关键词: 岩浆硫化物矿床, 硫饱和, 支持向量机, 非线性, 岩浆混合作用, 预测模型

Abstract:

Sulfur plays an important role in the formation of magmatic sulfide deposits. Based on the drill core data of the Voisey’s Bay nickel-copper sulfide deposit in Labrador, Canada, the correlation between nickel and copper mass fraction and sulfur mass fraction was analyzed by support vector machine (support vector machine, SVM) and kernel function based on radial basis function (radial basis function, RBF), and the prediction model of sulfur was established based on     sulfur mass fraction. In the prediction model, nickel and copper mass fractions are used as independent variables, sulfur mass fraction is used as the dependent variable, the predicted value of sulfur mass fraction is calculated by SVM to fit the original value. According to the calculation results of the fitting curve, the sulfur evolution can be divided into three stages: In the sulfur saturation stage, the mass fraction of sulfur element is 3.12×10-6-20.80×10-6, the variance is less than 1.44×10-7, the fractal dimension is 0.35, λ>0, and the stage is chaotic; In the mineralization stage, the mass fraction of sulfur element is 6.60×10-7-17.80×10-7, the variance is less than 1.37×10-9, the fractal dimension is 0.60, λ>0, and the stage is chaotic; In the sulfur loss stage, the sulfur mass fraction is 2.00×10-8-38.0.×10-8, the variance is less than 1.56×10-10, the fractal dimension is 0.94, λ=0, and the stage is stable. The results show that the mass fraction of nickel, copper and sulfur in the immiscible sulfur-saturated magma is not linearly or simply nonlinearly correlated, but staged nonlinearly.

Key words: magmatic sulfide deposit, sulfur saturation, support vector machine, nonlinear, magmatic mixing, prediction model