Exploitation
F. Sotoudeh; M. Ataei; R. Kakaie; Y. Pourrahimian
Abstract
In mining projects, all uncertainties associated with a project must be considered to determine the feasibility study. Grade uncertainty is one of the major components of technical uncertainty that affects the variability of the project. Geostatistical simulation, as a reliable approach, is the most ...
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In mining projects, all uncertainties associated with a project must be considered to determine the feasibility study. Grade uncertainty is one of the major components of technical uncertainty that affects the variability of the project. Geostatistical simulation, as a reliable approach, is the most widely used method to quantify risk analysis to overcome the drawbacks of the estimation methods used for an entire ore body. In this work, all the algorithms developed by numerous researchers for optimization of the underground stope layout are reviewed. After that, a computer program called stope layout optimizer 3D is developed based on a previously proposed heuristic algorithm in order to incorporate the influence of grade variability in the final stope layout. Utilizing the sequential gaussian conditional simulation, 50 simulations and a kriging model are constructed for an underground copper vein deposit situated in the southwest of Iran, and the final stope layout is carried out separately. It can be observed that geostatistical simulation can effectively cope with the weakness of the kriging model. The final results obtained show that the frequency of economic value for all realizations varies between 6.7 M$ and 30.7 M$. This range of variation helps designers to make a better and lower risk decision under different conditions.
Exploitation
F. Soltani; P. Moarefvand; F. Alinia; P. Afzal
Abstract
The traditional approaches of modeling and estimation of highly skewed deposits have led to incorrect evaluations, creating challenges and risks in resource management. The low concentration of the rare earth element (REE) deposits, on one hand, and their strategic importance, on the other, enhances ...
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The traditional approaches of modeling and estimation of highly skewed deposits have led to incorrect evaluations, creating challenges and risks in resource management. The low concentration of the rare earth element (REE) deposits, on one hand, and their strategic importance, on the other, enhances the necessity of multivariate modeling of these deposits. The wide variations of the grades and their relation with different rock units increase the complexities of the modeling of REEs. In this work, the Gazestan Magnetite-Apatite deposit was investigated and modeled using the statistical and geostatistical methods. Light and heavy REEs in apatite minerals are concentrated in the form of fine monazite inclusions. Using 908 assayed samples, 64 elements including light and heavy REEs from drill cores were analyzed. By performing the necessary pre-processing and stepwise factor analysis, and taking into account the threshold of 0.6 in six stages, a mineralization factor including phosphorus with the highest correlation was obtained. Then using a concentration-number fractal analysis on the mineralization factor, REEs were investigated in various rock units such as magnetite-apatite units. Next, using the sequential Gaussian simulation, the distribution of light, heavy, and total REEs and the mineralization factor in various realizations were obtained. Finally, based on the realizations, the analysis of uncertainty in the deposit was performed. All multivariate studies confirm the spatial structure analysis, simulation and analysis of rock units, and relationship of phosphorus with mineralization.
Exploitation
M. Bavand Savadkoohi; B. Tokhmechi; E. Gloaguen; A.R. Arab-Amiri
Abstract
Computer graphics offer various gadgets to enhance the reconstruction of high-order statistics that are not correctly addressed by the two-point statistics approaches. Almost all the newly developed multiple-point geostatistics (MPS) algorithms, to some extent, adapt these techniques to increase the ...
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Computer graphics offer various gadgets to enhance the reconstruction of high-order statistics that are not correctly addressed by the two-point statistics approaches. Almost all the newly developed multiple-point geostatistics (MPS) algorithms, to some extent, adapt these techniques to increase the simulation accuracy and efficiency. In this work, a scrutiny comparison between our recently developed MPS algorithm, the cross-correlation-wavelet simulation (CCWSIM), and a well-known MPS algorithm, FILTERSIM, is performed. The main motivation to benchmark these two algorithms is that both exploit some digital image processing filters for feature extraction. Indeed, both algorithms compute the similarity (or dissimilarity) between data events in simulation grid and training image in the feature space. In order to compare the accuracy of the algorithms, some statistics such as facies proportion, variogram, and connectivity function are computed. The results obtained reveal an excellent agreement of the CCWSIM realizations with the training image rather than FILTERSIM. Furthermore, on average, the required simulation runtime for CCWSIM is at least 10 times less than that for FILTERSIM.
Exploitation
I. Masoumi; Gh.R. Kamali; O. Asghari
Abstract
Dilution can best be defined as the proportion of waste tonnage to the total weight of ore and waste in each block. Predicting the internal dilution based on geological boundaries of waste and ore in each block can help engineers to develop more reliable long-term planning designs in mining activities. ...
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Dilution can best be defined as the proportion of waste tonnage to the total weight of ore and waste in each block. Predicting the internal dilution based on geological boundaries of waste and ore in each block can help engineers to develop more reliable long-term planning designs in mining activities. This paper presents a method to calculate the geological internal dilution in each block and to correct the ultimate grade of each geological block according to the internal dilution values that have already been calculated for each one of them. In this regard, the input data is first indexed based on the lithological logs of drill holes. The occurrence probabilities of ore and waste in each block are calculated via 100 realizations using the sequential indicator simulation. Dilution is computed as the ratio of waste rock tonnage to the total tonnage of ore and waste. Furthermore, joint simulation of the continuous variables is performed for each mining block using the minimum/maximum auto-correlation factors. In the next step, for each block, the final grade variables including iron and iron oxide are computed by considering the calculated internal dilution. These analyses are applied to the Gohar Zamin iron ore deposit, and the actual internal dilution calculated based on the lithological logs of blast holes is compared with the same values obtained based on the proposed method in each block. The results obtained were found to be satisfactory.
Exploitation
S. Talesh Hosseini; O. Asghari; Seyed R. Ghavami Riabi
Abstract
Due to the existence of a constant sum of constraints, the geochemical data is presented as the compositional data that has a closed number system. A closed number system is a dataset that includes several variables. The summation value of variables is constant, being equal to one. By calculating the ...
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Due to the existence of a constant sum of constraints, the geochemical data is presented as the compositional data that has a closed number system. A closed number system is a dataset that includes several variables. The summation value of variables is constant, being equal to one. By calculating the correlation coefficient of a closed number system and comparing it with an open number system, one can see an increase in the values of the closed number system, which is false. Such features of this data prevent the application of standard statistical techniques to process the data. Therefore, several methods have been proposed for transforming the data from closed to open number systems. There are various geostatistical methods consisting of estimation and simulation methods in order to model a deposit. Geostatistical simulations can produce various models for a deposit with different probability percentages. The most applicable geostatistical simulation method is the sequential Gaussian simulation technique, which is highly flexible. In this work, 392 Litho-geochemical data of the Baghqloom region of Kerman in Iran consisting of 20 elements were at first converted using an open number system. Afterwards, the elements that were helpful for exploring the area and were normally standard were simulated for 100 times. After the simulations, the valid output was chosen using geostatistical validation. The maps derived from the simulations revealed the enriched concentrations of mineralization elements in the central regions.
