Automated mineralogy explained

Automated mineralogy is a generic term describing a range of analytical solutions, areas of commercial enterprise, and a growing field of scientific research and engineering applications involving largely automated and quantitative analysis of minerals, rocks and man-made materials.

Technology

Automated mineralogy analytical solutions are characterised by integrating largely automated measurement techniques based on Scanning Electron Microscopy (SEM) and Energy-dispersive X-ray spectroscopy (EDS). Commercially available lab-based solutions include QEMSCAN and Mineral Liberation Analyzer (MLA) from FEI Company, Mineralogic from Zeiss, AZtecMineral from Oxford Instruments, the TIMA (Tescan integrated mineral analyzer) from TESCAN, AMICS from Bruker, and MaipSCAN from Rock Scientific. The first oil & gas wellsite solution was launched jointly by Zeiss and CGG Veritas in 2011 called RoqSCAN. This was followed approximately 6 months later by the release of QEMSCAN Wellsite by FEI Company. More recently in 2016, a ruggedized mine site solution for mining and mineral processing was launched by Zeiss called MinSCAN.

Business

The business of automated mineralogy is concerned with the commercialisation of the technology and software in terms of development and marketing of integrated solutions. This includes all aspects of: service; maintenance; customer support; R&D; marketing and sales. Customers of automated mineralogy solutions include: laboratory facilities; mine sites, well sites, and research institutions.

Applications

Automated mineralogy solutions are applied in a variety of fields requiring statistically reliable, quantitative mineralogical information. These include the following sectors: mining;[1] O&G;[2] coal;[3] environmental sciences;[4] forensic geosciences;[5] archaeology;[6] agribusiness; built environment and planetary geology.[7]

History of the use of the term

The first recorded use of the term automated mineralogy in technical journals can be traced back to seminal papers in the late eighties early nineties describing QEMSCAN technology and applications.[8] [9] The term gained significant popularity after it was used to name a new international conference in July 2006.[10]

See also

Notes and References

  1. Goodall, W.R., Scales, P.J., Butcher, A.R. 2005. The use of QEMSCAN and diagnostic leaching in the characterisation of visible gold in complex ores. Minerals Engineering, 18, 8, 877-886 doi:org/10.1016/j.mineng.2005.01.018
  2. Fröhlich, S., Redfern, J., Petitpierre, L., J.D. Marshall, M. Power, Grech, P. 2010. Diagenetic evolution of incised channel sandstones: implications for reservoir characterisation of the Lower Carboniferous Marar Formation, Ghadames Basin, Western Libya. Journal of Petroleum Geology, 33; 3-18. abstract
  3. Liu, Y., Gupta, R., Sharma, A., Wall, T., Butcher, A., Miller, G., Gottlieb, P., French, D. 2005. Mineral matter–organic matter association characterisation by QEMSCAN and applications in coal utilisation. Fuel, 84, 10, 1259–1267.
  4. Haberlah, D., Williams, M.A.J., Halverson, G., Hrstka, T., Butcher, A.R., McTainsh, G.H., Hill, S.M., Glasby, P. 2010. Loess and floods: high-resolution multi-proxy data of Last Glacial Maximum (LGM) slackwater deposition in the Flinders Ranges, semi-arid South Australia. Quaternary Science Reviews, 29, 19-20, 2673–2693.
  5. Pirrie, D., Power, M.R., Rollinson, G.K., Wiltshire, P.E.J., Newberry, J., Campbell, H.E. 2005. Automated SEM-EDS (QEMSCAN) Mineral Analysis in Forensic Soil Investigations: Testing Instrumental Reproducibility. In:K. Ritz et al. (eds.) Criminal and Environmental Soil Forensics, 84, 10, 411-430, Springer Science doi:org/10.1007/978-1-4020-9204-6_26
  6. Knappett, C., Pirrie, D., Power, M.R., Nikolakopoulou, I., Hilditch, J., Rollinson, G.K. 2005. Mineralogical analysis and provenancing of ancient ceramics using automated SEM-EDS analysis (QEMSCAN): A pilot study on LB I pottery from Akrotiri, Thera. Journal of Archaeological Science, in press https://dx.doi.org.10.1016/j.jas.2010.08.022
  7. Schrader, C.M., Rickman, D., Stoeser, D., Wentworth, S.J., Botha, P.W.S.K., Butcher, A.R., McKay, D., Horsch, H., Benedictus, A., Gottlieb, P. 2008. Analysis of Lunar Highland Regolith Samples from Apollo 16 Drive Core 64001/2 and Lunar Regolith Simulants - An Expanding Comparative Database. NASA Technical Report, MSFC-2144 abstract
  8. Sutherland, D., Gottlieb, P., Jackson, R., Wilkie, G., Stewart, P. 1988. Measurement in section of particles of known composition. Minerals Engineering, 1, 4, 317-326.
  9. Sutherland, D.N., Gottlieb, P. 1991. Application of automated quantitative mineralogy in mineral processing . Minerals Engineering, 4, 7-11, 753-762.
  10. Web site: Minerals Engineering Conferences - Automated Mineralogy 06.

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