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Geosciences 2016, 6(2), 30; doi:10.3390/geosciences6020030

Ore Petrography Using Optical Image Analysis: Application to Zaruma-Portovelo Deposit (Ecuador)

1
Instituto Geológico y Minero de España, C/Matemático Pedrayes, 25, Oviedo 33005, Spain
2
Consultor-Auditor Minero Freelance, Piñas 070401, Ecuador
3
Universidad de Guayaquil, Av. Raúl Gómez Lince s/n y Av. Juan Tanca Marengo, Guayaquil 090612, Ecuador
4
Universidad Politécnica de Madrid. España, C/Ríos Rosas, 21, Madrid 28003, Spain
5
Escuela Superior Politécnica del Litoral, Campus Prosperina Espol, Guayaquil 090903, Ecuador
6
Compañía Minera PL S.A., Zaruma 070301, Ecuador
*
Author to whom correspondence should be addressed.
Academic Editor: Antonio Acosta-Vigil
Received: 19 April 2016 / Revised: 6 June 2016 / Accepted: 12 June 2016 / Published: 21 June 2016
View Full-Text   |   Download PDF [7223 KB, uploaded 21 June 2016]   |  

Abstract

Optical image analysis (OIA) supporting microscopic observation can be applied to improve ore mineral characterization of ore deposits, providing accurate and representative numerical support to petrographic studies, on the polished section scale. In this paper, we present an experimental application of an automated mineral quantification process on polished sections from Zaruma-Portovelo intermediate sulfidation epithermal deposit (Ecuador) using multispectral and color images. Minerals under study were gold, sphalerite, chalcopyrite, galena, pyrite, pyrrhotite, bornite, hematite, chalcocite, pentlandite, covellite, tetrahedrite and native bismuth. The aim of the study was to quantify the ore minerals visible in polished section through OIA and, mainly, to show a detailed description of the methodology implemented. Automated ore identification and determination of geometric parameters predictive of geometallurgical behavior, such as grade, grain size or liberation, have been successfully performed. The results show that automated identification and quantification of ore mineral images are possible through multispectral and color image analysis. Therefore, the optical image analysis method could be a consistent automated mineralogical alternative to carry on detailed ore petrography. View Full-Text
Keywords: optical image analysis; multispectral images; color images; ore minerals; optical microscopy optical image analysis; multispectral images; color images; ore minerals; optical microscopy
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Berrezueta, E.; Ordóñez-Casado, B.; Bonilla, W.; Banda, R.; Castroviejo, R.; Carrión, P.; Puglla, S. Ore Petrography Using Optical Image Analysis: Application to Zaruma-Portovelo Deposit (Ecuador). Geosciences 2016, 6, 30.

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