共查询到20条相似文献，搜索用时 31 毫秒
1.
Xavier Emery 《Mathematical Geology》2006,38(7):801-819
Multigaussian kriging aims at estimating the local distributions of regionalized variables and functions of these variables
(transfer or recovery functions) at unsampled locations. In this paper, we focus on the evaluation of the recoverable reserves
in an ore deposit accounting for a change of support and information effect caused by ore/waste misclassifications. Two approaches
are proposed: the multigaussian model with Monte Carlo integration and the discrete Gaussian model. The latter is simpler
to use but requires stronger hypotheses than the former. In each model, ordinary multigaussian kriging gives unbiased estimates
of the recoverable reserves that do not utilize the mean value of the normal score data.
The concepts are illustrated through a case study on a copper deposit which shows that local estimates of the metal content
based on ordinary multigaussian kriging are close to the optimal conditional expectation when the data are abundant and are
not dominated by the global mean when the data are scarce. The two proposed approaches (Monte Carlo integration and discrete
Gaussian model) lead to similar results when compared to two other geostatistical methods: service variables and ordinary
indicator kriging, which show strong deviations from conditional expectation. 相似文献
2.
Ali Akbar Daya 《Journal of the Geological Society of India》2014,83(5):567-576
Most significant iron ore deposits in Iran are located in Central Iran Zone. These deposits belong to the Bafq mining district. The Bafq mining district is located in the Early Cambrian Kashmar-Kerman volcanic arc of Central Iran. Linear estimation of regionalized variables (for example by inverse distance weighting or ordinary Kriging) results in relatively high estimation variances, i.e. the estimates have very low precision. Assessment of project economics (or other critical decision making) based on linear estimation is therefore risky. Non-linear estimation methods like disjunctive kriging perform better and the lower estimation variance allows less risky economic decision-making. Another advantage of disjunctive kriging is that it allows estimation of functions of the primary variable, which here is the grade (Fe %) of the ore. In particular it permits estimation of indicator functions defined using thresholds on the primary variable. This paper is devoted to application of disjunctive kriging method in Choghart North Anomaly iron ore deposit in Central Iran, Yazd province, Iran. In this study, the Fe concentration of Choghart North Anomaly iron ore deposit was modelled and estimated. The exploration data consists of borehole samples measuring the Fe concentration. A Gaussian isofactorial model is fitted to these data and disjunctive kriging was used to estimate the regionalized variable (Fe %) at unsampled locations and to assess the probabilities that the actual concentrations exceed a threshold value at a given location. Consequently a three dimensional model of probability of exceeding a threshold value and the estimated value are provided by disjunctive kriging to divide the ore into an economic and uneconomic part on the basis of estimation of indicator functions using thresholds grades defined on point support. The tools and concepts are complemented by a set of computer programs that are applied to the case study. The study showed that disjunctive kriging can be applied successfully for modeling the grade of an ore deposit. Results showed that the correlation between the estimated value and real value at locations close to each other is 81.9%. 相似文献
3.
Models for Support and Information Effects: A Comparative Study 总被引：1，自引：0，他引：1
The recoverable reserves in an ore deposit depend on several factors, in particular the size of the selective mining units (support effect) and the misclassifications when sending these units to mill or dump according to their estimated grade (information effect). Both effects imply a loss of selectivity and have to be correctly forecasted. In this work, several models are reviewed and applied to a synthetic ore deposit characterized by a highly skewed grade histogram and a spatial connectivity of high grades. The affine correction, mosaic correction, and discrete Gaussian model are compared when assessing the global recoverable reserves, whereas local estimations are performed by indicator kriging with affine correction, bigaussian disjunctive kriging, and multigaussian conditional expectation. Despite their convenience and simplicity, distribution-free methods like affine correction or indicator kriging have a poorer accuracy than the other methods. In the global framework, the discrete Gaussian model is a better alternative and is based on mild assumptions. Local estimations are not accurate and may be improved by resorting to a more suitable parametric model or to conditional simulations. 相似文献
4.
Optimally locating additional drill holes in three dimensions using grade and simulated annealing 总被引：2，自引：0，他引：2
Saeed Soltani Mohammadi Ardeshir Hezarkhani A. Erhan Tercan 《Journal of the Geological Society of India》2012,80(5):700-706
Average kriging variance is a standard tool used in optimization of the location of additional drill holes. However, this tool cannot distinguish between areas with different priorities. This limitation could be eliminated by using weighted average kriging variance. This paper extends the problem of optimal location to three dimensional cases, use grade as a weight and search optimum locations by simulated annealing. Weighted average kriging variance is used as objective function. The method is applied to a copper deposit. Results have shown that weighting of the estimation variance with ??grade?? is effective only when the difference among the grades estimated for different blocks is considerable. 相似文献
5.
Kriging Prediction Intervals Based on Semiparametric Bootstrap 总被引：1，自引：0，他引：1
Kriging is a widely used method for prediction, which, given observations of a (spatial) process, yields the best linear unbiased
predictor of the process at a new location. The construction of corresponding prediction intervals typically relies on Gaussian
assumptions. Here we show that the distribution of kriging predictors for non-Gaussian processes may be far from Gaussian,
even asymptotically. This emphasizes the need for other ways to construct prediction intervals. We propose a semiparametric
bootstrap method with focus on the ordinary kriging predictor. No distributional assumptions about the data generating process
are needed. A simulation study for Gaussian as well as lognormal processes shows that the semiparametric bootstrap method
works well. For the lognormal process we see significant improvement in coverage probability compared to traditional methods
relying on Gaussian assumptions. 相似文献
6.
Masoud Monjezi Majid Rajabalizadeh Kashani Mohammad Ataei 《Arabian Journal of Geosciences》2013,6(1):123-128
Grade estimation is very important in designing open pits. In the process of grade estimation, underestimation can result in loss of economic ore, whereas overestimation would unnecessarily increase stripping ratio. Normally, kriging method, which suffers from underestimation and/or overestimation due to smoothing effect, is used for grade estimation. To overcome drawbacks of the kriging method, more efficient techniques such as conditional simulation can be applied. In this paper, utilizing sequential Gaussian conditional simulation, grade models were constructed for Sungun copper deposit situated in the North West of Iran. According to the obtained results, it was observed that conditional simulation can effectively cope with the weakness of kriging method. Also, it was observed that as compared to the kriging method, grade distribution, resulted from the conditional simulation, is almost identical to that of the real exploration data. Accordingly, using conditional simulation, the amount of mineable ore was significantly increased, and also, average net present value as the mines’ most important economic indicator was improved by 40%. 相似文献
7.
Xavier Emery 《Mathematical Geology》2005,37(3):295-319
Multigaussian kriging is used in geostatistical applications to assess the recoverable reserves in ore deposits, or the probability for a contaminant to exceed a critical threshold. However, in general, the estimates have to be calculated by a numerical integration (Monte Carlo approach). In this paper, we propose analytical expressions to compute the multigaussian kriging estimator and its estimation variance, thanks to polynomial expansions. Three extensions are then considered, which are essential for mining and environmental applications: accounting for an unknown and locally varying mean (local stationarity), accounting for a block-support correction, and estimating spatial averages. All these extensions can be combined; they generalize several known techniques like ordinary lognormal kriging and uniform conditioning by a Gaussian value. An application of the concepts to a porphyry copper deposit shows that the proposed “ordinary multigaussian kriging” approach leads to more realistic estimates of the recoverable reserves than the conventional methods (disjunctive and simple multigaussian krigings), in particular in the nonmineralized undersampled areas. 相似文献
8.
V. Kameshwara Rao C. R. Rao A. C. Narayana 《Journal of the Geological Society of India》2014,83(5):549-554
Conventional methods of ore deposit estimates are time consuming, whereas geostatistical methods provide quick and reliable estimates with minimum variance. Geostatistical tools, semi-variograms and kriging, have been used for estimation of grades of an iron ore deposit in the present study. In order to model the deposit and estimate grade, 4537 samples collected from 93 boreholes were used in the study. 3-D data have been converted to 2-D for analyzing the variation of Fe within the boreholes. For each borehole, the weighted mean of Fe grade and its coefficient of variation (CV) are calculated and further analysis is carried out for these two variables. Semi-variogram model suggests that the deposit extends over a zone of influence up to 700 m. Grade maps of kriged estimates reveal that the iron ore deposit is distributed in three distinct zones. 相似文献
9.
This work deals with the joint simulation of copper grade (as a continuous regionalized variable) and rock type (as a categorical variable) in Lince–Estefanía deposit, located in northern Chile. The region under study is heterogeneous, containing three main rock types (intrusive, andesite and breccia bodies) with different copper grade distributions. To perform joint simulation, the multi-Gaussian and pluriGaussian models are used in a combined form. To this end, three auxiliary Gaussian random fields are considered, one for simulating copper grade, up to a monotonic transformation, and two for simulating rock types according to a given truncation rule. Furthermore, the dependence between copper grade and rock types is reproduced by considering cross correlations between these Gaussian random fields. To investigate the benefits of the joint simulation algorithm, copper grade and rock types are also simulated by the traditional cascade approach and the results are compared. It is shown that the cascade approach produces hard boundaries, that is, abrupt transitions of copper grades when crossing rock-type boundaries, a condition that does not exist in the study area according to the contact analysis held on the available data. In contrast, the joint simulation approach produces gradual transitions of the copper grade near the rock-type boundaries and is more suited to the actual data. 相似文献
10.
Compensating for estimation smoothing in kriging 总被引：2，自引：0，他引：2
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. 相似文献
11.
Obtaining accurate geological boundaries and assessing the uncertainty in these limits are critical for effective ore resource and reserve estimation. The uncertainty in the extent of an ore body can be the largest source of uncertainty in ore resource estimation when drilling is sparse. These limits are traditionally interpreted deterministically and it can be difficult to quantify uncertainty in the boundary and its impact on ore tonnage. The proposed methodology is to consider stochastic modeling of the ore boundary with a distance function recoding of the available data. This technique is modified to incorporate non-stationarities in the form of a locally varying anisotropy field used in kriging and sequential Gaussian simulation. Implementing locally varying anisotropy kriging retains the geologically realistic features of a deterministic model while allowing for a stochastic assessment of uncertainty. A case study of a gold deposit in Northern Canada is used to demonstrate the methodology. The proposed technique generates realistic, curvilinear geological boundary models and allows for an assessment of the uncertainty in the model. 相似文献
12.
Compositional data are very common in the earth sciences. Nevertheless, little attention has been paid to the spatial interpolation of these data sets. Most interpolators do not necessarily satisfy the constant sum and nonnegativity constraints of compositional data, nor take spatial structure into account. Therefore, compositional kriging is introduced as a straightforward extension of ordinary kriging that complies with these constraints. In two case studies, the performance of compositional kriging is compared with that of the additive logratio-transform. In the first case study, compositional kriging yielded significantly more accurate predictions than the additive logratio-transform, while in the second case study the performances were comparable. 相似文献
13.
Xavier Emery 《Mathematical Geosciences》2008,40(6):671-688
An important aspect in mineral resource evaluation is the reduction of variance when post-processing the grade distributions
defined on the support (volume) of the available data into distributions defined on the support of the proposed selective
mining units. Although the volume-variance relationship is well understood for the estimation of global grade distributions,
it is still an unsolved issue for local estimation studies based on non-parametric geostatistical methods, such as indicator
kriging, for which the support correction is not inherent to the method. To clarify this relationship, the local change of
support problem is examined in the scope of two parametric models (multi-Gaussian and discrete Gaussian models). It is shown
that the variance reduction factor between point and block-support local distributions depends on the block being considered
and is less than the global variance reduction factor. As a consequence, post-processing the local point-support grade distributions
on the basis of the latter systematically understates the importance of the change of support at the local scale and makes
selective mining appear more economically attractive than it really is. In the light of these results, a methodology is proposed
to post-process the local point-support distributions obtained via non-parametric (indicator) methods into block-support distributions.
An application to simulated data indicates that this methodology provides an accurate estimation at the block support when
dealing with diffusion-type random fields. 相似文献
14.
Restricted kriging for mixture of grade models 总被引：2，自引：0，他引：2
A modified type of kriging, referred to as restricted kriging (RK), is proposed in this study. The method incorporates constraints on different grade classes to restrict the influence of the samples having different likelihoods in estimation. RK is motivated by the estimation of mineral reserves when grades have highly skewed distributions. Ordinary kriging tends to produce an overly smoothed interpolated surface by underestimating high grades and overestimating low grades. The fact that ordinary kriging gives a uniform prior treatment to all samples independent of their values is a major factor associated with this smoothing effect. The new approach differentiates each grade portion by preselected cutoffs. RK is developed for a single cutoff and then extended into a general form for any finite number of cutoffs. Restricted cokriging (RCK) is also formulated to simultaneously estimate a set of random functions with restriction conditions. Methods are suggested for determination of the probabilities of occurrence of different grade portions. Finally, the new approach is demonstrated on a case study of an epithermal gold deposit. 相似文献
15.
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 相似文献
16.
P. S. N. Murthy 《Mathematical Geology》1989,21(4):443-461
This paper presents the results of disjunctive kriging applied to a supergene iron ore deposit of Bailadila Range of India. Disjunctive kriging is applied firstly to compare estimates of the blocks by ordinary kriging and secondly to estimate benchwise local recoverable reserves of the orebody. Good agreement exists between block estimates by ordinary kriging and disjunctive kriging except for peripheral blocks with less borehole information. Estimation of benchwise reserves shows that the behavior of the distribution of grades is different in various benches. The study shows that disjunctive kriging can be applied successfully for estimation of local recoverable reserves in the case of a good grade hematite iron ore deposit. 相似文献
17.
Soil contamination by heavy metals and organic pollutants around industrial premises is a problem in many countries around
the world. Delineating zones where pollutants exceed tolerable levels is a necessity for successfully mitigating related health
risks. Predictions of pollutants are usually required for blocks because remediation or regulatory decisions are imposed for
entire parcels. Parcel areas typically exceed the observation support, but are smaller than the survey domain. Mapping soil
pollution therefore involves a local change of support. The goal of this work is to find a simple, robust, and precise method
for predicting block means (linear predictions) and threshold exceedance by block means (nonlinear predictions) from data
observed at points that show a spatial trend. By simulations, we compared the performance of universal block kriging (UK),
Gaussian conditional simulations (CS), constrained (CK), and covariance-matching constrained kriging (CMCK), for linear and
nonlinear local change of support prediction problems. We considered Gaussian and positively skewed spatial processes with
a nonstationary mean function and various scenarios for the autocorrelated error. The linear predictions were assessed by
bias and mean square prediction error and the nonlinear predictions by bias and Peirce skill scores. 相似文献
18.
19.
Ore deposits are usually composed of rock units or facies with different grade distributions and complex spatial structures. Being able to simulate the spatial layout of these facies are essential to have a comprehensive mining plan and an accurate resources and reserves evaluation. Modelers are faced with a set of challenges when creating the facies model such as: reproducing the facies proportions and spatial continuity as well as the topological contacts between facies, capturing post depositional overprinting, and honoring the data obtained from drill holes. Plurigaussian simulation (PGS) is a geostatistical approach that allows covering these challenges. This study addresses the application of PGS to Sungun porphyry copper deposit (Iran), in order to simulate the layout of three facies: mineralized porphyry and skarn and non-mineralized dykes. The aim of this study is to construct numerical models in which the dyke structures reflect the evolution observed in the geology. 相似文献
20.
Ronald Christensen 《Mathematical Geology》1990,22(6):655-664
A proof is provided that the predictions obtained from kriging based on intrinsic random functions of orderk are identical to those obtained from anappropriate universal kriging model. This is a theoretical result based on known variability measures. It does not imply that people performing traditional universal kriging will get the same predictions as those using intrinsic random functions, because traditionally these methods differ in how variability is modeled. For intrinsic random functions, the same proof shows that predictions do not depend on the specific choice of the generalized covariance function. It is argued that the choice between these methods is really one of modeling and estimating the variability in the data. 相似文献