Next Article in Journal
Motivated for Action and Collaboration: The Abrahamic Religions and Climate Change
Previous Article in Journal
Geochemical Characterization of Trace MVT Mineralization in Paleozoic Sedimentary Rocks of Northeastern Wisconsin, USA
Article Menu

Export Article

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

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

Instituto Geológico y Minero de España, C/Matemático Pedrayes, 25, Oviedo 33005, Spain
Consultor-Auditor Minero Freelance, Piñas 070401, Ecuador
Universidad de Guayaquil, Av. Raúl Gómez Lince s/n y Av. Juan Tanca Marengo, Guayaquil 090612, Ecuador
Universidad Politécnica de Madrid. España, C/Ríos Rosas, 21, Madrid 28003, Spain
Escuela Superior Politécnica del Litoral, Campus Prosperina Espol, Guayaquil 090903, Ecuador
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]   |  


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

Figure 1

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).

Scifeed alert for new publications

Never miss any articles matching your research from any publisher
  • Get alerts for new papers matching your research
  • Find out the new papers from selected authors
  • Updated daily for 49'000+ journals and 6000+ publishers
  • Define your Scifeed now

SciFeed Share & Cite This Article

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.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics



[Return to top]
Geosciences EISSN 2076-3263 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top