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Marzeihe Shademan Khakestar Hassan Madani Hossein Hassani Parvizz Moarefvand 《Journal of the Geological Society of India》2013,81(4):581-585
Ordinary kriging and non-linear geostatistical estimators are now well accepted methods in mining grade control and mine reserve estimation. In kriging, the search volume or ‘kriging neighbourhood’ is defined by the user. The definition of the search space can have a significant impact on the outcome of the kriging estimate. In particular, too restrictive neighbourhood, can result in serious conditional bias. Kriging is commonly described as a ‘minimum variance estimator’ but this is only true when the neighbourhood is properly selected. Arbitrary decisions about search space are highly risky. The criteria to consider when evaluating a particular kriging neighbourhood are the slope of the regression of the ‘true’ and ‘estimated’ block grades, the number of kriging negative weights and the kriging variance. Search radius is one of the most important parameters of search volume which often is determined on the basis of influence of the variogram. In this paper the above-mentioned parameters are used to determine optimal search radius. 相似文献
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The valuation of a mining project depends upon the accuracy of geological block model. Sampling density, estimation method, and proper block size mainly affect the accuracy of estimated block. This paper aims to answer three questions: (1) which estimation method is more accurate, (2) what is the relation between sampling density and block size, and (3) what the optimum block size is. Conditional Gaussian simulation (CGS) was used to generate a hypothetical deposit, considered as a real block model. A range of different block dimensions were estimated by ordinary kriging, inverse squared distance, and nearest neighbor methods based on tow-simulated drilling grids database. The comparison of estimated and real block grades reveals that increasing the sampling density results the similar outcomes of geostatistics and deterministic interpolation methods. Furthermore, it was deduced that sampling density could not be a viable alternative in choosing appropriate block dimension and the variogram rang a was suggested as an affective parameter in block size selection. Then a geometrical formula was developed to obtain the block size based on the variogram range. The increment in project value that a mine planner can expected from the additional information of the dense drilling grid was also calculated and it was concluded that the block size obtained based on the suggested formula results acceptable information value. Finally, the database of Chador Malu iron ore mine which is located in 180 km northeast of Yazd city in the central part of Iran were used to validate the suggested formula. 相似文献
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M. Soleiman Dehkordi K. Shahriar P. Moarefvand M. Gharouninik 《Arabian Journal of Geosciences》2013,6(4):1241-1248
Estimation of rock load is a very important issue because the selection of a support system is highly related to this parameter. Several methods are used to estimate this parameter such as experimental, empirical, and numerical methods. This study propose a new empirical method to estimate the rock load in squeezing ground condition using actual collapses data of Emamzade Hashem tunnel of Iran based on the ration of the post-failure residual strain energy to the pre-failure stored strain energy. Prediction of squeezing ground condition in this study is performed based on Jethwa, Singh, and Hoek criterions. Results show that some sections in shale and sandstone of the Shemshak formation are prone to squeezing. Finally, the relation between the rock load and the ratio of the post-failure residual strain energy to the pre-failure stored strain energy, Ψ, in squeezing ground condition is estimated. Based on the statistical analysis, the maximum correlation between both parameters is achieved when Alejano’s equations are used to estimate the drop modulus. As the rock mass behavior changes from elastic–plastic to elastic–brittle, the drop modulus changes from 0 to infinite. The reason is that by increasing the quality of rock mass and reducing the minimum principal stresses, the ratio of post-failure residual strain energy to pre-failure stored strain energy and rock load height (H p) reduce. So, regression analysis is used to investigate the relation between the rock load height and the ratio of post-failure residual strain energy to pre-failure stored strain energy, and finally, a formulation is presented to determine rock load height based on power function. 相似文献
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Acta Geochimica - One of the essential tasks accelerate the decision-making process in mineral exploration projects is ranking anomalous areas. In this study, we used fourteen geologic maps (at... 相似文献
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