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1.
In order to determine whether it is desirable to quantify mineral-deposit models further, a test of the ability of a probabilistic
neural network to classify deposits into types based on mineralogy was conducted. Presence or absence of ore and alteration
mineralogy in well-typed deposits were used to train the network. To reduce the number of minerals considered, the analyzed
data were restricted to minerals present in at least 20% of at least one deposit type. An advantage of this restriction is
that single or rare occurrences of minerals did not dominate the results. Probabilistic neural networks can provide mathematically
sound confidence measures based on Bayes theorem and are relatively insensitive to outliers. Founded on Parzen density estimation,
they require no assumptions about distributions of random variables used for classification, even handling multimodal distributions.
They train quickly and work as well as, or better than, multiple-layer feedforward networks. Tests were performed with a probabilistic
neural network employing a Gaussian kernel and separate sigma weights for each class and each variable. The training set was
reduced to the presence or absence of 58 reported minerals in eight deposit types. The training set included: 49 Cyprus massive
sulfide deposits; 200 kuroko massive sulfide deposits; 59 Comstock epithermal vein gold districts; 17 quartzalunite epithermal
gold deposits; 25 Creede epithermal gold deposits; 28 sedimentary-exhalative zinc-lead deposits; 28 Sado epithermal vein gold
deposits; and 100 porphyry copper deposits. The most common training problem was the error of classifying about 27% of Cyprus-type
deposits in the training set as kuroko. In independent tests with deposits not used in the training set, 88% of 224 kuroko
massive sulfide deposits were classed correctly, 92% of 25 porphyry copper deposits, 78% of 9 Comstock epithermal gold-silver
districts, and 83% of six quartzalunite epithermal gold deposits were classed correctly. Across all deposit types, 88% of
deposits in the validation dataset were correctly classed. Misclassifications were most common if a deposit was characterized
by only a few minerals, e.g., pyrite, chalcopyrite,and sphalerite. The success rate jumped to 98% correctly classed deposits
when just two rock types were added. Such a high success rate of the probabilistic neural network suggests that not only should
this preliminary test be expanded to include other deposit types, but that other deposit features should be added 相似文献
2.
The enrichment ratio (ER), defined as the ratio of grade of a metal element in a deposit to the crustal abundance of the metal, is proposed for assessing mineral resources. According to the definition, the enrichment ratio of a polymetallic deposit is given as a sum of enrichment ratios of all metals. The relation between ER and the cumulative tonnage integrated from the high ER side of about 4750 deposits in the world is approximated by the combination of three exponential functions crossing at ER values of 16 · 103 and 600. High ER deposits are expected for the commodities Ag, Pb, and Au+Ag, and for epithermal, mesothermal, unconformity-related and vein types. In contrast, low ER deposits are typical for the commodities Cu, Mn, Mo, Ni, and U, and for chemically precipitated, Cyprus, laterite, orthomagmatic, pegmatite, placer, porphyry, and sandstone deposits. The critical ER value of the low ER class (the differential metal amount decreases with decreasing ER in the regions lower than the value) is 250 in all deposits, 610 in W+Mo, 2800 in Pb+Zn and 360 in Au+Ag, 530 in massive sulfides, 160 in the orthomagmatic type, 170 in placers, 220 in the porphyry type, 1900 in the replacement type, 580 in the stratabound type, 3400 in the unconformity-related type, and 1700 in vein type deposits. The frequency proportion determined by a keyword and a commodity provides valuable suggestions for mineral exploration: for example, the exploration target for chromite is a deposit characterized as orthomagmatic, whereas the expected commodity of a newly developed orthomagmatic deposit is chromite. 相似文献
3.
Gary L. Raines 《Natural Resources Research》2008,17(2):87-97
It has been proposed that the spatial distribution of mineral deposits is bifractal. An implication of this property is that
the number of deposits in a permissive area is a function of the shape of the area. This is because the fractal density functions
of deposits are dependent on the distance from known deposits. A long thin permissive area with most of the deposits in one
end, such as the Alaskan porphyry permissive area, has a major portion of the area far from known deposits and consequently
a low density of deposits associated with most of the permissive area. On the other hand, a more equi-dimensioned permissive
area, such as the Arizona porphyry permissive area, has a more uniform density of deposits. Another implication of the fractal
distribution is that the Poisson assumption typically used for estimating deposit numbers is invalid. Based on datasets of
mineral deposits classified by type as inputs, the distributions of many different deposit types are found to have characteristically
two fractal dimensions over separate non-overlapping spatial scales in the range of 5–1000 km. In particular, one typically
observes a local dimension at spatial scales less than 30–60 km, and a regional dimension at larger spatial scales. The deposit
type, geologic setting, and sample size influence the fractal dimensions. The consequence of the geologic setting can be diminished
by using deposits classified by type. The crossover point between the two fractal domains is proportional to the median size
of the deposit type. A plot of the crossover points for porphyry copper deposits from different geologic domains against median
deposit sizes defines linear relationships and identifies regions that are significantly underexplored. Plots of the fractal
dimension can also be used to define density functions from which the number of undiscovered deposits can be estimated. This
density function is only dependent on the distribution of deposits and is independent of the definition of the permissive
area. Density functions for porphyry copper deposits appear to be significantly different for regions in the Andes, Mexico,
United States, and western Canada. Consequently, depending on which regional density function is used, quite different estimates
of numbers of undiscovered deposits can be obtained. These fractal properties suggest that geologic studies based on mapping
at scales of 1:24,000 to 1:100,000 may not recognize processes that are important in the formation of mineral deposits at
scales larger than the crossover points at 30–60 km. 相似文献
4.
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
5.
Estimates of numbers of undiscovered mineral deposits, fundamental to assessing mineral resources, are affected by map scale.
Where consistently defined deposits of a particular type are estimated, spatial and frequency distributions of deposits are
linked in that some frequency distributions can be generated by processes randomly in space whereas others are generated by
processes suggesting clustering in space. Possible spatial distributions of mineral deposits and their related frequency distributions
are affected by map scale and associated inclusions of non-permissive or covered geological settings. More generalized map
scales are more likely to cause inclusion of geologic settings that are not really permissive for the deposit type, or that
include unreported cover over permissive areas, resulting in the appearance of deposit clustering. Thus, overly generalized
map scales can cause deposits to appear clustered. We propose a model that captures the effects of map scale and the related
inclusion of non-permissive geologic settings on numbers of deposits estimates, the zero-inflated Poisson distribution. Effects
of map scale as represented by the zero-inflated Poisson distribution suggest that the appearance of deposit clustering should
diminish as mapping becomes more detailed because the number of inflated zeros would decrease with more detailed maps. Based
on observed worldwide relationships between map scale and areas permissive for deposit types, mapping at a scale with twice
the detail should cut permissive area size of a porphyry copper tract to 29% and a volcanic-hosted massive sulfide tract to
50% of their original sizes. Thus some direct benefits of mapping an area at a more detailed scale are indicated by significant
reductions in areas permissive for deposit types, increased deposit density and, as a consequence, reduced uncertainty in
the estimate of number of undiscovered deposits. Exploration enterprises benefit from reduced areas requiring detailed and
expensive exploration, and land-use planners benefit from reduced areas of concern. 相似文献
6.
7.
Quantitative Analysis of Mineral Resources for Strategic Planning: Implications for Australian Geological Surveys 总被引：5，自引：0，他引：5
A quantitative valuation study has been made of Australian state surveys with the specific goals of (1) establishing the 'worth' of current programs upgrading state government geoscientific information infrastructure, and (2) considering the results of the valuation in terms of strategic planning. The study has been done from the perspective of the community as a whole and has been undertaken in two phases reflecting the different objectives of Australian state surveys in terms of the exploration industry and government policy-making. This paper reports on the second part of this valuation process, measuring the impact of upgraded survey data on government mineral policy decision processes. The valuation methodology developed is a comparative approach used to determine net benefit foregone by not upgrading information infrastructure. The underlying premise for the geological survey study is that existing and upgraded data sets will have a different probability that a deposit will be detected. The approach used in the valuation of geoscientific data introduces a significant technical component with the requirement to model both favorability of mineral occurrence and probability of deposit occurrence for two different generations of government data. The estimation of mineral potential uses modern quantitative methods, including the U.S. Geological Survey three-part resource-assessment process and computer-based prospectivity modeling. To test the methodology mineral potential was assessed for porphyry copper type deposits in part of the Yarrol Province, central Queensland. Results of the Yarrol case study supports the strategy of the state surveys to facilitate effective exploration by improving accuracy and acquiring new data, as part of resource management. It was determined in the Yarrol Province case study that in going from existing to upgraded data sets the area that would be considered permissible for the occurrence of porphyry type deposits almost doubled. The implication of this result is that large tracts of potentially mineralized land would not be identified using existing data. Results of the prospectivity modeling showed a marked increase in the number of exploration targets and in target rankings using the upgraded data set. A significant reduction in discovery risk also is associated with the upgraded data set, a conclusion supported by the fact that known mines with surface exposure are not identified in prospectivity modeling using the existing data sets. These results highlight the absence in the existing data sets of information critical for the identification of prospective ground.Quantitative resource assessment and computer-based prospectivity modeling are seen as complementary processes that provide the support for the increasingly sophisticated needs of Australian survey clients. Significant additional gains to the current value of geoscientific data can be achieved through the in-house analysis and characterization of individual data sets, the integration and interpretation of data sets, and the incorporation of information on geological uncertainty. 相似文献
8.
Evaluation of Weights of Evidence to Predict Epithermal-Gold Deposits in the Great Basin of the Western United States 总被引：7，自引：0，他引：7
The weights-of-evidence method provides a simple approach to the integration of diverse geologic information. The application addressed is to construct a model that predicts the locations of epithermal-gold mineral deposits in the Great Basin of the western United States. Weights of evidence is a data-driven method requiring known deposits and occurrences that are used as training sites in the evaluated area. Four hundred and fifteen known hot spring gold–silver, Comstock vein, hot spring mercury, epithermal manganese, and volcanogenic uranium deposits and occurrences in Nevada were used to define an area of 327.4 km2 as training sites to develop the model. The model consists of nine weighted-map patterns that are combined to produce a favorability map predicting the distribution of epithermal-gold deposits. Using a measure of the association of training sites with predictor features (or patterns), the patterns can be ranked from best to worst predictors. Based on proximity analysis, the strongest predictor is the area within 8 km of volcanic rocks younger than 43 Ma. Being close to volcanic rocks is not highly weighted, but being far from volcanic rocks causes a strong negative weight. These weights suggest that proximity to volcanic rocks define where deposits do not occur. The second best pattern is the area within 1 km of hydrothermally altered areas. The next best pattern is the area within 1 km of known placer-gold sites. The proximity analysis for gold placers weights this pattern as useful when close to known placer sites, but unimportant where placers do not exist. The remaining patterns are significantly weaker predictors. In order of decreasing correlation, they are: proximity to volcanic vents, proximity to east-west to northwest faults, elevated airborne radiometric uranium, proximity to northwest to west and north-northwest linear features, elevated aeromagnetics, and anomalous geochemistry. This ordering of the patterns is a function of the quality, applicability, and use of the data. The nine-pattern favorability map can be evaluated by comparison with the USGS National Assessment for hot spring gold–silver deposits. The Spearman's ranked correlation coefficient between the favorability and the National Assessment permissive tracts is 0.5. Tabulations of the areas of agreement and disagreement between the two maps show 74% agreement for the Great Basin. The posterior probabilities for 51 significant deposits in the Great Basin, both used and not used in the model, show the following: 26 classified as favorable; 25 classified as permissive; and 1, Florida Canyon, classified as nonpermissive.The Florida Canyon deposit has a low favorability because there are no volcanic rocks near the deposit on the Nevada geologic map used. The largest areas of disagreement are caused by the USGS National Assessment team concluding that volcanic rocks older than 27 Ma in Nevada are not permissive, which was not assumed in this model. The weights-of-evidence model is evaluated as reasonable and delineates permissive areas for epithermal deposits comparable to expert's delineation. The weights-of-evidence model has the additional characteristics that it is well defined, reproducible, objective, and provides a quantitative measure of confidence. 相似文献
9.
V.F. Rodriguez-Galiano M. Chica-Olmo M. Chica-Rivas 《International journal of geographical information science》2014,28(7):1336-1354
Mineral exploration activities require robust predictive models that result in accurate mapping of the probability that mineral deposits can be found at a certain location. Random forest (RF) is a powerful machine data-driven predictive method that is unknown in mineral potential mapping. In this paper, performance of RF regression for the likelihood of gold deposits in the Rodalquilar mining district is explored. The RF model was developed using a comprehensive exploration GIS database composed of: gravimetric and magnetic survey, a lithogeochemical survey of 59 elements, lithology and fracture maps, a Landsat 5 Thematic Mapper image and gold occurrence locations. The results of this study indicate that the use of RF for the integration of large multisource data sets used in mineral exploration and for prediction of mineral deposit occurrences offers several advantages over existing methods. Key advantages of RF include: (1) the simplicity of parameter setting; (2) an internal unbiased estimate of the prediction error; (3) the ability to handle complex data of different statistical distributions, responding to nonlinear relationships between variables; (4) the capability to use categorical predictors; and (5) the capability to determine variable importance. Additionally, variables that RF identified as most important coincide with well-known geologic expectations. To validate and assess the effectiveness of the RF method, gold prospectivity maps are also prepared using the logistic regression (LR) method. Statistical measures of map quality indicate that the RF method performs better than LR, with mean square errors equal to 0.12 and 0.19, respectively. The efficiency of RF is also better, achieving an optimum success rate when half of the area predicted by LR is considered. 相似文献
10.
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
11.
The quantitative probabilistic assessment of the undiscovered mineral resources of the 17.1-million-acre Tongass National Forest (the largest in the United States) and its adjacent lands is a nonaggregated, mineral-resource-tract-oriented assessment designed for land-planning purposes. As such, it includes the renewed use of gross-in-place values (GIPV's) in dollars of the estimated amounts of metal contained in the undiscovered resources as a measure for land-use planning.Southeastern Alaska is geologically complex and contains a wide variety of known mineral deposits, some of which have produced important amounts of metals during the past 100 years. Regional geological, economic geological, geochemical, geophysical, and mineral exploration history information for the region was integrated to define 124 tracts likely to contain undiscovered mineral resources. Some tracts were judged to contain more than one type of mineral deposit. Each type of deposit may contain one or more metallic elements of economic interest. For tracts where information was sufficient, the minimum number of as-yet-undiscovered deposits of each type was estimated at probability levels of 0.95, 0.90, 0.50, 0.10, and 0.05.The undiscovered mineral resources of the individual tracts were estimated using the U.S. Geological Survey's MARK3 mineral-resource endowment simulator; those estimates were used to calculate GIPV's for the individual tracts. Those GIPV's were aggregated to estimate the value of the undiscovered mineral resources of southeastern Alaska. The aggregated GIPV of the estimates is $40.9 billion.Analysis of this study indicates that (1) there is only a crude positive correlation between the size of individual tracts and their mean GIPV's: and (2) the number of mineral-deposit types in a tract does not dominate the GIPV's of the tracts, but the inferred presence of synorogenic-synvolcanic nickel-copper, porphyry copper skarn-related, iron skarn, and porphyry copper-molybdenum deposits does. The influence of this study on the U.S. Forest Service planning process is yet to be determined. 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.
Ore value-tonnage diagrams for resource assessment 总被引：4，自引：0，他引：4
An ore value-tonnage diagram has been proposed for assessing mineral resources. Diagrams of W+Mo, and Pb+Zn deposits show
a good linearity between ore value and logarithms of cumulative ore tonnage. Diagrams of the massive sulfide, orthomagmatic,
placer, porphyry, replacement, and stratabound types are also linear. It is assumed, therefore, that deposits of each of these
commodities and these types belong to a single population. In contrast, the ore value-tonnage relations of all the deposits
analyzed here is approximated by the combination of two exponential functions. The same feature is seen for deposits of the
Cu+W+Mo, Cu+Pb+Zn, and Au+Ag commodities, and of the vein and unconformity-related types. This suggests that deposits belonging
to each of such categories are divided into the high and low value groups. We can expect, accordingly, to find high value
deposits of such categories. 相似文献
14.
Victor F. Hollister 《Natural Resources Research》1992,1(4):293-302
A plutonic porphyry gold deposit model is proposed that is imilar to the plutonic porphyry copper deposit model. However, unlike the plutonic porphyry copper deposit model, the proposed model is deficient in copper and contains less than 1 percent total sulfides. In the proposed model, gold is accompanied by scheelite, molybdenite, arsenopyrite, a variety of bismuth sulfides, tellurides, and native bismuth. The host rock varies from granite to granodiorite stock. Most of the ore is in the pluton. Deposits cited as examples of the proposed model are the Mokrsko deposit in Czechoslovakia, the Fort Knox deposit in the United States, and the Dublin Gulch deposit in Canada. In each of these deposits, pervasive potassic or phyllic alteration zones accompany the gold ore, which is disseminated in quartz-rich stockworks, veinlet swarms, and veins. Tonnages of gold-bearing material are large, but grades are low in the cited deposits. The proposed model is distinct from other gold deposit models because of the low Cu to Au ratio and the association of Au, Bi, W, and Mo. 相似文献
15.
Sidnei Pires Rostirolla Paulo César Soares Hung Kiang Chang 《Natural Resources Research》1998,7(1):7-24
A methology to define favorable areas in petroleum and mineral exploration is applied, which consists in weighting the exploratory variables, in order to characterize their importance as exploration guides. The exploration data are spatially integrated in the selected area to establish the association between variables and deposits, and the relationships among distribution, topology, and indicator pattern of all variables. Two methods of statistical analysis were compared. The first one is the Weights of Evidence Modeling, a conditional probability approach (Agterberg, 1989a), and the second one is the Principal Components Analysis (Pan, 1993). In the conditional method, the favorability estimation is based on the probability of deposit and variable joint occurrence, with the weights being defined as natural logarithms of likelihood ratios. In the multivariate analysis, the cells which contain deposits are selected as control cells and the weights are determined by eigendecomposition, being represented by the coefficients of the eigenvector related to the system’s largest eigenvalue. The two techniques of weighting and complementary procedures were tested on two case studies: 1. Recôncavo Basin, Northeast Brazil (for Petroleum) and 2. Itaiacoca Formation of Ribeira Belt, Southeast Brazil (for Pb-Zn Mississippi Valley Type deposits). The applied methdology proved to be easy to use and of great assistance to predict the favorability in large areas, particularly in the initial phase of exploration programs. 相似文献
16.
陡坡钼矿床是一新发现的中型钼矿床,该矿床赋存于早白垩世灵山超单元岩体与围岩的接触带内侧,矿化类型主要为细脉浸染状。矿床中金属矿物主要为黄铜矿、辉钼矿、方铅矿、闪锌矿、黄铁矿、磁铁矿、赤铁矿,次为磁黄铁矿、斑铜矿等。灵山超单元花岗岩岩石类型属高硅富碱钙碱性(偏碱性)系列,SiO2含量72～77%,K2O+Na2O总量大于7.9%,K2O/Na2O大于1。矿床的围岩蚀变叠加组合主要为硅化——钾长石化——黄铁矿化组合、硅化——绿泥石化——黄铁矿化组合。该矿床属中高温热液斑岩型钼矿床,结合岩浆岩特征,成矿作用于与岩体关系密切,并可能受幔源岩浆混合作用的影响。 相似文献
17.
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
18.
Recognition of effective factors that influence the spatial extension of supergene weathering zones is important both for the identification of high potential areas of exotic deposits and for the cost-effective planning of mining. In particular, recognition of exotic mineralization around porphyry copper deposits early in mine development prevents them from being buried beneath mine infrastructures such as waste dump and tailing structures. Mass-balance modeling, a practical method for determining high potential areas of undiscovered exotic mineralization, investigates important factors in forming exotic deposits. Mass-balance modeling is a two-phase methodology that becomes progressively more detailed. An initial result, presented here as phase 1, is based solely on Cu assays. Phase 2 incorporates relict sulfide mineral studies to improve phase 1 modeling results and computes actual fluxes of copper that escaped vertically downward from the leached cap to form the enrichment blanket and then flowed laterally away to form exotic mineralization. In addition, geostatistical approaches, especially sequential Gaussian simulation, are useful tools for investigating the spatial relationships and modeling of mass-balance results in phase 1 studies. This paper introduces a method for interpolation and downscaling of the preliminary mass-balance analysis (phase 1) to highlight the role of geological features in the evolution of the supergene process. Using only copper assays without any need for relict sulfide mineralogy, this approach can be used to approximately identify the geographic direction of metal movement in exotic copper deposits, and thus serve as an initial exploration guide in prospecting for exotic deposits. For this, a vertical columnar block model was constructed for each of the supergene weathering zones and preliminary analysis of mass balance was conducted to reconstruct the apparent total leached zone column height assuming zero lateral flux. This analysis was applied to each of the vertical block model columns. The results of mass balance were interpolated in a 5?×?5 m grid by sequential Gaussian simulation method, and the simulated surface of the total leached zone was conflated with geological features. The roles of topography, argillic alteration and linear structures were identified in the transport of supergene solutions in the Miduk porphyry copper deposit of Iran. In the northern section of the deposit, which is in accordance with the topography gradient and the presence of advanced argillic alteration zone, the computed top total of leaching is below the actual surface topography, whereas the hypogene isograd curves confirm the expansion of primary copper in these areas. The northern section of the deposit was introduced as a susceptible area for the removal of copper-bearing solutions from the supergene enrichment system.
相似文献19.
Where Are Porphyry Copper Deposits Spatially Localized? A Case Study in Benguet Province,Philippines 总被引：10，自引：0，他引：10
To provide guides for exploration of porphyry copper mineralization at a district scale, we examine the spatial association between known porphyry copper deposits and geologic features in Benguet, Philippines. The spatial associations between the porphyry copper deposits and strike-slip fault discontinuities, batholithic pluton margins and porphyry plutons are quantified using weights of evidence modeling. In the training and testing district, the porphyry copper occurrences are associated spatially with strike-slip fault discontinuities, batholithic pluton margins and contacts of porphyry plutons within distances of 3 km, 2.25 km, and 1 km, respectively. In addition, the porphyry plutons are associated spatially with strike-slip fault discontinuities and contacts of batholithic plutons within a distance of 2.25 km and 3 km, respectively. Based on these significant spatial associations, predictive maps are generated to delineate zones favorable for porphyry copper mineralization and zones favorable for emplacement of porphyry plutons in Benguet province, Philippines. Validations of the predictive models demonstrate their efficacy in pointing to zones for subsequent follow-up exploration work. 相似文献
20.
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