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Multivariate Geostatistical Simulation of a Nickel Laterite Deposit

机译:镍红土矿床的多元地统计学模拟

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摘要

There are many variables to consider in the evaluation of nickel laterite deposits including the concentrations of nickel, iron, silica, and magnesia. These variables show complex relationships with each other such as mineralogical constraints, non-linear correlation, and heteroscedasticity. The complex multivariate relationship between the variables cannot be reproduced by conventional Gaussian or indicator geostatistical techniques. We introduce the stepwise conditional transformation method as a pre- and post-processing multivariate transform for the stochastic simulation of a nickel laterite deposit. Transformed data are multiGaussian and independent at h = 0; thus, cosimulation can be avoided after verification that variables are independent at all lag distances. Back transformation restores the features of the input multivariate distribution to the simulated realizations. The complex multivariate correlations are reproduced and sensitivity issues are addressed.
机译:在评估红土镍矿矿藏时,要考虑许多变量,包括镍,铁,二氧化硅和氧化镁的浓度。这些变量显示出彼此的复杂关系,例如矿物学约束,非线性相关性和异方差。变量之间的复杂多元关系无法通过常规的高斯或指标地统计技术来再现。我们引入逐步条件转换方法作为镍红土矿床随机模拟的前处理和后处理多元转换。转换后的数据是多高斯的,并且在h = 0时独立;因此,在验证变量在所有滞后距离处都是独立的之后,可以避免进行协同仿真。反向转换将输入多元分布的特征恢复到模拟实现。复制了复杂的多元相关性并解决了敏感性问题。

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