应用探地雷达探测活动断层

在浅覆盖区采用探地雷达探测地震活动断层。通过实验确定出最佳的采集参数和数据处理流程,在雷达剖面上,能够清晰地显示出断层上部的形态特征、上断点埋深和岩土分层。结合钻孔资料,利用雷达剖面上对第四系覆盖的分层结果和上断点所在的层位可以分析和评价断层的活动性。     

应用GPS数据与重力数据确定大地水准面

作为GPS/重力边值问题理论及方法的应用,在对GPS/重力方法确定(似)大地水准面的原理进行简要介绍与分析的基础上,利用收集到的N区的600个GPS/重力数据和48个高精度GPS水准数据,计算出该区域的(似)大地水准面。通过拟合法和系统差直接改正法进行的精度分析表明,应用GPS/重力数据结合水准方法确定的该地区(似)大地水准面的精度达到厘米级精度。     

Extreme value analysis of diamond-size distributions

Extreme value analysis provides a semiparametric method for analyzing the extreme long tails of skew distributions which may be observed when handling mining data. The estimation of important tail characteristics, such as the extreme value index, allows for a discrimination between competing distribution models. It measures the thickness of such long tailed distributions, if only a limited sample is available. This paper stresses the practical implementation of extreme value theory, which is used to discriminate a lognormal from a mixed lognormal distribution in a case study of size distributions for alluvial diamonds.     

Bayesian estimation of seismic hazard for two sites in Switzerland

Seismic hazard analysis is based on data and models, which both are imprecise and uncertain. Especially the interpretation of historical information into earthquake parameters, e.g. earthquake size and location, yields ambiguous and imprecise data. Models based on probability distributions have been developed in order to quantify and represent these uncertainties. Nevertheless, the majority of the procedures applied in seismic hazard assessment do not take into account these uncertainties, nor do they show the variance of the results. Therefore, a procedure based on Bayesian statistics was developed to estimate return periods for different ground motion intensities (MSK scale).Bayesian techniques provide a mathematical model to estimate the distribution of random variables in presence of uncertainties. The developed method estimates the probability distribution of the number of occurrences in a Poisson process described by the parameter . The input data are the historical occurrences of intensities for a particular site, represented by a discrete probability distribution for each earthquake. The calculation of these historical occurrences requires a careful preparation of all input parameters, i.e. a modelling of their uncertainties. The obtained results show that the variance of the recurrence rate is smaller in regions with higher seismic activity than in less active regions. It can also be demonstrated that long return periods cannot be estimated with confidence, because the time period of observation is too short. This indicates that the long return periods obtained by seismic source methods only reflects the delineated seismic sources and the chosen earthquake size distribution law.     

浙闽山区茶叶生产基地评价的探讨

茶叶基地的评价包括对基地的自然和经济条件的评估,应用系统分析方法,将自然和经济条件进行定量的综合评估,用综合评价值区分基地间的差异,最后定性与定量相结合,提出茶叶生产基地的合理布局.     

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.     

云南兰坪-思茅盆地生物地球化学找钾技术方法研究初探

在生物地球化学和“深穿透”理论的指导下,在兰坪-思茅盆地勐野井钾盐矿区及周边开展了生物地球化学找钾技术方法的探索性研究。沿江城县勐野井钾盐矿区及周边一线,对乔木类植物叶子进行了取样,分析,数据处理,特征指标筛选,获得了研究区植物样品主量和微量组分含量背景值,初步圈定了异常区,与以往圈定的找钾远景区较吻合。该区生物地球化学找钾技术取得较好的效果,今后还需扩大采样区域,获得更多样本数据,将找钾特征指标及其异常值的阈值进一步补充完善。     

多硅白云母b0值对澜沧群中压和高压变质的反映

多硅白云母b₀值作为相对地质压力计的理论和方法,已受到各国地质学家的普遍重视。本文以澜沧群多硅白云母作为研究对象,提出运用多硅白云母b₀值区分不同压力变质的方法。研究结果表明澜沧群经历了中压和高压变质作用,两期变质的多硅白云母b₀值分别为9.027Å和9.047Å。     

参数的期望估计及其在形变分析中的应用

利用“参数的期望估计”能准确定位、定量粗差及参数的期望估计不受粗差影响折特殊性质,寻找地壳变形区域和不变形区域,以确定拟稳点,进而进行拟稳变换,分析地菜变,将是一种有效方法。     

Estimation for partially observed Markov processes

Many stochastic process models for environmental data sets assume a process of relatively simple structure which is in some sense partially observed. That is, there is an underlying process (X_n, n 0) or (X_t, t 0) for which the parameters are of interest and physically meaningful, and an observable process (Y_n, n 0) or (Y_t, t 0) which depends on the X process but not otherwise on those parameters. Examples are wide ranging: the Y process may be the X process with missing observations; the Y process may be the X process observed with a noise component; the X process might constitute a random environment for the Y process, as with hidden Markov models; the Y process might be a lower dimensional function or reduction of the X process. In principle, maximum likelihood estimation for the X process parameters can be carried out by some form of the EM algorithm applied to the Y process data. In the paper we review some current methods for exact and approximate maximum likelihood estimation. We illustrate some of the issues by considering how to estimate the parameters of a stochastic Nash cascade model for runoff. In the case of k reservoirs, the outputs of these reservoirs form a k dimensional vector Markov process, of which only the kth coordinate process is observed, usually at a discrete sample of time points.