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1.
A test of the ability of a probabilistic neural network to classify deposits into types on the basis of deposit tonnage and average Cu, Mo, Ag, Au, Zn, and Pb grades is conducted. The purpose is to examine whether this type of system might serve as a basis for integrating geoscience information available in large mineral databases to classify sites by deposit type. Benefits of proper classification of many sites in large regions are relatively rapid identification of terranes permissive for deposit types and recognition of specific sites perhaps worthy of exploring further.Total tonnages and average grades of 1,137 well-explored deposits identified in published grade and tonnage models representing 13 deposit types were used to train and test the network. Tonnages were transformed by logarithms and grades by square roots to reduce effects of skewness. All values were scaled by subtracting the variable's mean and dividing by its standard deviation. Half of the deposits were selected randomly to be used in training the probabilistic neural network and the other half were used for independent testing. Tests were performed with a probabilistic neural network employing a Gaussian kernel and separate sigma weights for each class (type) and each variable (grade or tonnage).Deposit types were selected to challenge the neural network. For many types, tonnages or average grades are significantly different from other types, but individual deposits may plot in the grade and tonnage space of more than one type. Porphyry Cu, porphyry Cu-Au, and porphyry Cu-Mo types have similar tonnages and relatively small differences in grades. Redbed Cu deposits typically have tonnages that could be confused with porphyry Cu deposits, also contain Cu and, in some situations, Ag. Cyprus and kuroko massive sulfide types have about the same tonnages. Cu, Zn, Ag, and Au grades. Polymetallic vein, sedimentary exhalative Zn-Pb, and Zn-Pb skarn types contain many of the same metals. Sediment-hosted Au, Comstock Au-Ag, and low-sulfide Au-quartz vein types are principally Au deposits with differing amounts of Ag.Given the intent to test the neural network under the most difficult conditions, an overall 75% agreement between the experts and the neural network is considered excellent. Among the largestclassification errors are skarn Zn-Pb and Cyprus massive sulfide deposits classed by the neuralnetwork as kuroko massive sulfides—24 and 63% error respectively. Other large errors are the classification of 92% of porphyry Cu-Mo as porphyry Cu deposits. Most of the larger classification errors involve 25 or fewer training deposits, suggesting that some errors might be the result of small sample size. About 91% of the gold deposit types were classed properly and 98% of porphyry Cu deposits were classes as some type of porphyry Cu deposit. An experienced economic geologist would not make many of the classification errors that were made by the neural network because the geologic settings of deposits would be used to reduce errors. In a separate test, the probabilistic neural network correctly classed 93% of 336 deposits in eight deposit types when trained with presence or absence of 58 minerals and six generalized rock types. The overall success rate of the probabilistic neural network when trained on tonnage and average grades would probably be more than 90% with additional information on the presence of a few rock types. 相似文献
2.
Application of geostatistics in estimating recoverable reserves of beach sand deposit is rare. This paper made an attempt to estimate local recoverable reserves using disjunctive kriging and discrete Gaussian model considering support and information effects for a beach sand deposit located in the eastern part of India. The dependence of different selective mining unit (SMU) sizes and different production sampling strategies on the estimated tonnage, metal quantity, and the ore tonnage versus metal quantity relationships has been examined. The results of the study show that nonlinear geostatistics should be used for more precise assessment of the grade, ore tonnage, and metal quantity and their relationships, which are necessary for recoverable reserve estimation. In selective mining operation, both support and information effects have significant influence on recoverable reserve. Recoverable reserve estimation based on SMU involves estimating grade distributions of mining unit with much bigger support than the available drill core sample data. Information effect comes into picture from the real scenario where the actual grades of the blocks remain unknown even during mining. At the mining stage, discrimination of ore and waste blocks is carried out based on estimated grades of the production samples and it is likely that the blocks might be misclassified as either ore or waste and thus sent to wrong destination. Information effect modeling makes the estimation more reliable by taking care of misclassification. 相似文献
3.
4.
The Haji-Gak iron deposit of eastern Bamyan Province, eastern Afghanistan, was studied extensively and resource calculations
were made in the 1960s by Afghan and Russian geologists. Recalculation of the resource estimates verifies the original estimates
for categories A (in-place resources known in detail), B (in-place resources known in moderate detail), and C1 (in-place resources estimated on sparse data), totaling 110.8 Mt, or about 6% of the resources as being supportable for the
methods used in the 1960s. C2 (based on a loose exploration grid with little data) resources are based on one ore grade from one drill hole, and P2 (prognosis) resources are based on field observations, field measurements, and an ore grade derived from averaging grades
from three better sampled ore bodies. C2 and P2 resources are 1,659.1 Mt or about 94% of the total resources in the deposit. The vast P2 resources have not been drilled or sampled to confirm their extent or quality. The purpose of this article is to independently
evaluate the resources of the Haji-Gak iron deposit by using the available geologic and mineral resource information including
geologic maps and cross sections, sampling data, and the analog-estimating techniques of the 1960s to determine the size and
tenor of the deposit. 相似文献
5.
D. C. Mason M. O'Conaill I. McKendrick 《International journal of geographical information science》2013,27(5):429-449
Abstract Kriging is an optimal method of spatial interpolation that produces an error for each interpolated value. Block kriging is a form of kriging that computes averaged estimates over blocks (areas or volumes) within the interpolation space. If this space is sampled sparsely, and divided into blocks of a constant size, a variable estimation error is obtained for each block, with blocks near to sample points having smaller errors than blocks farther away. An alternative strategy for sparsely sampled spaces is to vary the sizes of blocks in such away that a block's interpolated value is just sufficiently different from that of an adjacent block given the errors on both blocks. This has the advantage of increasing spatial resolution in many regions, and conversely reducing it in others where maintaining a constant size of block is unjustified (hence achieving data compression). Such a variable subdivision of space can be achieved by regular recursive decomposition using a hierarchical data structure. An implementation of this alternative strategy employing a split-and-merge algorithm operating on a hierarchical data structure is discussed. The technique is illustrated using an oceanographic example involving the interpolation of satellite sea surface temperature data. Consideration is given to the problem of error propagation when combining variable resolution interpolated fields in GIS modelling operations. 相似文献
6.
Incorporating GIS Building Data and Census Housing Statistics for Sub-Block-Level Population Estimation 总被引：1，自引：0，他引：1
This article presents a deterministic model for sub-block-level population estimation based on the total building volumes derived from geographic information system (GIS) building data and three census block-level housing statistics. To assess the model, we generated artificial blocks by aggregating census block areas and calculating the respective housing statistics. We then applied the model to estimate populations for sub-artificial-block areas and assessed the estimates with census populations of the areas. Our analyses indicate that the average percent error of population estimation for sub-artificial-block areas is comparable to those for sub-census-block areas of the same size relative to associated blocks. The smaller the sub-block-level areas, the higher the population estimation errors. For example, the average percent error for residential areas is approximately 0.11 percent for 100 percent block areas and 35 percent for 5 percent block areas. 相似文献
7.
The method of making quantitative assessments of mineral resources sufficiently detailed for economic analysis is outlined in three steps. The steps are (1) determination of types of deposits that may be present in an area, (2) estimation of the numbers of deposits of the permissible deposit types, and (3) combination by Monte Carlo simulation of the estimated numbers of deposits with the historical grades and tonnages of these deposits to produce a probability distribution of the quantities of contained metal.Two examples of the estimation of the number of deposits (step 2) are given. The first example is for mercury deposits in southwestern Alaska and the second is for lode tin deposits in the Seward Peninsula.The flow of the Monte Carlo simulation program is presented with particular attention to the dependencies between grades and tonnages of deposits and between grades of different metals in the same deposit. 相似文献
8.
Vein-hosted gold deposits are characterized by mineralization, which is spatially restricted to narrow vein structures. Drillholes intersecting a mineralized vein can lead to unreliable and biased assay values compared to selective mining unit scale block grades. In this work, a discrete fracture network is simulated and adapted to model gold mineralization within the veins. Veins are assumed planar and the required inputs are distributions of vein orientation, vein length, and vein intensity (i.e., density). These inputs are collected from drillhole data, geological mapping, and expert knowledge of the deposit. A spatial point process is then applied to model gold grade as discrete events or “nuggets,” which are spatially restricted to the simulated quartz veins for the case of incomplete mineralization of the veins; when the vein is completely mineralized, a vein thickness distribution is required. The methodology is applied to an epithermal gold deposit in northwestern British Columbia, Canada and shows improvement in restricting the influence of the high-grade gold samples without resorting to ad-hoc manipulation of input assays through capping or cutting. The final output of this methodology is a block model of gold grade, which better honors the spatial structure of the veins in the deposit and is suitable for use in mine planning or resource estimation. 相似文献
9.
A. John Arnfield 《自然地理学》2013,34(4):361-372
The albedo measurements of Aida (1982), made over simulated urban surfaces constructed from arrangements of concrete blocks into canyon and grid configurations, are used to evaluate the performance of the urban canyon radiation model of Arnfield (1976a, 1982). The model is shown to be capable of producing acceptable estimates of surface albedo for city land-use zones consisting predominantly of canyons with lengths considerably greater than their width, especially for high sun (high irradiance) conditions. For the data best suited to model validation, about half the albedos were estimated to within ±5% and all were within ±10%. For grid canyon configurations, the method yields less satisfactory results but it is argued that errors will be less significant for surface geometries more realistic than those employed by Aida which possessed very short block lengths in relation to street widths. [Key words: urban climate, energy-budget climatology, albedo, radiation model.] 相似文献
10.
The need to integrate large quantities of digital geoscience information to classify locations as mineral deposits or nondeposits has been met by the weights-of-evidence method in many situations. Widespread selection of this method may be more the result of its ease of use and interpretation rather than comparisons with alternative methods. A comparison of the weights-of-evidence method to probabilistic neural networks is performed here with data from Chisel Lake-Andeson Lake, Manitoba, Canada. Each method is designed to estimate the probability of belonging to learned classes where the estimated probabilities are used to classify the unknowns. Using these data, significantly lower classification error rates were observed for the neural network, not only when test and training data were the same (0.02 versus 23%), but also when validation data, not used in any training, were used to test the efficiency of classification (0.7 versus 17%). Despite these data containing too few deposits, these tests of this set of data demonstrate the neural network's ability at making unbiased probability estimates and lower error rates when measured by number of polygons or by the area of land misclassified. For both methods, independent validation tests are required to ensure that estimates are representative of real-world results. Results from the weights-of-evidence method demonstrate a strong bias where most errors are barren areas misclassified as deposits. The weights-of-evidence method is based on Bayes rule, which requires independent variables in order to make unbiased estimates. The chi-square test for independence indicates no significant correlations among the variables in the Chisel Lake–Andeson Lake data. However, the expected number of deposits test clearly demonstrates that these data violate the independence assumption. Other, independent simulations with three variables show that using variables with correlations of 1.0 can double the expected number of deposits as can correlations of –1.0. Studies done in the 1970s on methods that use Bayes rule show that moderate correlations among attributes seriously affect estimates and even small correlations lead to increases in misclassifications. Adverse effects have been observed with small to moderate correlations when only six to eight variables were used. Consistent evidence of upward biased probability estimates from multivariate methods founded on Bayes rule must be of considerable concern to institutions and governmental agencies where unbiased estimates are required. In addition to increasing the misclassification rate, biased probability estimates make classification into deposit and nondeposit classes an arbitrary subjective decision. The probabilistic neural network has no problem dealing with correlated variables—its performance depends strongly on having a thoroughly representative training set. Probabilistic neural networks or logistic regression should receive serious consideration where unbiased estimates are required. The weights-of-evidence method would serve to estimate thresholds between anomalies and background and for exploratory data analysis. 相似文献
11.
Probabilistic Estimates of Number of Undiscovered Deposits and Their Total Tonnages in Permissive Tracts Using Deposit Densities 总被引：2，自引：0，他引：2
Empirical evidence indicates that processes affecting number and quantity of resources in geologic settings are very general
across deposit types. Sizes of permissive tracts that geologically could contain the deposits are excellent predictors of
numbers of deposits. In addition, total ore tonnage of mineral deposits of a particular type in a tract is proportional to
the type’s median tonnage in a tract. Regressions using size of permissive tracts and median tonnage allow estimation of number
of deposits and of total tonnage of mineralization. These powerful estimators, based on 10 different deposit types from 109
permissive worldwide control tracts, generalize across deposit types. Estimates of number of deposits and of total tonnage
of mineral deposits are made by regressing permissive area, and mean (in logs) tons in deposits of the type, against number
of deposits and total tonnage of deposits in the tract for the 50th percentile estimates. The regression equations (R
2 = 0.91 and 0.95) can be used for all deposit types just by inserting logarithmic values of permissive area in square kilometers,
and mean tons in deposits in millions of metric tons. The regression equations provide estimates at the 50th percentile, and
other equations are provided for 90% confidence limits for lower estimates and 10% confidence limits for upper estimates of
number of deposits and total tonnage. Equations for these percentile estimates along with expected value estimates are presented
here along with comparisons with independent expert estimates. Also provided are the equations for correcting for the known
well-explored deposits in a tract. These deposit-density models require internally consistent grade and tonnage models and
delineations for arriving at unbiased estimates. 相似文献
12.
Joseph S. Duval 《Natural Resources Research》2003,12(2):121-126
The U.S. Geological Survey has developed a technique that allows mineral resource experts to apply economic filters to estimates of undiscovered mineral resources. This technique builds on previous work that developed quantitative methods for mineral resource assessments. A Monte-Carlo calculation uses mineral deposit models to estimate commodity grades and tonnages of undiscovered deposits. The results then are analyzed using simple estimates of capital expenditures and daily operating costs for a mine and associated mill. The daily operating costs and the value of the ore are used to calculate the net present value of the deposit, which is compared to the capital expenditures to determine whether the deposit is economic. Repetition of these calculations for many deposits produces a table that can be interpreted in terms of the probability of there being deposits that have anet present value exceeding some specified amount. Sample calculations indicate that applying economic filters to simulated mineral resources might change the perception of the results compared to presenting the calculations in terms of the expected mean gross-in-place value of the minerals. 相似文献
13.
14.
In many cases of model evaluation in physical geography, the observed data to which model predictions are compared may not be error free. This paper addresses the effect of observational errors on the mean squared error, the mean bias error and the mean absolute deviation through the derivation of a statistical framework and Monte Carlo simulation. The effect of bias in the observed values may either decrease or increase the expected values of the mean squared error and mean bias error, depending on whether model and observational biases have the same or opposite signs, respectively. Random errors in observed data tend to inflate the mean squared error and the mean absolute deviation, and also increase the variability of all the error indices considered here. The statistical framework is applied to a real example, in which sampling variability of the observed data appears to account for most of the difference between observed and predicted values. Examination of scaled differences between modelled and observed values, where the differences are divided by the estimated standard errors of the observed values, is suggested as a diagnostic tool for determining whether random observational errors are significant. 相似文献
15.
Mineral resource classification plays an important role in the downstream activities of a mining project. Spatial modeling of the grade variability in a deposit directly impacts the evaluation of recovery functions, such as the tonnage, metal quantity and mean grade above cutoffs. The use of geostatistical simulations for this purpose is becoming popular among practitioners because they produce statistical parameters of the sample dataset in cases of global distribution (e.g., histograms) and local distribution (e.g., variograms). Conditional simulations can also be assessed to quantify the uncertainty within the blocks. In this sense, mineral resource classification based on obtained realizations leads to the likely computation of reliable recovery functions, showing the worst and best scenarios. However, applying the proper geostatistical (co)-simulation algorithms is critical in the case of modeling variables with strong cross-correlation structures. In this context, enhanced approaches such as projection pursuit multivariate transforms (PPMTs) are highly desirable. In this paper, the mineral resources in an iron ore deposit are computed and categorized employing the PPMT method, and then, the outputs are compared with conventional (co)-simulation methods for the reproduction of statistical parameters and for the calculation of tonnage at different levels of cutoff grades. The results show that the PPMT outperforms conventional (co)-simulation approaches not only in terms of local and global cross-correlation reproductions between two underlying grades (Fe and Al2O3) in this iron deposit but also in terms of mineral resource categories according to the Joint Ore Reserves Committee standard.
相似文献16.
Mineral resource evaluation requires defining grade domains of an ore deposit. Common practice in mineral resource estimation
consists of partitioning the ore body into several grade domains before the geostatistical modeling and estimation at unsampled
locations. Many ore deposits are made up of different mineralogical ensembles such as oxide and sulfide zone: being able to
model the spatial layout of the different grades is vital to good mine planning and management. This study addresses the application
of the plurigaussian simulation to Sivas (Turkey) gold deposits for constructing grade domain models that reproduce the contacts
between different grade domains in accordance with geologist’s interpretation. The method is based on the relationship between
indicator variables from grade distributions on the Gaussian random functions chosen to represent them. Geological knowledge
is incorporated into the model by the definition of the indicator variables, their truncation strategy, and the grade domain
proportions. The advantages of the plurigaussian simulation are exhibited through the case study. The results indicated that
the processes are seen to respect reproducing complex geometrical grades of an ore deposit by means of simulating several
grade domains with different spatial structure and taking into account their global proportions. The proposed proportion model
proves as simple to use in resource estimation, to account for spatial variations of the grade characteristics and their distribution
across the studied area, and for the uncertainty in the grade domain proportions. The simulated models can also be incorporated
into mine planning and scheduling. 相似文献
17.
Dennis P. Cox 《Natural Resources Research》1993,2(2):82-91
Quantitative mineral resource assessments used by the United States Geological Survey are based on deposit models. These assessments consist of three parts: (1) selecting appropriate deposit models and delineating on maps areas permissive for each type of deposit; (2) constructing a grade-tonnage model for each deposit model; and (3) estimating the number of undiscovered deposits of each type. In this article, I focus on the estimation of undiscovered deposits using two methods: the deposit density method and the target counting method.In the deposit density method, estimates are made by analogy with well-explored areas that are geologically similar to the study area and that contain a known density of deposits per unit area. The deposit density method is useful for regions where there is little or no data. This method was used to estimate undiscovered low-sulfide gold-quartz vein deposits in Venezuela.Estimates can also be made by counting targets such as mineral occurrences, geophysical or geochemical anomalies, or exploration plays and by assigning to each target a probability that it represents an undiscovered deposit that is a member of the grade-tonnage distribution. This method is useful in areas where detailed geological, geophysical, geochemical, and mineral occurrence data exist. Using this method, porphyry copper-gold deposits were estimated in Puerto Rico. 相似文献
18.
de Souza Luis Eduardo Costa João Felipe C. L. Koppe Jair C. 《Natural Resources Research》2004,13(1):1-15
For many decades the mining industry regarded resources/reserves estimation and classification as a mere calculation requiring basic mathematical and geological knowledge. Most methods were based on geometrical procedures and spatial data distribution. Therefore, uncertainty associated with tonnages and grades either were ignored or mishandled, although various mining codes require a measure of confidence in the values reported. Traditional methods fail in reporting the level of confidence in the quantities and grades. Conversely, kriging is known to provide the best estimate and its associated variance. Among kriging methods, Ordinary Kriging (OK) probably is the most widely used one for mineral resource/reserve estimation, mainly because of its robustness and its facility in uncertainty assessment by using the kriging variance. It also is known that OK variance is unable to recognize local data variability, an important issue when heterogeneous mineral deposits with higher and poorer grade zones are being evaluated. Altenatively, stochastic simulation are used to build local or global uncertainty about a geological attribute respecting its statistical moments. This study investigates methods capable of incorporating uncertainty to the estimates of resources and reserves via OK and sequential gaussian and sequential indicator simulation The results showed that for the type of mineralization studied all methods classified the tonnages similarly. The methods are illustrated using an exploration drill hole data sets from a large Brazilian coal deposit. 相似文献
19.
Estimates of the number of undiscovered deposits on a statewide basis offer a different perspective on the nation's undiscovered resources of gold, silver, copper, lead, and zinc. Mean estimates of the number of undiscovered deposits statewide were extracted from the estimates of undiscovered deposits nationwide. More than 50 undiscovered deposits are estimated to occur in Alaska, Arizona, Nevada, and Wisconsin. Estimating the number of undiscovered deposits statewide serves as a measure of a state's total remaining mineral resources in known conventional deposit types. 相似文献
20.
Oktay Erten Mehmet Siddik Kizil Erkan Topal Lachlan McAndrew 《Natural Resources Research》2013,22(3):207-227
Tropical laterite-type bauxite deposits often pose a unique challenge for resource modelling and mine planning due to the extreme lateral variability at the base of the bauxite ore unit within the regolith profile. An economically viable drilling grid is often rather sparse for traditional prediction techniques to precisely account for the lateral variability in the lower contact of a bauxite ore unit. However, ground-penetrating radar (GPR) offers an inexpensive and rapid method for delineating laterite profiles by acquiring fine-scale data from the ground. These numerous data (secondary variable) can be merged with sparsely spaced borehole data (primary variable) through various statistical and geostatistical techniques, provided that there is a linear relation between the primary and secondary variables. Four prediction techniques, including standard linear regression, simple kriging with varying local means, co-located cokriging and kriging with an external drift, were used in this study to incorporate exhaustive GPR data in predictive estimation the base of a bauxite ore unit within a lateritic bauxite deposit in Australia. Cross-validation was used to assess the performance of each technique. The most robust estimates are produced using ordinary co-located cokriging in accordance with the cross-validation analysis. Comparison of the estimates against the actual mine floor indicates that the inclusion of ancillary GPR data substantially improves the quality of the estimates representing the bauxite base surface. 相似文献