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非均质地层地质剖面的随机预测模型
引用本文:雷进生,夏磊,王乾峰,曹雪廷,陈建飞.非均质地层地质剖面的随机预测模型[J].地下空间与工程学报,2016,12(1):84-89.
作者姓名:雷进生  夏磊  王乾峰  曹雪廷  陈建飞
作者单位:三峡大学 土木与建筑学院,湖北 宜昌 443002
基金项目:国家自然科学基金(51279092;51278282),湖北省自然科学基金(2013CFB218),宜昌市科学技术研究与开发项目(A2011-302-5);三峡大学人才科研启动基金(KJ2014B004)
摘    要:基于目标要求进行非均质地层的地质建模,对地层局部地质信息的变异和随机性进行精细化描述和预测。基于随机分形理论,结合地质勘探资料,以孔隙率作为区域土层物性参数的数据源,采用改进数盒子法对钻孔数据分析和计算出分形维度,并应用Diamond-Square方法,考虑多个随机变量的相互关联作用,建立了孔隙率、渗透率等土层物性参数的随机分布预测模型。针对土层的地质点参数的相关性和其他不确定性因素,提出土性参数不确定性数学模型,并给出了土层中压缩模量与孔隙率之间的关系。

关 键 词:非均质地层  地质剖面  孔隙率  随机分形  预测模型  
收稿时间:2015-04-14

Random Prediction Model of Geological Section for Non-homogeneous Formation
Lei Jinsheng,Xia Lei,Wang Qianfeng,Cao Xueting,Chen Jianfei.Random Prediction Model of Geological Section for Non-homogeneous Formation[J].Chinese Journal of Underground Space and Engineering,2016,12(1):84-89.
Authors:Lei Jinsheng  Xia Lei  Wang Qianfeng  Cao Xueting  Chen Jianfei
Affiliation:College of Civil Engineering & Architecture,China Three Gorges University,Yichang, Hubei 443002, P. R. China
Abstract:A random prediction model based on the target was constructed. The model can describe and predict the variability and randomness of local geological information of formation in detail. Based on random fractal theory, and combined with the exploration data, taking the porosity as the data source of the regional soil physical parameters, analysis on drilling data was carried out to calculate the fractal dimension with the improved box-counting method, taking into account the interrelated role of multiple random variables with the Diamond-Square methods to establish the stochastic prediction model of soil physical parameters such as porosity and penetration rate. Considering the correlation and other uncertainties in the geological parameters of the soil, the mathematical model of the uncertain soil parameter is proposed and the relationship between the compression modulus and the porosity of the soil is given.
Keywords:non-homogeneous formation  geological section  porosity  random fractal  prediction model
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