云南个旧锡铜多金属矿床矿物微观组构非线性特征研究.doc

云南个旧锡铜多金属矿床矿物微观组构非线性特征研究 【中文摘要】分形理论作为非线性科学的一个分支,在地球科学各个领域得到了广泛的应用并取得了重要的成果。本文主要用奇异性和成矿系数理论、周长-面积模型和计盒维数来研究矿物微观组构的非线性特征。金属矿物的数目和非金属矿物的数目在一定标准e或矿石量V内是遵循分形关系的。假如奇异性指数在矿化区域内是多变的,那么这些数目服从多重分形分布。通过奇异性指数可以评价成矿系数或者两个经过对数变换的变量之间的相关系数。通过成矿系数来量化成矿系统,关于成矿系数k的等值线图可以用来显示不同位置的矿化强度。P-A周长-面积模型把具有自相似性的不规则变形几何体的周长与面积联系起来,用以度量矿物颗粒的不规则变化,包括计算分形维数。计盒维数反映了矿物在空间平面上的生长分布情况,用来揭示矿物颗粒分布的自相似性和定量描述复杂颗粒分布的几何形态。基于以上理论模型的支持,本论文以云南个旧锡铜多金属矿床为研究地区,在充分分析研究区域地质背景和矿区地质特征的基础上开展矿物微观组构非线性特征的研究。野外观察取样与室内数据处理与分析相结合,采用GIS图像处理手段,以矿物微观结构和分布的数据为基础,从分形奇异性和多重分形模型出发,研究成矿富集系数,以此熟悉成矿的物理和化学环境、成矿作用动力学,为开展宏观标准地质异常和矿床矿体的奇异性分析提供微观依据。具体的研究内容有研究典型剖面云南个旧锡铜多金属矿床老厂期北山七段玄武岩主要金属矿物磁黄铁矿的结构、颗粒大小及分布的非线性特征;研究矿物微观标准上金属矿物与非金属矿物之间的成矿系数、不同金属矿物之间的分布相关系数,进而获得了以下几个方面的熟悉1通过用P-A、计盒维数这两种不同的分形模型对老厂期北山垂向上七段玄武岩磁黄铁矿的结构、颗粒大小、分布的研究,得到了反映颗粒变化的参数面积分维DA、周长-面积分维D_PA和周长分维D_P。随着岩体深度的增加,从第一段玄武岩到第七段玄武岩,磁黄铁矿的面积分维D_A和周长分维D_P没有太大变化,总体保持不变的态势;而周长-面积分维D_PA却有逐渐增大的趋势。D_PA增大表明随着深度的增加,磁黄铁矿颗粒变得不规则起来,这些变化都可以从显微图片上观察验证。这种现象可能是由于随着深度的增加温度升高、压力变大引起的。2通过研究卡房大白岩玄武岩中金属矿物与非金属矿物之间的成矿系数,证实在矿物微观标准上它们之间多重分形的分布关系。从成矿系数k等值线分布图上可以清楚的看到每个位置成矿系数的高低,亦即反映了金属矿物与非金属矿物分布的多少。3研究了个旧矿区典型矿物标本中不同金属矿物之间的分布相关系数,结果说明它们之间存在着分形的分布关系。不同样品之间、不同金属矿物之间其相关系数是显然不同的;相同的两种金属矿物在不同样品中其相关系数是不同的;同一样品中相同的两种矿物位置不同,其相关系数是不同的,这就反映了分布系数k是服从多重分形分布的;k值的正负和大小,反映了中心位置四周矿物分布数目上的变化。以上工作表明,用分形模型来量化不同岩段里矿物颗粒的不规则性变化是可行的,进而可以反映成矿的物理化学环境;在微观标准上,矿物的分布在一定的标度区内都具分形结构,这对成矿作用理论的发展和成矿猜测都有重要意义。; 【Abstract】 Fractal theory as a branch of nonlinear science has been applied to various fields of geosciences and some significant achievements have been accomplished. This dissertation mainly uses singularity and mineralization coefficient theory、Perimeter-Area model and box-counting fractal model to research the nonlinear characteristics of mineral microtexture.Both quantity of metal mineral and quantity of nonmetal mineral follow power-law relationship with ore volume V or support scale e. These quantities follow multifractal distributions if the singularity inds a exponents vary in the mineralization domain. This indicates that the ratio of the singularities of the quantities of metal ore mineral and gauging minerals is related to the mineralization coefficient which can be estimated from a group of values of logΦand logΨby linear regression as the regression coefficient, which is also related to correlation coefficient R. Then one can use ratio of singularity inds to estimate the mineralization coefficient or the correlation coefficient between two log-transed variables. The index map k that can be estimated from the ratio of local singularities is useful for differentiating locations showing or not showing strong mineralization. The perimeter-area model is a mathematical model associating the relationship between the perimeter P and area A of similarly shaped sets. This model can be used to quantify the irregularities of minerals. The box-counting fractal model is used to reflect the complication of minerals distribution.Based on the theory listed above this dissertation took tin-copper polymetallic deposit in Gejiu as research district, and the main work is to research the nonlinear characters of mineral microtexture. This work is based on observation in field and data processing in doors. By using the of image processing based on GIS, we can get the data of mineral microtexture and distribution. And then by using the fractal singularity model and multifractal model, we can research the mineralization coefficient to know about the physical and chemical environment of mineralization. This work can provide some proof of macro-scale geological abnormity analysis and ore deposit singularity research.The detailed content of the *** is analysis the texture and shape change of pyrrhotite in seven sections basalt which is distributed in Qibeishan, Laochang, Gejiu in-copper polymetallic deposit; research the mineralization coefficient between quantity of metal mineral and quantity of nonmetal mineral; research the correlation coefficient between two different metal minerals. And some summing-up is as follows1 By using P-A and box-counting fractal model, the parameters D_Afractal dimension of area、D_PAfractal dimension of area and perimeter and Dpfractal dimension of perimeter of pyrrhotite was calculated. From the first section basalt to the seventh section basalt, as the depth of rock body increasing, the D_A and D_P change a little, but the D_PA has a trend of increase. This indicates that the shape of pyrrhotite is more and more irregular. This phenomenon may be due to that as the depth increases, the temperature and pressure becomes higher.2 By the research of mineralization coefficient between quantity of metal mineral and quantity of nonmetal mineral in basalt of Dabaiyan, it is approved that these quantities follow multifractal distributions. From the index map k we can see that different locations show different degree of mineralization.3 By the research of correlation coefficient between quantity of different metal minerals, it is approved that these quantities follow fractal distributions. Different metal minerals, different correlation coefficient; although the metal minerals are same if the locations are different, the correlation coefficient is also different, this phenomenon reflects that the correlation coefficient follow multifractal distribution.