Tatiane Marin

An estimation of the artisanal small-scale production of gold in the world.

The increase in gold price of over 400% between 2002 and 2012, due to a shift towards safe investments in a period of crisis in the global economy, created a rapid increase in gold production. A response to this shift in production was observed for artisanal and small-scale mining (ASM) units in remote locations of the world, but this phenomenon has not been quantified yet. The work presented here was done to provide a quantitative tool for estimation of the gold (Au) produced by ASM and the population of workers involved in the production process, and assessment of mercury (Hg) consumed. The following hypotheses were addressed: i) It is possible to estimate, on first approximation, the amount of Au production in the world by artisanal mining; ii) Au production by artisanal mining varies by country and continent and iii) Hg consumption due to ASM can be correlated with the methods applied in the different countries and continents for the production of Au. To do this we estimated the number of miners, calculated the change in Au price and production and then applied an adjustment factor to calculate Hg production by country and continent. The amount of Au produced depends on technology of the miners by continents (highest in South America, medium in Asia and Central America, and lowest in Africa), and the geologic setting (not investigated here). The results of the estimation show that, as of 2011, over 16 million Artisanal Miners, in the world, were involved in gold extraction (mining or treatment), producing between 380 and 450 t of gold per year, with clear global behavior between the continents in terms of recovery efficiency, confirmed by data on Hg release that is higher in countries with lower technology.

The impact of payload truck factor use in mine performance reports for an open pit copper mine in Brazil

This article aims to evaluate the use of a truck factor for off-highway trucks in open pit mine operations, thus reducing error on material movement and mine production data entry. This method is current for a copper mine located in South East Pará, Brazil. With a dispatch system, the truck factor is calculated using three data inputs called measured t, dump t and excavator load time. This dispatch system, designed to upload real time data from each truck, acquires measured load information by a truck weightometer and provides the basis for long-term, medium-term and mainly shortterm planning. Due to the significant impacts toward mine planning, through data error, a payload truck factor system provides data assurances in place of potential failure of onboard weighing. However, when using a system that is reliant on actual data, caution must be applied when replacing information with assumed fixed figures, thus forming the discussion on which this article attempts to review by providing overview on both the positive and negative impacts of implementing a truck factor system to an open pit mining using a dispatch system.

Economic advantages of dynamic analysis in the early stages of mining projects

The use of dynamic simulation is technically advantageous for the project as shown by various authors. However, is it economically advantageous in the early stages of the project (FEL1 and FEL2)? The methodology to economically evaluate the use of dynamic simulation considers the time and development cost compared with the time and cost spent to change the project in the next phase, considering changes that could be avoided with the use of dynamic simulation. Five process plant projects were evaluated, each one with an estimated CAPEX of US

Simulation-based risk quantification: a reconciliation-based performance analysis

300 million. The saved average is US

Modelagem de dados de entrada para simulação estocástica de lavra

44,200.00 and US

Gold losses and mercury recovery in artisanal gold mining on the Madeira River, Brazil

182,400.00 for FEL 1 and FEL 2 respectively. The percentage cost savings for FEL2 (2.0%) and FEL3 (3.1%) are significant. The estimated delay avoided for FEL2 (3 weeks) and FEL3 (8 weeks) is directly related to the implementation delay, whose cost is expressively greater than the savings shown. The study concludes that the use of dynamic simulation is economically advantageous for the project.

A practical approach for the management of resources and reserves in Small-Scale Mining

Abstract Recent studies have demonstrated the utilisation of stochastic simulation to quantify uncertainty in mineral deposits and allowing better management of the geological risk during mining scheduling. This paper describes an approach to evaluate the suitability of stochastically simulated models to characterise the real, but unknown, deposit represented in this study by an orebody model geostatistical estimate based on an extensive grade control drilling data-set. Traditional reconciliation techniques and the related mine call factors (or indicators) are evaluated against uncertainty measures derived from the set of stochastically simulated models. A case study carried out at the main mineral deposit of the Sossego copper mine in Brazil is presented in order to illustrate the practical aspects of the approach and how this approach is validated by traditional reconciliation studies using historical data of a mined out part of the orebody.

Economic feasibility of responsible small-scale gold mining

Mine simulation depends on data that is both coherent and representative of the mining operation. This paper describes a methodology for modeling operational data which has been developed for mine simulation. The methodology has been applied to a case study of an open-pit mine, where the cycle times of the truck fl eet have been modeled for mine simulation purposes. The results obtained have shown that once the operational data has been treated using the proposed methodology, the system variables have proven to be adherent to theoretical distributions. The research indicated the need for tracking the origin of data inconsistencies through the development of a process to manage inconsistent data from the mining operation.