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Exploration & Ore Deposits Modelling

Principal researchers: Diana Comte, Daniel Carrizo, Xavier Emery.
Academic associate researchers: Reynaldo Charrier, Katja Deckart, Marcos Díaz, Marcelo García, Francisco Gutiérrez, Denisse Pasten, Jorge Silva, Brian Townley.
Associate researchers: Germán Aguilar, Daniel Baeza, Alejandro Cáceres, Ernesto Castillo, Rodrigo Chi, Álvaro Egaña, Carlos González, Marcia Muñoz, Felipe Navarro, Tomás Opazo, Fabián Soto.
PhD. students: Amir Adeli, Gonzalo Díaz, José Guillermo Fuentes, Roberto Fustos, Amin Hekmatnejad, Mohammad Maleki, Marcela Oyarzún, Shaharokh Paravarzar, Italo Payacán, Mohammad Pishanhang.
MSc. students: Álvaro Aravena, Romina Arriaza, Sebastián Baeza, María Cerda, Andrés Echeverría, Víctor Fredes, Pablo Gómez, Gabriela González, Cindy Guaitía, Francisco González, Valentina Hanna, Nicolás Labbé, Lina Marulanda, Nadia Mery, Daniela Paredes, Gerardo Peña, Mario Pérsico, Fabián Riquelme, Katia Rossel, Leonel Sánchez.

Fundamentals

Chile’s geological resources constitute the most relevant asset for the development of mining companies and its operational continuity sustainability. Although Chile has numerous metal reserves, discovery of new deposits have diminished due to exhaustion of easily detectable superficial resources. Future findings will be, mainly, deposits hidden under the post-mineralization sedimentary crust, or deeper deposits with lesser or non-existent evidence on surface.
On one side, given the geological features of the Andean region, the interdependency of natural resources and associated geological dangers, it is necessary to develop multi-disciplinary strategies that lead towards reducing ambiguity in the exploration of future deposits. That requires an integrated geo-scientific approach, combining methodologies of geophysics, structural geology and geochemistry, applicable to fossil deposits and geothermal fields.
On the other side, considering that in the many stages of ore deposits characterization a great quantity of data is generated (much of it isn’t completely used to build resources, reserves and geometallurgic models), it is necessary to develop tools and models that better predict (or esteem) categorical and continuous variables and quantify uncertainty to ease decision-making.
Resources models are based on information acquired in probing samples and compiling relevant geo-scientific information in order to comprehend the nature of the deposit and to design the best extraction strategy.

Goal

The Exploration and Ore Deposits Modeling group of the Advanced Mining Technology Center studies and analyzes several problems of the mining business through research, development and innovation. Among its researchers are scholars and grad students (MSc. And PhD.) from the areas of Geology, Geophysics, Mine Engineering, Electric Engineering and Computer Engineering. The group’s research areas are based in studies of hydrothermal systems and formation processes in every scale, applied to activities that range from basic (regional) explorations to advanced (district and local) explorations, and pre-feasibility studies, including deposits modelling regarding estimation and simulation of resources and reserves and geo-mining-metallurgic models.
Research associated to exploration involves geophysical, geological, structural and geochemical techniques, from a regional scale to a local scale, from “green fields” to “brown fields”. Projects integrate the aforementioned areas, in a way to achieve multi-scale and transversal exploration criteria, that give more confidence at determining exploration targets. At deposit level geologic-structural researches are conducted, as well as studies of mineral and geochemical characterization, applied to exploration models and evaluation of resources and geologic and/or geo-miming-metallurgic models.
In modelling, geo-mining-metallurgic characterization studies are conducted in order to discriminate and determine, quantitatively and qualitatively, predictive models of mineral behavior. These predictive models have a strong research component in the development of geostatistic modelling of ore deposits oriented towards uni-variable and multi-variable estimation of resources and reserves in complex situations, along with development of specialized software for such a task.

Application

The development of competence areas in the group has allowed the generation of research lines that present a diversity of direct applications for the mining industry, which allow to improve knowledge and technologies oriented towards the optimization of the mining business. Current research lines and applications are:

  • Seismic tomography: An exploration geophysical tool
  • Applied tectonics and structural modelling
  • Evaluation of geologic danger
  • Geology for mining exploration
  • Numeric modelling of magmatic and hydrothermal systems
  • Rock characterization through image analysis for development of geo-metallurgic prediction models
  • Geologic modelling with advanced computer tools and coding of specialized software for mining development.
  • Geo-mining-metallurgic modelling of deposits with focus on integration of geologic and geochemical information in high-performance computer models.

Research lines

  1. Evaluation of geologic danger
  2. Geophysical instrumentation
  3. Seismic tomography: An exploration geophysical tool
  4. Modelling of magmatic and hydrothermal systems
  5. Applied tectonics and multi-scale structural modelling
  6. Geology for mining exploration
  7. Rock characterization through image analysis for development of geo-metallurgic prediction models
  8. Geo-mining-metallurgic modelling of deposits with focus on integration of geologic and geochemical information in high-performance computer models
  9. Geologic modelling with advanced computer tools and coding of specialized software for mining development

Laboratories

Development of the research lines has allowed for the creation of thematic laboratories, the first three ones gathered at the AG2E (Applied Geosciences & Georesources Exploration) lab, the last one is ALGES (Advanced Laboratory for Geostatistics and Supercomputing):

Fact sheet: Laboratory of optimization tools for geological and geophysical multi-scale modelling

Fact sheet: Laboratory of geotecnologies for mining exploration in covered areas

Fact
sheet: Alges Laboratory