• الصفحة الرئيسية
  • Comparison of original and weighted singularity indexin separation of Pb- Zn mineralized zone in the Haft Savaran district, Central Iran

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عنوان URL للمقالة


رقم المقالة : IJES-1801-1169 (R1) زيارة : 116 الصفحة: 160 - 170

10.30495/ijes.2019.665321

نوع المخطوط: ابحاث

Comparison of original and weighted singularity indexin separation of Pb- Zn mineralized zone in the Haft Savaran district, Central Iran

الموضوعات :

Feridon Ghadimi 1 , Massume Khavari 2

1 - Department of Mining Engineering, Arak University of Technology, Arak, Iran
2 - Department of Mining Engineering, Arak University of Technology, Arak, Iran

تاريخ الإرسال : 20 الثلاثاء , جمادى الأولى, 1439 تاريخ التأكيد : 02 السبت , شوال, 1439 تاريخ الإصدار : 25 الإثنين , رجب, 1440

الکلمات المفتاحية: Haft Savaran, Original singularity, Weighted singularity, Mineralized zones,

ملخص المقالة :

The Haft Saravan area is located in 90 km SE Arak in the central Iran. This area is a part of Malyer-Isfahan metallogenic belt. The article's objective is determining the most suitable method for identifying mineralized zones using original singularity and weighted singularity methods in three-dimensional space. In weighted singularity method, mineralized zones have a greater volume relative to original singularity method. Coefficient of areal association showed that percentage of overlapping of two methods is less than 50% for Pb, Fe and Mn and less than 55% for Zn. Two methods were compared by modified singularity method in order to select the best method. Percentage of overlapping is more than 98% both original and modified singularity methods for Pb, Zn and Mn and is less than 45% for weighted singularity method. Therefore, it can be said that original singularity method is suitable relative to weighted singularity in identifying mineralized zones due to the high overlapping of original and modified singularity method.

المصادر:


  1. Adib A, Afzal A, Mirzaei Ilani Sh, Aliyari F (2017) Determination of the relationship between major fault and zinc mineralization using fractal modeling in the Behabad fault zone, central Iran. Journal of African Earth Sciences 134: 308-319.
    2.
  2. Afzal P, Ahmadi K, Rahbar K (2017) Application of fractal-wavelet analysis for separation of geochemical anomalies. Journal of African Earth Sciences 128: 27-36.
    3.
  3. Afzal P, Mirzaei M, Yousefi M, Adib A, Khalajmasoumi M, ZiaZarifi A, Foster P, Bijan Yasrebi A (2016) Delineation of geochemical anomalies based on stream sediment data utilizing fractal modeling and staged factor analysis. Journal of African Earth Sciences 119: 139-149.
    4.
  4. Afzal P, Karami K (2015) Application of multifractalmodeling for separation of sulfidic mineralized zones based on induced polarization and resistivity data in the Ghare-Tappeh Cu deposit, NW Iran. Iranian Journal of Earth Sciences17 (2): 134-141.
    5.
  5. Carranza EJM (2008) Geochemical Anomaly and Mineral Prospectivity Mapping in GIS. Handbook of Exploration and Environmental Geochemistry 11. Elsevier,Amsterdam.
    6.
  6. Carranza EJM, Owusu EA, Hale M (2009) Mapping of prospectivity and estimationof number of undiscovered prospects for lode gold, southwestern Ashanti Belt, Ghana.Mineralium Deposita 44: 915-938.
    7.
  7. Carranza EJM, Sadeghi M (2010) Predictive mapping of prospectivity andquantitative estimation of undiscovered VMS deposits in Skellefte district (Sweden). Ore Geology Reviews 38: 219-241.
    8.
  8. Chen X, Xu R, Zheng Y, Jiang X, Du W (2018) Identifying potential Au-Pb-Ag mineralization in SE Shuangkoushan, North Qaidam, Western China: Combined log-ratio approach and singularity mapping. Journal of Geochemical Exploration 189: 109-121.
    9.
  9. Cheng Q (1999) Multifractality and spatial statistics.Computer & Geosciences 25: 949-961.
    10.
  10. Cheng Q (2007) Mapping singularities with stream sediment geochemical data for prediction of undiscovered mineral deposits in Gejiu, Yunnan Province, China, Ore Geology Reviews 32: 314 – 324.
    11.
  11. Cheng Q (2008) Non-linear theory and power-law models for information integrationand mineral resources quantitative assessments. Mathematical Geoscience 40: 503–532.
    12.
  12. Cheng Q, Agterberg FP, Ballantyne SB (1994) The separation of geochemicalanomalies from background by fractal methods. Journal of Geochemical Exploration 51: 109-130.
    13.
  13. Cheng Q, Agterberg FP (2009) Singularity analysis of ore-mineral and toxic trace elements in stream sediments, Computers & Geosciences 35: 234–244.
    14.
  14. Cheng Q, Zhao P (2011) Singularity theories and methods for characterizing mineralization processes and mapping geo-anomalies for mineral deposit prediction, Geoscience Frontiers (China University of Geosciences (Beijing)) 2(1): 67 – 79.
    15.
  15. Daneshvar L (2017) Delineation of enriched zones of Mo, Cu and Re by concentration-volume fractal model in Nowchun Mo-Cu porphyry deposit, SE Iran. Iranian Journal of Earth Sciences 9(1): 64-72.
    16.
  16. Khavari M (2016) Application of fractal method and singularity index for distinguish of geochemical elements anomalous related to Pb& Zn mineralization in Khomyen. M.Sc thesis, Department of Mining Engineering Exploration Arak University of Technology, In: Persion.
    17.
  17. Liu Y, Cheng Q, Xia Q, Wang X (2014) Identification of REE mineralization-related geochemical anomalies using fractal/multifractal methods in the Nanling belt, South China. Environment Earth Science72 (12): 5159-5169.
    18.
  18. Mandelbrot BB (1972) Possible refinement of the lognormal hypothesis concerning the
    19.
  19. distribution of energy dissipation in intermittent turbulence. In: Rosenblatt, M. and Van
    20.
  20. Atta, C. (Eds.), Statistical Models and Turbulence, Lecture Notes in Physics, 12.
    21.
  21. Springer, New York: 333-351.
    22.
  22. Parsa M, Maghsoudi A, Yousefi M, Carranza EJM (2017a) Multifractal interpolation and spectrum–area fractal modeling of stream sediment geochemical data: Implications for mapping exploration targets. Journal of African Earth Sciences 128: 5-15.
    23.
  23. Parsa M, Maghsoudi A, Yousefi M, Sadeghi M (2017b) Multifractal analysis of stream sediment geochemical data: Implications for hydrothermal nickel prospection in an arid terrain, eastern Iran. Journal of Geochemical Exploration 181: 305-317.
    24.
  24. Parsa M, Maghsoudi A, Carranza EJM, Yousefi M (2017c) Enhancement and mapping of weak multivariate stream sediment geochemical anomalies in Ahar Area, NW Iran. Natural Resources Research 26(4): 443-455.
    25.
  25. Shahrestani Sh, Mokhtari AR (2016) Dilution correction equation revisited: The impact of stream slope, relief ratio and area size of basin on geochemical anomalies. African Earth Sciences128:16-26.
    26.
  26. Xiao F, Chen J, Hou W, Wang Zh, Zhou Y, Erten O (2018) A spatially weighted singularity mapping method applied to identify epithermal Ag and Pb-Zn polymetallic mineralization associated geochemical anomaly in Northwest Zhejiang, China, Journal of Geochemical Exploration 189: 122-137.
    27.
  27. Zandy Ilghani N, Ghadimi F and Ghomi M (2018) Application of alteration index and zoning for Pb-Znexploration in Haft-Savaran area, Khomein, Iran. Journal of Mining &Environmen 9 (1): 229-242.
    28.
  28. Zhang DJ, Cheng QM, Agterberg FP, Cheng ZJ (2016) An improved solution of localwindow parameters setting for local singularity analysis based on Excel VBA batchprocessing technology. Computers & Geosciences 88: 54-66.
    29.
  29. Zhao J, Chen Sh, Zuo R (2017) Identification and mapping of lithogeochemical signatures using staged factor analysis and fractal/multifractal models. Geochemistry: Exploration, Environment,Analysis 17 (3): 239-251.
    30.
  30. Zhao J, Wang WL, Cheng QM, Agterberg FP (2016) Mapping of Fe mineral potential by spatially weighted principal component analysis in the eastern Tianshan mineral district, China. Journal of Geochemical Exploration 164: 107-121.
    31.
  31. Zuo R, Cheng Q, Agterberg FP, Xia Q (2009) Application of singularity mapping technique to identify local anomalies using stream sediment geochemical data, a case study from Gangdese, Tibet, western China, Journal of Geochemical Exploration101: 225–235.
    32.
  32. Zuo R (2014) Identification of weak geochemical anomalies using robust neighborhood statistics coupled with GIS in covered areas. Journal of Geochemical Exploration 136: 93–101.
    33.
  33. Zuo R, Xia Q, Zhang D (2013) A comparison study of the C–A and S–A models with singularity analysis to identify geochemical anomalies in covered areas, Applied Geochemistry 33: 165–172.
    34.
  34. Zuo R, Wang J, Chen G, Yang M (2014) Identification of weak anomalies: A multifractal perspective, Journal of Geochemical Exploration 148: 12-24.
    35.
  35. Zuo R, Wang J, Chen G, Yang M (2015) Identification of weak anomalies: A multifractal perspective. Journal of Geochemical Exploration 148: 12–24.
    36.

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