马槽滩磷矿区的矿体形态特征及合理勘查工程间距

马槽滩磷矿区矿体形态复杂,底板起伏不定,多年来勘查工程间距不断改变,因此用多种方法讨论了合理工程间距.探采对比和数理统计学方法求得控制资源量的合理工程间距分别为200m×150m和200m×100m;控制半变异函数的变程亦为200m×100m,均与现行规范相吻合。但沿走向和倾向的变异相同,因此建议用正方形网格进行勘查更为合理,间距为150m×150m。     

抗差最小二乘配置在数字化地图几何纠正中的应用讨论

抗差估计具有较好的抗拒异常观测值及粗差的能力,而最小二乘配置又能较好地处理系统误差,本文结合两者的优点,利用抗差最小二乘配置对数字化地图进行几何纠正,其中对协方差函数采用抗差拟合,得到了较好的结果。实验证明在GIS数据处理的扫描数字化地图几何纠正中,抗差最小二乘配置在抗拒异常值和处理系统误差方面优于单纯的最小二乘估计和单纯的最小二乘配置方法。     

小波变换在遥感图像上矿区空间定位方面的分析与应用——以鄂东南铁矿矿区为例

随着社会的发展,人们对自然地物的影响越来越显著,大量地改变了地表的状况,在遥感图像上则表现为灰度值变化剧烈,其中的纹理信息发生改变.在频率域上说,人工改变的区域部分的高频成分比其他区域部分要丰富很多,小波变换能够有效地将其中的高频信息提取出来,用假彩色分割图将其中的异常值明显地表示出来.湖北大冶的铁山矿区分布着六大露天矿区,地表开挖范围广,影响程度大,以该地区为例,分析小波变换在遥感图像上矿区空间定位方面的应用.使用本文介绍的方法处理效果比较明显.矿区位置的确定还需要参考断层分布信息,这意味着使用小波变换进行处理的方法具有一定的局限性.     

Dynamic data integration for structural modeling: model screening approach using a distance-based model parameterization

This paper proposes a novel history-matching method where reservoir structure is inverted from dynamic fluid flow response. The proposed workflow consists of searching for models that match production history from a large set of prior structural model realizations. This prior set represents the reservoir structural uncertainty because of interpretation uncertainty on seismic sections. To make such a search effective, we introduce a parameter space defined with a “similarity distance” for accommodating this large set of realizations. The inverse solutions are found using a stochastic search method. Realistic reservoir examples are presented to prove the applicability of the proposed method.     

DCT域遥感影像融合算法

提出一种基于离散余弦变换(Discrete Cosine Transform,DCT)与IHS变换的多光谱与全色遥感影像融合方法及其改进算法。本文方法依据DCT系数的特点在DCT域进行遥感影像融合,适合压缩格式的遥感影像快速融合。目视效果与客观评价表明,相比常用遥感影像融合方法,本文方法能在提高空间分辨率与保持光谱特性之间得到更好的折衷。     

小波边缘分析建模波阻抗反演方法在煤层解释中的应用

受限于地震波主波长的1／4,常规地震处理难以分辨较薄煤层。基于模型的波阻抗反演虽然克服了厚、薄煤层计算问题．但因难以得到准确的高频部分,很多情况下反演结果的精度和分辨率往往不能满足地质预测的要求。小波边缘分析建模波阻抗反演方法是从地震数据中提取地震特征参数,用于建模并参与迭代反演。该方法即可以弥补反演过程中高频成分的误差,减少对钻井数据的依赖程度,得到较为合理的初始模型,又可提高反演的精度和分辨率．使反演结果更好的反映实际地下地质情况。利用该方法,对大井-将军庙及新疆红沙泉2个勘探区的侏罗系中统西山窑组含煤地层进行波阻抗反演,反演结果与钻井资料进行比较,其中大井一将军庙0802及0809号孔单煤层厚度误差分别为3％、8％．新疆红沙泉多煤层厚度及煤层之间的夹层厚度预测结果除B6煤层误差较大外,其它误差均小于7％．可见该反演方法的计算结果比较准确。     

一种基于小波域的分形遥感影像压缩方法

解决大数据量遥感影像传输和存储问题的方案之一,是对遥感影像进行高保真快速压缩。通过对遥感影像进行小波变换产生子带频域之间的相似性,再利用分形方法对具有相似性的相邻高频子带进行编码,由高一级的子影像构造低一级的子影像,然后采用分形迭代解码和小坡变换的逆变换重建影像。实验结果表明,该方法在一定程度上能够提高压缩比,在压缩时间上比传统的分形方法有明显的缩短,并且压缩后影像信息的损失量较少,影像恢复的质量较好。     

Multi-Scale Texture Modeling

Patterns of crystallographic preferred orientation are referred to as texture. The specific subject of texture analysis is the experimental determination and interpretation of the statistical distribution of orientations of crystals within a specimen of polycrystalline material, which could be metals or rocks. The objective is to relate an observed pattern of preferred orientation to its generating processes and vice versa. In geosciences, texture of minerals in rocks is used to infer constraints on their tectono-metamorphic history. Since most physical properties of crystals, such as elastic moduli, the coefficients of thermal expansion, or chemical resistance to etching depends on crystal symmetry and orientation, the presence of texture imparts directional properties to the polycrystalline material. A major issue of mathematical texture analysis is the resolution of the inverse problem to determine a reasonable orientation density function on SO(3) from measured pole intensities on , which relates to the inverse of the totally geodesic Radon transform. This communication introduces a wavelet approach into mathematical texture analysis. Wavelets on the two-dimensional sphere and on the rotational group SO(3) are discussed, and an algorithms for a wavelet decomposition on both domains following the ideas of Ta-Hsin Li is given. The relationship of these wavelets on both domains with respect to the totally geodesic Radon transform is investigated. In particular, it is shown that the Radon transform of these wavelets on SO(3) are again wavelets on . A novel algorithm for the inversion of experimental pole intensities to an orientation density function based on this relationship is developed.     

地震综合效应场函数及其在地震预报中的应用──（一）地震综合效应场函数及其计算方法

在系统地分析了目前各种测震学地震预报方法科学思路的基础上,认为测震学地震预报方法基本上可以分为两大类。一类是以已经发生的一些地震作为未来可能发生的地震的“因”,即由于已经发生的地震对区域应力场的影响,导致未来发生较强地震。这一类包括的预报方法较多,如空区、条带、ｂ值、地震迁移、相关地震等等及其由此衍生出来的各种方法。另一类是把已经发生的一些地震作为区域应力场增强的“果”,即已经发生的地震是区域应力场增强过程中的一种反映,而未来地震不一定是已经发生的地震所导致的结果。这一类包括“地震窗口”、小震群活动等方法。针对第一类方法,各种预报方法都是力图从地震三要素中提取未来地震的信息,而具体作法又都是利用地震三要素这个多维空间的某个剖面。为了从地震活动诸要素的多维空间提取综合信息,我们对每个地震加入了破裂面方位,构成了地震第四要素,并依据地震４要素建立了地震综合效应场函数。地震综合效应场函数概括了多种测震学地震预报方法的科学思路和预报经验,从而可以形成测震学的综合预报方法。     

Estimation of covariance matrix from geochemical data with observations below detection limits

Multivariate statistical analyses have been extensively applied to geochemical measurements to analyze and aid interpretation of the data. Estimation of the covariance matrix of multivariate observations is the first task in multivariate analysis. However, geochemical data for the rare elements, especially Ag, Au, and platinum-group elements, usually contain observations the below detection limits. In particular, Instrumental Neutron Activation Analysis (INAA) for the rare elements produces multilevel and possibly extremely high detection limits depending on the sample weight. Traditionally, in applying multivariate analysis to such incomplete data, the observations below detection limits are first substituted, for example, each observation below the detection limit is replaced by a certain percentage of that limit, and then the standard statistical computer packages or techniques are used to obtain the analysis of the data. If a number of samples with observations below detection limits is small, or the detection limits are relatively near zero, the results may be reasonable and most geological interpretations or conclusions are probably valid. In this paper, a new method is proposed to estimate the covariance matrix from a dataset containing observations below multilevel detection limits by using the marginal maximum likelihood estimation (MMLE) method. For each pair of variables, sayY andZ whose observations containing below detection limits, the proposed method consists of three steps: (i) for each variable separately obtaining the marginal MLE for the means and the variances, , , , and forY andZ: (ii) defining new variables by and and lettingA=C+D andB=C–D, and obtaining MLE for variances, and forA andB; (iii) estimating the correlation coefficient _YZ by and the covariance _YZ by . The procedure is illustrated by using a precious metal geochemical data set from the Fox River Sill, Manitoba, Canada.