Journal of Mining and Environement
Volume:2 Issue: 2, Summer 2011

In the past, mining activities have generated major acid drainage sources, which usually carry dissolved metals that flow into the main rivers of the affected basins. The study looks at natural attenuation processes in local, sub-basin and basin areas, in the El Bierzo and Odiel basins of Spain, where coal and metal mining activities were formerly conducted. In this study, sampling and in situ monitoring of pH, Eh, dissolved oxygen, conductivity, temperature, flow, turbidity, acidity, alkalinity, Fe2+, Fe3+ and total Fe were carried out during the hydrological cycle. Chemical analysis was also performed on water samples, following the water quality data of the ICA Network of the Spanish Environment Ministry for a period of 10 years. The results show that the main natural attenuation processes were: dilution by mixing with clean water, oxidation and hydrolysis of dissolved metals, reduction of anaerobic sulphates, and precipitation of secondary minerals.

The trace element contents on the surface originated from mineralization would depend to the thickness of the calcrete layer above the ore deposit on the surface. A very thick layer of calcrete may not allow for much dispersion of the elements of interest in the surface. These elements may be concentrated in non-magnetic and magnetic part of calcrete. Based on the current research, mineralogical composition of the non-magnetic part of the calcrete consists of calcite, quartz and microcline and the magnetic part comprises of magnetite, hematite, calcite and albite (at Kantienpan). It could be demonstrated that calcrete samples close to the ore zone have higher contents of Cu, Zn and CaCO3 when compared to the calcrete samples further away from the ore zone. Lithogeochemical exploration program based on the visually cleaned calcrete samples may lead to the successful identification of underlying mineralization, but the dispersion of the interest elements may be severely restricted. It is however evident that these elements are available at the calcrete-sand interface and could then be dispersed by ground and rain water as in the case of mobile metal ions.

This study proposes a simple but novel and applicable approach to solve the problem of smoothing effect of ordinary kriging estimates. This approach is based on transformation equation in which Z scores are derived from ordinary kriging estimates and then rescaled by the standard deviation of sample data with addition of the mean value of original samples to the results. It bears great potential to reproduce the histogram and semivariogram of the primary data. Actually, raw data are transformed into normal scores in order to avoid the asymmetry of ordinary kriging estimates. Thus ordinary kriging estimates are first rescaled using the transformation equation and then back-transformed into the original scale of measurement. To test the proposed procedure, stratified random samples have been drawn from an exhaustive data set. Corrected ordinary kriging estimates follow the semivariogram model and back-transformed values reproduce the sample histogram, while preserving local accuracy.

Ultimate limits of an open pit, which define its size and shape at the end of the mine’s life, is the pit with the highest profit value. A number of algorithms such as floating or moving cone method, floating cone method II and the corrected forms of this method, the Korobov algorithm and the corrected form of this method, dynamic programming and the Lerchs and Grossmann algorithm based on graph theory have been developed to find out the optimum final pit limits. Each of these methods has special advantages and disadvantages. Among these methods, the floating cone method is the simplest and fastest technique to determine optimum ultimate pit limits to which variable slope angle can be easily applied. In contrast, this method fails to find out optimum final pit limits for all the cases. Therefore, other techniques such as floating cone method II and the corrected forms of this method have been developed to overcome this shortcoming. Nevertheless, these methods are not always able to yield the true optimum pit. To overcome this problem, in this paper a new algorithm called floating cone method III has been introduced to determine optimum ultimate pit limits. The results show that this method is able to produce good outcome.

In this study, an ore grade estimation model was developed based on image processing and pattern recognition techniques. The study was performed at a limestone mine in central part of Iran. The samples were randomly collected from different parts of the mine and crushed down (from 10 cm to 2.58 cm). The images of the samples were taken in an appropriate environment and processed. A total of 76 features were extracted from the identified rock samples in all images. Neural network was used as an intelligent tool for ore grade estimation. First, six principal components derived from principal component analysis were used as input of neural network and four grade attributes of limestone (CaCO3, Al2O3, Fe2O3 and MgCO3) were used as the output. The root of mean squared error between the observed values and the model estimated values for the test data set were 0.38, 0.84, 0.15 and 0.03; the R2 values were 0.78, 0.76, 0.76 and 0.81 for the mentioned chemical compositions respectively. The value of R2 indicates the correlation between the actual and estimated data. It can therefore be inferred that the model could successfully estimate the percentage of chemical compositions of the samples collected from the same mine.

Determination of rock mass deformation modulus is very important in different projects, especially in civil and mining engineering works. In-situ measurements such as dilatometer, plate load and flat jack methods may be applied to determine the deformation modulus. However, these methods are very expensive and time- consuming. Analytical methods are very useful approaches which can also be used to estimate rock mass deformation modulus. Using these methods, the parameters influencing the rock mass modulus can also be evaluated. Analytical methods are based on the resultant displacement of rock mass and joints which are finally used to predict the rock modulus. It should be mentioned that none of the available analytical models could present a model to consider the effect of lateral stresses on rock mass modulus calculations. Therefore, this paper tries to investigate the effect of intermediate principal stress (σ2) and minimum principal stress (σ3) on the deformation modulus of jointed rock mass.

Most of the Earth's crust contains fluids, and fractures are common throughout the upper part. They exist at a wide range of scales from micro-fractures within grains to major faults and shear zones that traverse the crust. In this paper, the stress-dependent permeability in fractured rock masses have been investigated considering the effects of nonlinear normal deformation and shear dilation of fractures using a two-dimensional distinct element method program, UDE. A new analytical and numerical model was proposed to determine the relationship between fracture dip angle, aperture and permeability. The numerical work were conducted in two ways: (1) increasing the overall stresses with a fixed ratio of horizontal to vertical stresses components; and (2) increasing the differential stresses (i.e., the difference between the horizontal and vertical stresses) while keeping the magnitude of vertical stress constant. The results showed that at the stress ratio of 1 the significant shear dilation occurs at an approximately low stress and mean fracture angles. For the differential stresses case, the shearing process can result in breakage of the asperities, resulting in the decrease of the dilation rate and strain softening of the fracture.