Mine Planning and Optimisation Techniques Applied in an Iron Ore Mine

Author(s):  
Moore Theresa Malisa ◽  
Bekir Genc
Author(s):  
P. Stone ◽  
G. Froyland ◽  
M. Menabde ◽  
B. Law ◽  
R. Pasyar ◽  
...  

Minerals ◽  
2020 ◽  
Vol 10 (4) ◽  
pp. 336
Author(s):  
Iman Masoumi ◽  
Gholamreza Kamali ◽  
Omid Asghari ◽  
Xavier Emery

Since the Gol-Gohar iron ore mine (GGIOM), which is located in southeastern Iran, is currently one of the biggest iron mines in this region, increasing the accuracy of its mineral resources model has become a challenge for geologists, metallurgists and mining engineers. Given that an accurate classification of the mining blocks into ore or waste is highly significant in strategic mine planning, three approaches for simulating the iron grades were compared against the true grades obtained from production data. The comparison was done by calculating the ratio between the total number of blocks correctly classified as ore and waste and the total number of misclassified blocks, and it was conducted for each approach in three mined benches at the GGIOM. The results reveal that the grade simulation that ignores the geological boundaries and the grade simulation based on a deterministic geological interpretation are much less accurate than the hierarchical approach, which consists of simulating both the geological boundaries and the grades.


2011 ◽  
Vol 21 (6) ◽  
pp. 781-786 ◽  
Author(s):  
Maowei Ji ◽  
Xiaojing Li ◽  
Shunchuan Wu ◽  
Yongtao Gao ◽  
Linlin Ge

2021 ◽  
Vol 4 ◽  
pp. 1-8
Author(s):  
R.A. Adebimpe ◽  
A.O. Fatoye

Knowledge of tailings characteristics is required for utilisation and management purposes in the mining and construction industry. Tailings from the mine waste dumps at Itakpe iron ore mine were collected and analysed in the laboratory to determine their chemical and physical characteristics and these include; permeability, porosity, specific gravity, particle size distribution, chemical composition and bioavailability factor of element. Geochemical speciation with quantitative X-ray powder diffraction was used to evaluate the chemical and mineral composition of Itakpe iron ore tailings. The aim is to offer base line data necessary to assess metal mobility and bioavailability. The distribution of heavy metals such as Cu, Ni, Cd, Cr, Zn and Fe was determined using multi- step sequential extraction. The results obtained indicate that the permeability is 6.24 x 10-3 cm/sec; porosity is 35%; and specific gravity is 3.58. The tailings is well graded and is sand gravel. Nickel and Zinc was found to be considerably high in exchangeable and bound to carbonates fraction which are mobile region and is bound to Fe – Mn oxides which is slightly mobile region but the higher concentration of Ni found in residual fraction. The implication of this result is that Nickel and Zinc partially enter into the food chain. Chromium and Cadmium concentration result indicated that these metals can easily enter into the food chain because of their presence in the mobile region and their higher mobility percentage.


2021 ◽  
Vol 18 (1) ◽  
pp. 32-44
Author(s):  
Abdolhakim Batajrobeh Rudi ◽  
Mohsen Mohammadnia Ahmadi ◽  
Mehdi Mogharnasi ◽  
◽  
◽  
...  

Author(s):  
Amirhossein Najafabadipour ◽  
Gholamreza Kamali ◽  
Hossein Nezamabadi-pour

The Forecasting of Groundwater Fluctuations is a useful tool for managing groundwater resources in the mining area. Water resources management requires identifying potential periods for groundwater drainage to prevent groundwater from entering the mine pit and imposing high costs. In this research, Auto-Regressive Integrated Moving Average (ARIMA) and Holt-Winters Exponential Smoothing (HWES) data-driven models were used for short-term modeling of the groundwater fluctuations in a piezometer around the Gohar Zamin Iron Ore Mine. For this purpose, 250 non-seasonal groundwater fluctuations data in the period 22-Nov-2018 to 29-Jul-2019, 200 data for modeling, and 50 data for prediction were used. To take advantage of all the features of the two developed models, the predictions are combined with different methods and specific weights. The results show better accuracy for the ARIMA method between the two short-term forecasts, while the HWES method requires less time for modeling. Also, among all the predictions made, the highest accuracy for the combined least-squares method is for forecasting the groundwater fluctuations in the short-term. All the forecasts show a decrease in the groundwater fluctuations, indicating pumping wells around the Gohar Zamin Iron Ore Mine area.


2008 ◽  
Vol 52 (1) ◽  
pp. S43-S50 ◽  
Author(s):  
Malcolm Ross ◽  
Robert P. Nolan ◽  
Gordon L. Nord

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