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Stefano Bonduà

Associate Professor

Department of Civil, Chemical, Environmental, and Materials Engineering

Academic discipline: ING-IND/28 Excavation Engineering and Safety


Thesis availability - Raw Materials - Mineral Production Systems

Proposal summary:

The mine industry produces millions of tons of waste with low grade contents of minerals, usually referred as stockpiles/tailings. New technologies allow recovering valuable materials from these stockpiles/tailings coupling economic and environmental benefits. To obtain maps of the grade concentration of stockpile/tailing, survey sampling is necessary. Sampling can be an economical and time expensive phase and in general more samples are available, maps with higher accuracy can be provided. Hence, design of an optimum sampling plan is essential. On the other hand, data coming from Earth observation data like Copernicus land services should be joined with the collected in situ data, in order to improve map accuracy by reducing the more expensive in situ sampling methods. Hence, using both sampling data and Earth observation data, maps of grade and environmental indexes can be achieved. The raw material contained in stockpiles/tailings can be a potential economic resource. Economical evaluation and/or identification of hazardous areas of the resource can be obtained by maps of grade, using both in situ sampling method and Earth observation data. Optimal sampling plans can be designed by geostatistical methods. Several statistical tool can be used, like the estimation variance. The data sampling variogram model can be used for evaluating the estimation variance for a wide variety of possible sample patterns, without actually doing the sampling and hence to find the grid that just gives the required accuracy. Therefore, the geostatistical approaches with combined use of Earth observation data can lead to a high reconstruction accuracy maps with a given number of samples.

Possible related thesis topics:

  • Sampling for exploration and ore body evaluations

  • Survey sampling from piles, stockpiles and tailings;

  • In-situ sampling in remote sensing;

  • Methods of Multi-Stage Sampling in mining (exploration and in-field sampling);

  • Geostatistical methods for sample optimization based on estimation variance;

  • Copernicus data for mining exploration

Published on: October 16 2018