Geostatistical Approach to Integrated Modeling of Iron Mine for Evaluation of Ore Body

철광산의 광체 평가를 위한 지구통계학적 복합 모델링

  • Ahn, Taegyu (Department of Energy and Resources Engineering, Kangwon National University) ;
  • Oh, Seokhoon (Department of Energy and Resources Engineering, Kangwon National University) ;
  • Kim, Kiyeon (Department of Energy and Resources Engineering, Kangwon National University) ;
  • Suh, Baeksoo (Department of Energy and Resources Engineering, Kangwon National University)
  • 안태규 (강원대학교 에너지.자원공학과) ;
  • 오석훈 (강원대학교 에너지.자원공학과) ;
  • 김기연 (강원대학교 에너지.자원공학과) ;
  • 서백수 (강원대학교 에너지.자원공학과)
  • Received : 2012.10.18
  • Accepted : 2012.11.14
  • Published : 2012.11.30


Evaluation of three-dimensional ore body modeling has been performed by applying the geostatistical integration technique to multiple geophysical (electrical resistivity, MT) and geological (borehole data, physical properties of core) information. It was available to analyze the resistivity range in borehole and other area through multiple geophysical data. A correlation between resistivity and density from physical properties test of core was also analyzed. In the case study results, the resistivity value of ore body is decreased contrast to increase of the density, which seems to be related to a reason that the ore body (magnetite) includes heavy conductive component (Fe) in itself. Based on the lab test of physical properties in iron mine region, various geophysical, geological and borehole data were used to provide ore body modeling, that is electrical resistivity, MT, physical properties data, borehole data and grade data obtained from borehole data. Of the various geostatistical techniques for the integrated data analysis, in this study, the SGS (sequential Gaussian simulation) method was applied to describe the varying non-homogeneity depending on region through the realization that maintains the mean and variance. With the geostatistical simulation results of geophysical, geological and grade data, the location of residual ore body and ore body which is previously reported was confirmed. In addition, another highly probable region of iron ore bodies was estimated deeper depth in study area through integrated modeling.


Supported by : 기상청


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