainty and on methods and procedures of assessments because geology is seldom known and geophysical methods typically have attenuated responses. Many earlier assessment methods were based on relationships of geochemical and geophysical variables to deposits learned from deposits exposed on the surface-these will need to be relearned based on covered deposits. Mineral-deposit models are important in quantitative resource assessments for two reasons: (1) grades and tonnages of most deposit types are significantly different, and (2) deposit types are present in different geologic settings that can be identified from geologic maps. Mineral-deposit models are the keystone in combining the diverse geoscience information on geology, mineral occurrences, geophysics, and geochemistry used in resource assessments and mineral exploration. Grade and tonnage models and development of quantitative descriptive, economic, and deposit density models will help reduce the uncertainty of these new assessments.

       

    • loading
    • [1]
      Allais M. Method of appraising economic prospects of mining exploration over large territories: Algerian Sahara case study[J]. Management Science, 1957, 3 (4): 285~347.
      [2]
      Singer D A, Kouda R. Examining risk in mineral exploration[J]. Natural Resources Research, 1999, 8 (2): 111~122.
      [3]
      Singer D A. World class base and precious metal deposits—aquantitative analysis[J]. Economic Geology, 1995, 90 (1): 88~104. doi: 10.2113/gsecongeo.90.1.88
      [4]
      Cox D P, Singer D A. Mineral deposit models[J]. U. S. Geological Survey Bulletin, 1986, 1693: 379.
      [5]
      Bliss J D. Developments in mineral deposit modeling[J]. U. S. Geological Survey Bulletin, 1992, 2004: 168.
      [6]
      Bliss J D, Menzie W D. Spatial mineral-deposit models and the prediction of undiscovered mineral deposits [A]. In: Kirkham RV, Sinclair RV, Thorpe W D, et al, eds. Min eral deposit modeling[C]. Geological Association Canada Special Paper, 1993, 40: 693~706.
      [7]
      Wilford J. Thematic mapping and three-dimensional modeling of the regolith for mineral and environmental assessment [M/CD ]. 31th International Geologic Congress. Brazil: [s. n. ], 2000.
      [8]
      Berger BR, Drew L J, Singer D A. Quantifying mineral-de-posit models for resource assessment [A ]. In: ído L, Korpás L, McCammon R B, etal, eds. Deposit modeling and mining-induced environmental risks [C ]. Geologica Hungarica Series Geologica, 1999, 24: 41~54.
    • 加载中

    Catalog

      通讯作者: 陈斌, bchen63@163.com
      • 1. 

        沈阳化工大学材料科学与工程学院 沈阳 110142

      1. 本站搜索
      2. 百度学术搜索
      3. 万方数据库搜索
      4. CNKI搜索

      Figures(1)

      Article views (3603) PDF downloads(12) Cited by()
      Proportional views

      /

      DownLoad:  Full-Size Img  PowerPoint
      Return
      Return