西藏甲玛铜多金属矿床储量的协同克立格估值  

Estimation of reserves based on Cokriging in Jiama polymetallic copper deposit,Tibet

作　　者：蒋鑫[1] 庹先国[1,2] 柳炳琦 李怀良[2] 

机构地区：[1]成都理工大学地质灾害防治与地质环境保护国家重点实验室,成都610059 [2]西南科技大学核废物与环境安全国防重点学科实验室,绵阳621010

出　　处：《物探化探计算技术》2015年第3期372-378,共7页Computing Techniques For Geophysical and Geochemical Exploration

基　　金：国家自然科学基金重大科研仪器设备研制专项(41227802);国家杰出青年基金(41025015)

摘　　要：西藏甲玛铜多金属矿矿区元素分布复杂,传统的地质统计学方法对其进行储量估算时忽略了多金属的相互影响,因此为了反映出不同金属元素的空间变异情况,采用协同克里格法对该矿区的金属元素储量进行估算。这里首先介绍了协同克里格算法的相关理论和相关技术,然后以此为基础,对不同方向上的空间变差函数进行结构套合的优化,并对协同克里格方程组进行降维处理。最后以2012年甲玛矿区勘探工程的数据为例,以Cu为主区域化变量,以Ag为协同区域化变量,计算了各自的实验变差函数和交差实验变差函数,分别进行协同克里格法插值和普通克里格法插值。交叉验证结果表明,协同克里格估值的标准差为0.6477,在储量计算上面精度更高,并能广泛应用于西藏甲玛铜多金属矿的地质属性、储量估算等空间数据建模。The distribution of mining area element is very complex in Jiama polymetallic copper deposit,Tibet.Traditional geostatistical method ignored the phenomenon of mutual influence more metal on the reserves estimation.In order to reflect different metal elements of space mutation,metal reserves of the mine area is estimated based on the cokriging method in this paper.The paper first introduces the relevant theory and technology of the Cokriging algorithm,then optimizes spatial variation function in different directions to structure of nested,and decreases the dimension of cokriging equations.Finally,by taking an example of the data of exploration engineering for Jiama mining area in 2012,with Cu as the main regionalized variables and with Ag as collaborative regionalized variables,this paper calculate the experimental variogram and the interactive experimental variogram,respectively,Cokriging interpolation and the ordinary kriging interpolation.Cross validation results point out that the standard deviation of Cokriging is 0.6477,and the Cokriging is higher in the calculation of reserves above precision.The Cokriging can be widely used in the geological properties,reserve estimation and spatial data modeling of Jiama polymetallic copper deposit,Tibet.

关 键 词：储量估算 协同克里格 空间变异 结构套合 

分 类 号：P632[天文地球—地质矿产勘探]