地球学报Issue(3)：347-353,7.DOI:10.3975/cagsb.2013.03.10
利用地质统计学方法模拟岩石裂隙网络的三维空间分布--以云南个旧高松矿田为例
Three-dimensional Simulation of Rock Fractures by Geostatistical Method：A Case Study of Gaosong Field in Yunnan Province
摘要
Abstract
The simulation of fracture distribution is an important problem in various fields of geosciences. To simulate the spatial distribution of fracture networks, this paper proposes a geostatistical method in consideration of their directions (strikes and dips). Fracture locations are generated randomly, following fracture density values assigned by sequential Gaussian simulation method. Fracture direction is divided into n equal (or unequal) groups, and sample fracture directions are assigned to its corresponding group. Then sample fracture directions are transformed into indicators consisting of n binary variables, where 1 and 0 represents belonging to and not belonging to this group. For calculation convenience, the indicator number is reduced by using the principal component analysis. Then ordinary kriging is employed to estimate the distributions of these principal components. The results are inversed to the original indicator form, and the biggest one is assigned as 1 while the others are assigned as 0. Fracture directions are generated randomly by using the cumulative distribution function of the biggest group. Based on these simulated results, fracture elements can be determined with location and direction. At last, fracture elements within the angle and distance tolerances are connected to be one fracture. The case study of the fracture data in Gejiu dolomite of southeast Yunnan Province shows that the combination of sequential Gaussian simulation, ordinary kriging and principal component analysis can provide a reasonable simulation result for locations and directions of fractures.关键词
裂隙网络/三维空间分布/地质统计学/个旧锡矿Key words
fracture network/three dimensional distribution/geostatistics/Gejiu tin mine分类
数理科学引用本文复制引用
刘春学,倪春中,燕永锋,谭喨..利用地质统计学方法模拟岩石裂隙网络的三维空间分布--以云南个旧高松矿田为例[J].地球学报,2013,(3):347-353,7.基金项目
本文由国家自然科学基金项目“地学中方向性变量的多尺度空间分布模拟”(编号:40902058)资助。 （编号:40902058）
