共查询到20条相似文献，搜索用时 15 毫秒
1.
The aim of this work is to investigate whether it is possible to determine a critical sampling grid density for a given ore body, above which further improvement in the accuracy of the estimated ore reserves would be small or negligible. The methodology employed is based on the theory of information. First, it is proven that the range of influence, when appears in the variogram function, is a measure of the maximum variability frequency observed in the ore body. Then, a simple application of the well-known sampling theorem shows that, under certain assumptions, it is possible to define a critical sampling density as mentioned before. An approximate rule of thumb can then be stated: that critical sampling grid size is half the range of influence observed in the variogram. 相似文献
2.
Sample schemes used in geostatistical surveys must be suitable for both variogram estimation and kriging. Previously schemes
have been optimized for one of these steps in isolation. Ordinary kriging generally requires the sampling locations to be
evenly dispersed over the region. Variogram estimation requires a more irregular pattern of sampling locations since comparisons
must be made between measurements separated by all lags up to and beyond the range of spatial correlation. Previous studies
have not considered how to combine these optimized schemes into a single survey and how to decide what proportion of sampling
effort should be devoted to variogram estimation and what proportion devoted to kriging
An expression for the total error in a geostatistical survey accounting for uncertainty due to both ordinary kriging and variogram
uncertainty is derived. In the same manner as the kriging variance, this expression is a function of the variogram but not
of the sampled response data. If a particular variogram is assumed the total error in a geostatistical survey may be estimated
prior to sampling. We can therefore design an optimal sample scheme for the combined processes of variogram estimation and
ordinary kriging by minimizing this expression. The minimization is achieved by spatial simulated annealing. The resulting
sample schemes ensure that the region is fairly evenly covered but include some close pairs to analyse the spatial correlation
over short distances. The form of these optimal sample schemes is sensitive to the assumed variogram. Therefore a Bayesian
approach is adopted where, rather than assuming a single variogram, we minimize the expected total error over a distribution
of plausible variograms. This is computationally expensive so a strategy is suggested to reduce the number of computations
required 相似文献
3.
Guillaume Larocque Pierre Dutilleul Bernard Pelletier James W. Fyles 《Mathematical Geology》2007,39(3):263-288
Coregionalization analysis has been presented as a method of multi-scale analysis for multivariate spatial data. Despite an
increasing use of this method in environmental and earth sciences, the uncertainty associated with the estimation of parameters
in coregionalization analysis (e.g., sills and functions of sills) is potentially high and has not yet been characterized.
This article aims to discuss the theory underlying coregionalization analysis and assess the robustness and limits of the
method. A theoretical framework is developed to calculate the ergodic and fluctuation variance-covariance matrices of least-squares
estimators of sills in the linear model of coregionalization. To adjust for the positive semidefiniteness constraint on estimated
coregionalization matrices, a confidence interval estimation procedure for sills and functions of sills is presented. Thereafter,
the relative importance of uncertainty measures (bias and variance) for sills and structural coefficients of correlation and
determination is assessed under different scenarios to identify factors controlling their uncertainty. Our results show that
the sampling grid density, the choice of the least-squares estimator of sills, the positive semidefiniteness constraint, the
presence of scale dependence in the correlations, and the number and range of variogram models, all affect the level of uncertainty,
sometimes through multiple interactions. The asymptotic properties of variogram model parameter estimators in a bounded sampling
domain impose a theoretical limit to their accuracy and precision. Because of this limit, the uncertainty was found to be
high for several scenarios, especially with three variogram models, and was often more dependent on the ratio of variogram
range to domain extent than on the sampling grid density. In practice, in the coregionalization analysis of a real dataset,
the circular requirement for sill estimates in the calculation of uncertainty measures makes the quantification of uncertainty
very problematic, if not impossible. The use of coregionalization analysis must be made with due knowledge of the uncertainty
levels and limits of the method. 相似文献
4.
Estimation of non-ergodic variograms and their sampling variance by design-based sampling strategies
Design-based sampling strategies based on classical sampling theory offer unprecedented potentials for estimation of non-ergodic variograms. Unbiased and uncorrelated estimates of the semivariance at the selected lags and of its sampling variance can be simply obtained. These estimates are robust against deviations from an assumed spatial autocorrelation model. The same holds for the variogram model parameters and their sampling (co)variances. Moreover, an objective measure for lack of fit of the fitted model can simply be derived. The estimators for two basic sampling designs, simple random sampling and stratified simple random sampling of pairs of points, are presented. The first has been tested in real world for estimating the non-ergodic variograms of three soil properties. The parameters of variogram models and their sampling (co)variances were estimated with 72 pairs of points distributed over six lags. 相似文献
5.
Guillaume Larocque Pierre Dutilleul Bernard Pelletier James W. Fyles 《Mathematical Geosciences》2007,39(3):263-288
Coregionalization analysis has been presented as a method of multi-scale analysis for multivariate spatial data. Despite an increasing use of this method in environmental and earth sciences, the uncertainty associated with the estimation of parameters in coregionalization analysis (e.g., sills and functions of sills) is potentially high and has not yet been characterized. This article aims to discuss the theory underlying coregionalization analysis and assess the robustness and limits of the method. A theoretical framework is developed to calculate the ergodic and fluctuation variance-covariance matrices of least-squares estimators of sills in the linear model of coregionalization. To adjust for the positive semidefiniteness constraint on estimated coregionalization matrices, a confidence interval estimation procedure for sills and functions of sills is presented. Thereafter, the relative importance of uncertainty measures (bias and variance) for sills and structural coefficients of correlation and determination is assessed under different scenarios to identify factors controlling their uncertainty. Our results show that the sampling grid density, the choice of the least-squares estimator of sills, the positive semidefiniteness constraint, the presence of scale dependence in the correlations, and the number and range of variogram models, all affect the level of uncertainty, sometimes through multiple interactions. The asymptotic properties of variogram model parameter estimators in a bounded sampling domain impose a theoretical limit to their accuracy and precision. Because of this limit, the uncertainty was found to be high for several scenarios, especially with three variogram models, and was often more dependent on the ratio of variogram range to domain extent than on the sampling grid density. In practice, in the coregionalization analysis of a real dataset, the circular requirement for sill estimates in the calculation of uncertainty measures makes the quantification of uncertainty very problematic, if not impossible. The use of coregionalization analysis must be made with due knowledge of the uncertainty levels and limits of the method. 相似文献
6.
When estimating the mean value of a variable, or the total amount of a resource, within a specified region it is desirable to report an estimated standard error for the resulting estimate. If the sample sites are selected according to a probability sampling design, it usually is possible to construct an appropriate design-based standard error estimate. One exception is systematic sampling for which no such standard error estimator exists. However, a slight modification of systematic sampling, termed 2-step tessellation stratified (2TS) sampling, does permit the estimation of design-based standard errors. This paper develops a design-based standard error estimator for 2TS sampling. It is shown that the Taylor series approximation to the variance of the sample mean under 2TS sampling may be expressed in terms of either a deterministic variogram or a deterministic covariance function. Variance estimation then can be approached through the estimation of a variogram or a covariance function. The resulting standard error estimators are compared to some more traditional variance estimators through a simulation study. The simulation results show that estimators based on the new approach may perform better than traditional variance estimators. 相似文献
7.
Geostatistical calculations were carried out on two completely exhausted open-pit bauxite mines in the Iharkut bauxite district, Hungary. Fictitious regular drilling grids were laid on the maps, and horizontal variograms were calculated for drilling grids evaluating the bauxite surface, footwall surface, and bauxite thickness. Point kriging was carried out for all three parameters. Bauxite reserves were calculated using block kriging for bauxite thickness. The total estimation variance of the reserves has been established. Results were compared with real reserves obtained from the mine maps. 相似文献
8.
克里格法在离子吸附型稀土矿勘查储量估算中的应用 总被引：1，自引：1，他引：0
我国在离子吸附型稀土矿勘查工作中,一般采用地质块段法估算储量,块段法是将矿体划分为不同厚度的块段投影到水平或垂直方向上,块段的划分、各块段的面积和厚度、品位都会影响储量估算结果。本文以赣南某离子吸附型稀土矿床作为研究对象,基于先期勘探钻孔数据资料,运用三维建模软件创建了该矿床钻孔数据库,建立了矿区内矿体的三维DTM模型;采用克里格法对矿体进行稀土氧化物品位分析,将克里格法的储量计算结果与块段法的储量计算结果作对比分析。结果显示,克里格法计算的矿体体积比块段法增加了11.8%,稀土氧化物储量增加了15%,与实际勘探数据相比较,克里格法的计算结果基本合理,且具有快速、准确、方便的特点。本文利用自主开发的以克里格法为基础的三维数字矿山经济评价系统中价格-边界品位敏感性分析模块,动态设置边界品位,灵活圈定不同价格下经济可采的矿体边界,如当精矿的市场价格从10万元/吨变化为12万元/吨时,通过计算获得了此矿山经济可采矿体的空间扩展范围。基于克里格法的三维估算系统能够帮助矿山选择合理的采矿工程布置,有利于满足矿山动态管理的需要以及保证矿产资源的合理利用。 相似文献
9.
煤炭质量核心指标的估算有利于煤炭质量的管控,并为智能开采、分质开采提供科学依据。将克里金插值法引入到煤质指标估算模型的建立,利用差分进化算法求解其变差函数的模型参数;针对在差分进化过程中因"早熟"现象导致最优解被破坏的问题,在变异过程中设计可动态修正变异方向的缩放因子,提出修正变异方向的自适应差分进化算法(UMDE)来确定变差函数的模型参数,并用该方法对煤矿井下未开采区域的全水分进行克里金插值。通过交叉验证与对比实验,证明基于自适应差分克里金方法(UMDE-Kriging)构建的煤质指标估算模型较其他优化方案在估算精度上有显著提升。 相似文献
10.
Subhash Lele 《Mathematical Geology》1995,27(5):673-692
Two important problems in the practical implementation of kriging are: (1) estimation of the variogram, and (2) estimation of the prediction error. In this paper, a nonparametric estimator of the variogram to circumvent the problem of the precise choice of a variogram model is proposed. Using orthogonal decomposition of the kriging predictor and the prediction error, a method for selecting, what may be considered, a statistical neighborhood is suggested. The prediction error estimates based on this scheme, in fact, reflects the true prediction error, thus leading to proper coverage for the corresponding prediction interval. By simulations and a reanalysis of published data, it is shown that the proposals made in this paper are useful in practice. 相似文献
11.
Before optimal linear prediction can be performed on spatial data sets, the variogram is usually estimated at various lags and a parametric model is fitted to those estimates. Apart from possible a priori knowledge about the process and the user's subjectivity, there is no standard methodology for choosing among valid variogram models like the spherical or the exponential ones. This paper discusses the nonparametric estimation of the variogram and its derivative, based on the spectral representation of positive definite functions. The use of the estimated derivative to help choose among valid parametric variogram models is presented. Once a model is selected, its parameters can be estimated—for example, by generalized least squares. A small simulation study is performed that demonstrates the usefulness of estimating the derivative to help model selection and illustrates the issue of aliasing. MATLAB software for nonparametric variogram derivative estimation is available at http://www-math.mit.edu/~gorsich/derivative.html. An application to the Walker Lake data set is also presented. 相似文献
12.
磁共振探测估算含水层渗透系数的原位试验研究 总被引：1，自引：0，他引：1
通过一个完整的磁共振探测（MRS）、钻探、抽水试验过程,开展了MRS估算含水层渗透系数的原位试验研究。在分析MRS估算渗透系数准确性的基础上,系统剖析了引起准确性差异的主要因素,并对进一步提高估算效果提出了建议。结果显示：（1）采用现阶段常用的参数设置,与抽水试验计算值相比,MRS估算渗透系数的差值为抽水试验计算值的17.59%。（2）MRS推断的含水层顶板、底板埋深与钻孔揭示的信息相比,差值分别为4.11m、1.03m,表明其对估算渗透系数准确性的影响较小。（3）CP值是影响估算准确性的重要因素,其值为10-9数量级符合大多数地层的特点。另外,通过在已知渗透系数的钻孔附近进行MRS,从而获取CP参考值,应用该值估算的渗透系数准确性高于常用的参数设置。（4）指数a、b设置方面,应用Seevers公式（a=1、b=2）的估算效果优于Kenyon公式（a=4、b=2）。本成果有助于提高MRS估算渗透系数方法在野外条件下的适用性。 相似文献
13.
Estimating Variogram Uncertainty 总被引：10，自引：0，他引：10
The variogram is central to any geostatistical survey, but the precision of a variogram estimated from sample data by the method of moments is unknown. It is important to be able to quantify variogram uncertainty to ensure that the variogram estimate is sufficiently accurate for kriging. In previous studies theoretical expressions have been derived to approximate uncertainty in both estimates of the experimental variogram and fitted variogram models. These expressions rely upon various statistical assumptions about the data and are largely untested. They express variogram uncertainty as functions of the sampling positions and the underlying variogram. Thus the expressions can be used to design efficient sampling schemes for estimating a particular variogram. Extensive simulation tests show that for a Gaussian variable with a known variogram, the expression for the uncertainty of the experimental variogram estimate is accurate. In practice however, the variogram of the variable is unknown and the fitted variogram model must be used instead. For sampling schemes of 100 points or more this has only a small effect on the accuracy of the uncertainty estimate. The theoretical expressions for the uncertainty of fitted variogram models generally overestimate the precision of fitted parameters. The uncertainty of the fitted parameters can be determined more accurately by simulating multiple experimental variograms and fitting variogram models to these. The tests emphasize the importance of distinguishing between the variogram of the field being surveyed and the variogram of the random process which generated the field. These variograms are not necessarily identical. Most studies of variogram uncertainty describe the uncertainty associated with the variogram of the random process. Generally however, it is the variogram of the field being surveyed which is of interest. For intensive sampling schemes, estimates of the field variogram are significantly more precise than estimates of the random process variogram. It is important, when designing efficient sampling schemes or fitting variogram models, that the appropriate expression for variogram uncertainty is applied. 相似文献
14.
The reliability of using fractal dimension (D) as a quantitative parameter to describe geological variables is dependent mainly
on the accuracy of estimated D values from observed data. Two widely used methods for the estimation of fractal dimensions
are based on fitting a fractal model to experimental variograms or power-spectra on a log-log plot. The purpose of this paper
is to study the uncertainty in the fractal dimension estimated by these two methods. The results indicate that both spectrum
and variogram methods result in biased estimates of the D value. Fractal dimension calculated by these two methods for the
same data will be different unless the bias is properly corrected. The spectral method results in overestimated D values.
The variogram method has a critical fractal dimension, below which overestimation occurs and above which underestimation occurs.
On the bases of 36,000 simulated realizations we propose empirical formulae to correct for biases in the spectral and variogram
estimated fractal dimension. Pitfalls in estimating fractal dimension from data contaminated by white noise or data having
several fractal components have been identified and illustrated by simulated examples. 相似文献
15.
16.
If a particular distribution for kriging error may be assumed, confidence intervals can be estimated and contract risk can be assessed. Contract risk is defined as the probability that a block grade will exceed some specified limit. In coal mining, this specified limit will be set in a coal sales agreement. A key assumption necessary to implement the geostatistical model is that of local stationarity in the variogram. In a typical project, data limitations prevent a detailed examination of the stationarity assumption. In this paper, the distribution of kriging error and scale of variogram stationarity are examined for a coal property in northern West Virginia. 相似文献
17.
In the linear model of coregionalization (LMC), when applicable to the experimental direct variograms and the experimental
cross variogram computed for two random functions, the variability of and relationships between the random functions are modeled
with the same basis functions. In particular, structural correlations can be defined from entries of sill matrices (coregionalization
matrices) under second-order stationarity. In this article, modified t-tests are proposed for assessing the statistical significance of estimated structural correlations. Their specific aspects
and fundamental differences, compared with an existing modified t-test for global correlation analysis with spatial data, are discussed via estimated effective sample sizes, in relation to
the superimposition of random structural components, the range of autocorrelation, the presence of correlation at another
structure, and the sampling scheme. Accordingly, simulation results are presented for one structure versus two structures
(one without and the other with autocorrelation). The performance of tests is shown to be related to the uncertainty associated
with the estimation of variogram model parameters (range, sill matrix entries), because these are involved in the test statistic
and the degrees of freedom of the associated t-distribution through the estimated effective sample size. Under the second-order stationarity and LMC assumptions, the proposed
tests are generally valid. 相似文献
18.
19.
瑶岭钨矿区寒武纪地层特征对寻找石英脉型黑
钨矿的指示意义 总被引：1，自引：0，他引：1
瑶岭钨矿由北矿区、东矿区和白基寨矿区3个矿区组成,其中北矿区是主要生产矿区,以石英脉型黑钨矿为主.在对北矿区大比例尺填图过程中,我们发现矿区地表地层单一,主要为寒武纪沉积的变质砂岩和板岩.针时这种情况,我们采用土壤地球化学测量、物探磁法测量、钻探等工程方法对寒武纪地层进行研究,综合分析了矿区地质特征、地球物理磁法特征及地球化学特征在对矿脉水平分布、矿脉垂直分布、蚀变矿物因素、构造因素、热接触因素和成矿因素的外在表现,从而建立起矿区寒武纪地层对矿化的指示体系表,并指出瑶岭钨矿北区深部和东南部有很大的找矿潜力,是值得继续找矿的有利目标地段. 相似文献
20.
现有矿业软件的储量估算模块核心方法主要基于地质统计学。文章以河北迁安羊崖山铁矿床为例,通过3DMine软件在数据资料准备、变异函数确定、块体模型构建及储量报告等多方面的应用,规范了矿业软件在资源量估算方面的工作流程。利用普通克里金法和距离幂次反比法分别进行品位插值,完成资源量估算;并与传统储量估算结果进行比较,分析产生误差原因,建立了开采境界模型,计算了矿山开采储量和保有储量;利用赋值参数分析矿体控制程度,指导未来探矿工程重点部位。 相似文献