Document Type : Original Research Paper


1 Department of Mining Engineering, Amirkabir University of Technology, Tehran, Iran

2 Mineralogist Expert, Sarcheshmeh Copper Mine; Iran

3 Department of Mining Engineering, Faculty of Engineering, University of Kashan, Kashan, Iran


Geometallurgy has become an important tool to predict the processing behaviour of ores, and to decrease the production risks associated with the variable nature of economic mineral deposits. Understanding the ore variability and subsequently the response of the ore to processing are considered to be the most important functions of an accurate geometallurgical study. In this paper geometallurgical indices for grinding properties of a copper ore are investigated. Geometallurgical index (GI) is described as any geological feature which makes a footprint on the processing performance of the ores. A comprehensive study at Sarcheshmeh porphyry copper mine was undertaken. This included the process responses of the ore such as grade, recovery and plant throughput as possible geometallurgical indices. In this paper the effects of rock breakage variability on the plant throughput and energy consumption are presented. Ninety samples were collected based on geological features including lithology, hydrothermal alteration, and geological structures. The samples were characterized using X-ray diffraction, X-ray fluorescence, electron and optical microscopy. A small scale simulated test method for Bond ball mill work index (BWI) was used to perform the comminution examinations. The results showed that BWI values vary from 5.67 kWh/t to 20.21 kWh/t. Examination of the possible correlations between BWI and the geological features showed that the key geological feature related to comminution variability is lithology. In addition, the hydrothermal alteration would be an effective parameter in the period that the plant is fed with a single lithology.


  1. Ashley K, Callow M (2000) Ore variability: Exercises in geometallurgy, Engineering and Mining Journal 201:24.
  2. Bennett C, Lozano C (2004) The Architecture of the Geometallurgical Model, Proceedings Procemin:1-8.
  3. Bond FCJCE (1961) Crushing and grinding calculations Brit.
  4. Bond FCJME (1952) Third theory of comminution,  4:484.
  5. Boomeri M, Nakashima K, Lentz DR (2010) The Sarcheshmeh porphyry copper deposit, Kerman, Iran: A mineralogical analysis of the igneous rocks and alteration zones including halogen element systematics related to Cu mineralization processes, Ore Geology Reviews 38:367-381.
  6. Cohen H (1983) Energy usage in mineral processing, Transactions of the Institution of Mining and Metallurgy 92:160-163.
  7. David D The importance of geometallurgical analysis in plant study, design and operational phases. In: Proceedings Ninth Mill Operators’ Conference 2007 : 241-248.
  8. Deutsch JL, Palmer K, Deutsch CV, Szymanski J, Etsell TH (2016) Spatial modeling of geometallurgical properties: techniques and a case study, Natural Resources Research 25:161-181.
  9. Dominy S, O’Connor L, Xie Y (2016) Sampling and testwork protocol development for geometallurgical characterisation of a sheeted vein gold deposit. In: Proceedings of the International Geometallurgy Conference, Perth, Australia: 15-16.
  10. Ehrig K (2011) Quantitative mineral mapping,  The First AusIMM International Geometallurgy Conference: 31.
  11. Etminan H (1977) Le porphyre cuprifère de Sar Cheshmeh (Iran): rôle des phases fluides dans les mécanismes d'altération et de minéralisation. Fondation scientifique de la géologie et de ses applications.
  12. Garrido M, Sepúlveda E, Ortiz JM, Navarro F, Townley B (2018) A Methodology for the Simulation of Synthetic Geometallurgical Block Models of Porphyry Ore Bodies.
  13. Heiskari H, Kurki P, Luukkanen S, Gonzalez MS, Lehto H, Liipo J (2019) Development of a comminution test method for small ore samples, Minerals Engineering 130: 5-11.
  14. Hezarkhani A (2006) Hydrothermal evolution of the Sar-Cheshmeh porphyry Cu–Mo deposit, Iran: evidence from fluid inclusions, Journal of Asian Earth Sciences 28: 409-422.
  15. Hilden MM, Powell MS (2017) A geometrical texture model for multi-mineral liberation prediction, Minerals Engineering 111: 25-35.
  16. Keeney L, Walters SA (2011) methodology for geometallurgical mapping and orebody modelling. In: GeoMet 1st AusIMM International Geometallurgy Conference.  Australasian Institute of Mining and Metallurgy, pp 217-225.
  17. Koch P-H, Lund C, Rosenkranz J (2019) Automated drill core mineralogical characterization method for texture classification and modal mineralogy estimation for geometallurgy, Minerals Engineering 136:99-109.
  18. Kosick G, Bennett C, DOBBY–SGS G (2002) Managing Company Risk by Incorporating the Mine Resource Model into Design and Optimization of Mineral Processing Plants, TECHNICAL BULLETIN : 21.
  19. Kuhar L, McFarlane A, Chapman N, Meakin R, Martin R, Turner N, Robinson D (2013) Calibration and testing of a geometallurgical leaching protocol for determining copper mineralogical deportment. In: Proceedings of the 2nd AusIMM International Geometallurgy Conference: 177-186.
  20. Lamberg P, Rosenkranz J, Wanhainen C, Lund C, Minz F, Mwanga A, Parian M (2013) Building a geometallurgical model in iron ores using a mineralogical approach with liberation data. In: Proceedings of the Second AusIMM International Geometallurgy Conference, Brisbane, Australia: 317-324.
  21. Lishchuk V, Lamberg P, Lund C (2015) Classification of geometallurgical programs based on approach and purpose. In: SGA 2015.
  22. Lishchuk V, Lamberg P, Lund C (2016) Evaluation of sampling in geometallurgical programs through synthetic deposit model. In: XXVIII International Mineral Processing Congress, Québec City, September: 11-15.
  23. Lishchuk V, Lund C, Lamberg P, Miroshnikova E (2018) Simulation of a mining value chain with a synthetic ore body model: Iron ore example, Minerals 8:536.
  24. Mwanga A, Rosenkranz J, Lamberg P (2015) Testing of ore comminution behavior in the geometallurgical context-A review, Minerals 5:276-297.
  25. Mwanga A, Rosenkranz J, Lamberg P (2017) Development and experimental validation of the Geometallurgical Comminution Test (GCT), Minerals Engineering 108:109-114.
  26. Napier-Munn TJ, Morrell S, Morrison RD, Kojovic T (1996) Mineral comminution circuits: their operation and optimisation.
  27. Niiranen K, Böhm A (2012) A systematic characterization of the orebody for mineral processing at Kirunavaara iron ore mine operated by LKAB in Kiruna, Northern Sweden, Impc 1039: 3855-3864.
  28. Piché M, Jébrak MJJoGE (2004) Normative minerals and alteration indices developed for mineral exploration,  Journal of Geochemical Exploration 82: 59-77.
  29. Rincon J, Gaydardzhiev S, Stamenov L (2019) Coupling comminution indices and mineralogical features as an approach to a geometallurgical characterization of a copper ore, Minerals Engineering 130: 57-66.
  30. Shafiei B, Shahabpour J (2012) Geochemical aspects of molybdenum and precious metals distribution in the Sar Cheshmeh porphyry copper deposit, Iran, Mineralium Deposita 47: 535-543.
  31. Sillitoe RH (2010) Porphyry copper systems, Economic geology 105: 3-41.
  32. Stewart M, Coward S, Vann J (2010) Challenges of quality management in sampling and measurement of geometallurgical variables, Sampling Conference: 69-159.
  33. Suriadi S, Leemans SJ, Carrasco C, Keeney L, Walters P, Burrage K, ter Hofstede AH, Wynn MT (2018) Isolating the impact of rock properties and operational settings on minerals processing performance: A data-driven approach, Minerals Engineering 122: 53-66.
  34. Voigt M, Miller J, Bbosa L, Govender R, Bradshaw D, Mainza A, Becker M (2019) Developing a 3D mineral texture quantification method of drill core for geometallurgy, Journal of the Southern African Institute of Mining and Metallurgy 119: 347-353.
  35. Waterman GC, Hamilton R (1975) The Sar Cheshmeh porphyry copper deposit, Economic Geology 70: 568-576.
  36. Williams SR, Richardson J (2004) Geometallurgical Mapping: A new approach that reduces technical risk. In: Proceedings 36th Annual Meeting of the Canadian Mineral Processors: 241-268
  37. Yildirim BG, Bradshaw D, Powell M, Evans C, Clark A (2014) Development of an effective and practical Process Alteration Index (PAI) for predicting metallurgical responses of Cu porphyries, Minerals Engineering 69: 91-96.