综合应用多种估算方法于资源储量估算——以内蒙古某冶金熔剂用石英岩矿为例

本文以等高线法、水平投影地质块段法、平行断面法以及水平投影地质块段法配合水平断面法在矿山资源储量估算中的应用实例为背景，对多种储量估算方法在矿山资源储量估算中的综合应用进行研究。经实际应用发现，多种储量估算方法在矿山资源储量估算中的综合应用不但具有高效、准确的特点外，还可最大限度降低各因素对矿体资源储量的影响，使资源储量估算更为准确。     

探边测计算储量方法的数值研究与实际考虑

利用探边测试计算储量有压降法、压力恢复法和麦斯盖特法。实际应用中发现，三种方法计算的储量差别很大。为此，使用油藏数值模拟方法对3种计算方法进行检验。结果证明：压降法计算的储量较为精确，压力恢复法和麦蓁盖特法计算的储量误差较大，只能当作参考。     

任意面积储量计算方法研究

这里介绍了一种任意面积储量计算方法，该方法的核心技术是充分利用现有的石油勘探、开发数据库资料，由计算机来自动确定任意含油面积，进而通过容积法来计算石油储量。该方法解决了用求积仪来求取面积时的大量手工操作，在储量计算过程中自动化程度高，具有方便、灵活、实用的特点。     

限制性克立格法在阿舍勒铜矿储量计算中的研究与应用

为提高矿产储量计算的精确性，本文运用了限制性克立格法。给出了限制性克立格法的计算理论，并设计出限制性克立格法在阿舍勒铜矿中的储量计算流程，实现了对阿舍勒铜矿体的限制性克立格储量计算。结果表明，限制性克立格法的储量计算结果（783654．39t）要比普通克立格法的储量计算结果（706541．53t）更接近于实际勘探值（919454t），限制性克立格储量计算方法能够取得较为理想的预测结果。     

蒙特卡洛法在油气储量估算中的应用

详细论述了蒙特卡洛法的数学原理及其在油气储量估算中的具体使用方法，并通过应用实例说明在油气田的不同勘探开发阶段，根据拥有资料的多少选用适当的数学模型，利用蒙特卡洛法都可以估算出一个具有一定可信度的比较合理的油气储量数值。当一个区块勘探程度较高，拥有资料较多时，用蒙特卡洛法估算的储量与用容积法估算的储量比较接近。     

河南金渠金矿区采用先进的SD法储量计算审定方法效果显著

SD法是一种全新的储量计算和审定方法，是我国使用的三大储量计算方法（传统法、克里格法和SD法）之一。根据国土资源部的指示和 要求，三门峡金渠集团有限公司和北京恩地科技发展有限责任公司共同对河南省灵宝市金渠金矿区的6条矿脉、10个矿体的资源储量运用SD斜曲面法进行了全面的复核计算，有效地确定了各矿脉和矿体的储量数值及其地质可靠程度。     

可地浸砂岩型铀矿储量计算中的物探参数研究

可地浸砂岩型铀矿储量计算中的物探参数有密度，湿度，铀平衡系数，镭氡平衡系数，有效原子序数和钍钾元素干扰，它们在铀矿区的变化规律和数值大小，直接影响铀矿的储量计算，本文就新疆十红滩可地浸砂岩型铀矿床储量计算中的物探参数在采样，测定，数据计算和整理，资料分析研究方面总结了一套适合可地浸砂岩型铀矿的室内外工作方法，为铀矿储量计算提供了准确的物探参数修正值，在该矿区的储量计算中达到了预期的效果。     

克服地质统计学矿床建模中主观因素影响技术研究

精确的矿石储量估算是矿山设计、生产及管理的重要依据，地质统计学方法由于其考虑了区域化变量的结构性和随机性的二重性特征，获得了日益广泛的应用。然而，由于地质统计学方法是建立在一定假设的基础上，再加之各种主观因素的影响，地质统计学储量估算往往存在一定的偏差。在总结前人工作及地质统计学储量估算工作经验的基础上，认为影响估值精度的因素可归纳为两个方面：矿床具体条件及取样情况(客观因素)；储量计算时的处理手段和方法(主观因素)，提出克服主观因素是解决偏差产生的重要途径，对主要主观因素的影响及解决办法提出了较为详尽的论述。     

我国矿产资源储量管理已与国际接轨

我国原固体矿产资源储量分类标准存在着储量的涵盖太宽泛，可行性评价程度低，经济意义不突同等问题，不适应市场经济的需求，难以与国际分类对比，新分类标准根据经济意义，可行性评价阶段和地质可靠程度，把固体矿产资源储量分为储量，基础储量，资源量三大类16种类型，其最大特点是对矿产资源储量赋予了经济意义。     

我国储量统计将步入新轨道

据国土资源报2001－06－29报道：已经运行了半个多世纪的我国矿产资源储量统计制度将发生重大变革，从明年1月起，这项内容将桉《固体矿产资源／储量分类》国家标准实施。为此，国土资源部储量司6月21日在哈尔滨举办了储量统计软件培训班，对此项改革作了部署。矿产资源储量登记统计是资源合理利用和保护的基础工作，统计数据的可靠程度关系到国家宏观决策和微观管理的合理性、1999年12月1日《固体矿产资源／储量分类》国家标准实施后，国土资源部首先对45种矿产的储量进行套改，今年将完成其他种类矿产储量的套改：从明年起，矿产资源储量…     

Application of universal kriging for estimation of earthquake ground motion: Statistical significance of results

Universal kriging is compared with ordinary kriging for estimation of earthquake ground motion. Ordinary kriging is based on a stationary random function model; universal kriging is based on a nonstationary random function model representing first-order drift. Accuracy of universal kriging is compared with that for ordinary kriging; cross-validation is used as the basis for comparison. Hypothesis testing on these results shows that accuracy obtained using universal kriging is not significantly different from accuracy obtained using ordinary kriging. Tests based on normal distribution assumptions are applied to errors measured in the cross-validation procedure;t andF tests reveal no evidence to suggest universal and ordinary kriging are different for estimation of earthquake ground motion. Nonparametric hypothesis tests applied to these errors and jackknife statistics yield the same conclusion: universal and ordinary kriging are not significantly different for this application as determined by a cross-validation procedure. These results are based on application to four independent data sets (four different seismic events).     

Adding bounds to kriging

The ordinary kriging interpolation algorithm is extended by the inclusion of explicit lower and upper bounds on the estimate. The associated estimation variance is written as the ordinary kriging variance plus a non-negative correction term.     

Adding bounds to kriging

The ordinary kriging interpolation algorithm is extended by the inclusion of explicit lower and upper bounds on the estimate. The associated estimation variance is written as the ordinary kriging variance plus a non-negative correction term.     

Comparison of kriging techniques in a space-time context

Space-time processes constitute a particular class, requiring suitable tools in order to predict values in time and space, such as a space-time variogram or covariance function. The space-time co-variance function is defined and linked to the Linear Model of Coregionalization under second-order space-time stationarity. Simple and ordinary space-time kriging systems are compared to simple and ordinary cokriging and their differences for unbiasedness conditions are underlined. The ordinary space-time kriging estimation then is applied to simulated data. Prediction variances and prediction errors are compared with those for ordinary kriging and cokriging under different unbiasedness conditions using a cross-validation. The results show that space-time kriging tend to produce lower prediction variances and prediction errors that kriging and cokriging.     

地下水的资源功能与易遭污染脆弱性空间关系研究

本文以滹滏平原为研究区,从地下水资源功能和地下水易遭污染脆弱性内在联系为切入点,采用统计分析的方法,探讨地下水的资源功能与易遭污染脆弱性关系.结果表明,当地下水资源功能为一般时,地下水易遭污染脆弱性为一般或较低;地下水资源功能强或较弱时,地下水易遭污染脆弱性较高;地下水资源功能较强和弱时,地下水易遭污染脆弱性较低.当地下水易遭污染脆弱性一般时,地下水资源功能为一般或较强;地下水易遭污染脆弱性高或低时,地下水资源功能较弱;地下水易遭污染脆弱性较高或较低时,地下水资源功能强或较弱.然后从地下水补给和含水层状况等二者之间共有的评价指标分析了地下水资源功能较低和脆弱性低时形成多种对应关系的机理.     

Compensating for estimation smoothing in kriging

Smoothing is a characteristic inherent to all minimum mean-square-error spatial estimators such as kriging. Cross-validation can be used to detect and model such smoothing. Inversion of the model produces a new estimator—compensated kriging. A numerical comparison based on an exhaustive permeability sampling of a 4-ft² slab of Berea Sandstone shows that the estimation surface generated by compensated kriging has properties intermediate between those generated by ordinary kriging and stochastic realizations resulting from simulated annealing and sequential Gaussian simulation. The frequency distribution is well reproduced by the compensated kriging surface, which also approximates the experimental semivariogram well—better than ordinary kriging, but not as well as stochastic realizations. Compensated kriging produces surfaces that are more accurate than stochastic realizations, but not as accurate as ordinary kriging.     

拓扑克里格法与普通克里格法在区域洪水频率分析中的比较研究

依据北江(珠江流域支流)流域6个水文测站年最大洪峰流量资料,分别用Top-kriging(拓扑克里格法)和普通克里格法进行区域洪水频率估计。采用均方根误差作为频率分布线型拟合优度指标。运用线性矩法进行单站洪水频率分析,确定10、50、100、1000年一遇设计洪水值。在此基础上,从Topkriging和普通克里格法设计洪水估计不确定性和相对线性矩法单站洪水频率的估计误差两个方面比较Top-kriging和普通克里格法。结果表明:(1)Top-kriging法是更好的线性无偏估计,相比普通克里格法更适合于区域洪水频率估计;(2)Top-kriging法设计洪水估计不确定性明显小于普通克里格法;(3)Top-kriging法设计洪水估计结果更接近线性矩法单站洪水频率分析结果。     

Criteria to Compare Estimation Methods of Regionalized Compositions

The additive logratio (alr) transformation has been used in several case studies to predict regionalized compositions using standard geostatistical estimation methods such as ordinary kriging and ordinary cokriging. It is a simple method that allows application to transformed data all the body of knowledge available for geostatistical analysis of coregionalizations without a constant sum constraint. To compare the performance of methods, it is customary to use a univariate crossvalidation approach based on the leaving-one-out technique to evaluate the performance for each attribute separately. For multivariate observations this approach is difficult to interpret in terms of overall performance. Therefore, we propose using appropriate distances in real space and in the simplex, to improve the crossvalidation approach and, going a step forward, to adapt the concept of stress from multidimensional scaling to obtain a global measure of performance for each method. The Lyons West oil field of Kansas is used to illustrate the impactof using different distances in the performance of ordinary kriging versus ordinary cokriging.     

Geostatistical approach for identification of transmissivity structure at Dulliu area in Taiwan

 A thorough understanding of the characteristics of transmissivity makes groundwater deterministic models more accurate. These transmissivity data characteristics occasionally possess a complicated spatial variation over an investigated site. This study presents both geostatistical estimation and conditional simulation methods to generate spatial transmissivity maps. The measured transmissivity data from the Dulliu area in Yun-Lin county, Taiwan, is used as the case study. The spatial transmissivity maps are simulated by using sequential Gaussian simulation (SGS), and estimated by using natural log ordinary kriging and ordinary kriging. Estimation and simulation results indicate that SGS can reproduce the spatial structure of the investigated data. Furthermore, displaying a low spatial variability does not allow the ordinary kriging and natural log kriging estimates to fit the spatial structure and small-scale variation for the investigated data. The maps of kriging estimates are smoother than those of other simulations. A SGS with multiple realizations has significant advantages over ordinary kriging and even natural log kriging techniques at a site with a high variation in investigated data. These results are displayed in geographic information systems (GIS) as basic information for further groundwater study. Received: 27 August 1999 · Accepted: 22 February 2000     

土壤水分空间插值的克里金平滑效应修正方法

地统计学的普通克里金法是研究土壤水分空间变异特性和描绘其空间分布的有效方法。但与其它建立在最小二乘标准上的插值方法一样,普通克里金法也存在着平滑效应问题,即估计值的变异程度比实际要小,从而导致估计值往往不能反映出土壤水分真实的空间变化特征。结合实际的土壤水分监测数据,采用Yamamoto提出的一套针对普通克里金估计值进行后处理的方法,较好地解决了普通克里金法平滑效应的问题,在保证局部估计值精度的同时,重现了土壤含水率在空间的分布与变化特征。