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Lead–Zinc–Silver Metallogenic Prediction Based on GIS

  • Yan Sun
  • Xunlian Wang
  • Jianping Chen
  • Xiaoling Liu
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 216)

Abstract

Tuotuo River region lies in one of the most important metallogenic belts in China—Northwest Sanjiang Metallogenic Belt, thus Tuotuo River region can be of very high metal mineral potential. In this research, multisource data sources including geological, geochemical, geophysical, and remotely sensed images were integrated for mineral potential analysis with GIS technology. Using Weights of Evidence method, the metallogenic potential of this area was studied. Six level I, seven level II and nine level III lead–zinc–silver prospective belts were delineated with 83 % of known mineral deposits in them. Because of the belts’ similar metallogenic condition with known mineral deposits, they form the most promising zones for new mineral deposits, deserving more and adequate attention in future exploration.

Keywords

Sanjiang metallogenic belt Lead–zinc-silver GIS Weights of evidence Minerogenic prediction 

Notes

Acknowledgments

Sponsored by a GIS-Based Study on Special Education School Distribution of Beijing.

References

  1. 1.
    Agterberg FP, Bonham-Carter GF, Wright DF (1990) Statistical pattern integration for mineral exploration. In: Gaal G, Merriam DF (eds) Computer applications in resource estimation: predictions and assessment for metals and petroleum, vol 63. Pergamon, Oxford, pp 1–21Google Scholar
  2. 2.
    Bonham-Carter GF, Agterberg FP, Weight DF (1989) Weights of evidence modeling: a new approach to mapping mineral potential. In: Agterberg FP, Bonham-Carter GF (eds) Statistical applications in the earth science. Geological Survey of Canada. Paper 89–90:171–183Google Scholar
  3. 3.
    Deng Y, Qiu RS, Luo X (2007) Minerogenetic prediction based on the weight- of- evidence approach: a case study of the prediction of tungsten and tin deposits in Guangdong, China. Geol Bull Chin 26(9):1228–1234Google Scholar
  4. 4.
    Deng ZL, An YS, Wang QH et al (2005) 1:250,000 Tuotuo river regions geologic survey report. Xining, China 74:197–206Google Scholar
  5. 5.
    Hu WL, Lu RY, Gao HZ et al (1995) Deposit statistics prediction method procedure. Earth Sci 20(2):128–132Google Scholar
  6. 6.
    Liu SX, Xue LF, Qie RQ et al (2007) An application of GIS-based weights of evidence for gold prospecting in the northwest of Heilongjiang province. J Jilin Univ (Earth Sci Edn) 37(5):889–894Google Scholar
  7. 7.
    Wang GW, Chen JP (2008) Mineral resource prediction and assessment of copper multi-mineral deposit based on GIS technology in the north of Sanjiang region. Chin Earth Sci Front 15(4):027–032CrossRefGoogle Scholar
  8. 8.
    Yi PQ, Lu HF, Gu Y (2005) The preliminary analysis of exploration future for lead-zinc-silver poly metalic deposits in the Tuotuo river region. Eng Sci 7:292–295,310Google Scholar
  9. 9.
    Yi PQ, Wang YK, Gu Y (2001) A preliminary study on multi-metal mineralizing patterns in Tuotuo river region. Qinghai Guotu Jinglue 1:35–38Google Scholar
  10. 10.
    You YH, Yang JZ, Hu M et al (2006) Application of prospecting-information contents method for mineogenetic prediction: a case study on prediction of lead-zinc-copper deposit in western Wudang area. Contrib Geol Miner Res Res 21(3):58–62Google Scholar
  11. 11.
    Zhu YS, Xiao KY et al (1997) Methodology of metallogenic prognosis, vol 23. Geology publish House, Beijing, pp 24–35Google Scholar

Copyright information

© Springer-Verlag London 2013

Authors and Affiliations

  • Yan Sun
    • 1
  • Xunlian Wang
    • 2
  • Jianping Chen
    • 2
  • Xiaoling Liu
    • 3
  1. 1.Beijing Union UniversityBeijingChina
  2. 2.China University of GeosciencesBeijingChina
  3. 3.Headmen Mining Rights Appraisal FirmBeijingChina

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