Logistic-Based Translation of Orogenic Gold Forming Processes into Mappable Exploration Criteria for Fuzzy Logic Mineral Exploration Targeting in the Kushaka Schist Belt,North-Central Nigeria

This paper applied a logistic-based fuzzy logic inference system to integrate critical factors that could control orogenic gold mineralization in part of the Kushaka schist belt, north-central Nigeria to develop a process-based mineral potential mapping (MPM) of the area. The critical factors from geophysical and geological dataset were weighted using logistic functions. The fuzzy logic inference system provides the capability to handle complex geological processes that culminated in orogenic gold mineralization as well as minimizing systemic uncertainties/fuzziness that often plague MPM. The results of this work show that granitic intrusions with fuzzy scores of 0.67–0.90 played a major role in generating high geothermal gradient in the area. Seventy percent of the existing gold mine sites in the area spatially coincide with metasedimentary rocks, having fuzzy scores of 0.7–0.9; this suggests metasedimentary rocks as being responsible for the production of gold fluid and ligands in the area. The evidence of hydrothermal activity, with fuzzy scores of 0.53 and 0.91, confirms the occurrence of mineralization associated with quartz veins and granite rocks. Lithological contacts and faults, having fuzzy scores of 0.60–0.80, presumably contribute to the localization of orogenic gold mineralization in the area. Emerging from the results, favorable zones for primary orogenic gold mineralization in the area occurred predominantly on granite gneiss and quartz veins. The mineral potential map was found consistent with the local geology, structural styles and hydrothermal alteration signatures in the area, and its validation using the existing locations of geochemical anomalies and prediction–area rate curve in the study area showed 75 and 72% agreement, respectively, thus confirming the reliability of the developed mineral potential map for resource management.

     

Fractal structure of the time distribution of microfracturing in rocks

Using acoustic emission data obtained from laboratory double torsion tests, we have analysed the fractal nature of a series of 29 granite microfracturing processes in time. The data represent a wide variety of timescales, stress environments (increasing load with a constant displacement rate, relaxation, creep), soaking conditions [air, water, dodecyl trimethyl ammonium bromide (DTAB), polyethelene oxide (PEO) ], and material anisotropy. We find that the time distribution of rock microfracturing displays fractal and multifractal properties. In some cases, it has a single fractal or a multifractal structure. In other cases, it changes from a single fractal structure into a multifractal structure as the system evolves dynamically. We suggest that the heterogeneity of the rock, the distribution of joints or weak planes, the stress level, and the nature of the microfracturing mechanism lead to these multifractal properties. Whatever the fractal structure of the system, a lower fractal dimension is generally produced at near-failure of the rock due to an increased clustering. This result concerning the fractal-dimension decrease is consistent with the conclusion drawn from the spatial distribution of rock microfracturing. Therefore, from the vantage point of observation of the time distribution of rock microfracturing, the decrease of the fractal dimension has a potential use as a rock failure predictor.     

Application of Discriminant Analysis and Support Vector Machine in Mapping Gold Potential Areas for Further Drilling in the Sari-Gunay Gold Deposit,NW Iran

In this contribution, we used discriminant analysis (DA) and support vector machine (SVM) to model subsurface gold mineralization by using a combination of the surface soil geochemical anomalies and earlier bore data for further drilling at the Sari-Gunay gold deposit, NW Iran. Seventy percent of the data were used as the training data and the remaining 30 % were used as the testing data. Sum of the block grades, obtained by kriging, above the cutoff grade (0.5 g/t) was multiplied by the thickness of the blocks and used as productivity index (PI). Then, the PI variable was classified into three classes of background, medium, and high by using fractal method. Four classification functions of SVM and DA methods were calculated by the training soil geochemical data. Also, by using all the geochemical data and classification functions, the general extension of the gold mineralized zones was predicted. The mineral prediction models at the Sari-Gunay hill were used to locate high and moderate potential areas for further infill systematic and reconnaissance drilling, respectively. These models at Agh-Dagh hill and the area between Sari-Gunay and Agh-Dagh hills were used to define the moderate and high potential areas for further reconnaissance drilling. The results showed that the nu-SVM method with 73.8 % accuracy and c-SVM with 72.3 % accuracy worked better than DA methods.     

Mineral Potential Modelling for the Greater Nahanni Ecosystem Using GIS Based Analytical Methods

Mineral potential within the Greater Nahanni Ecosystem (GNE) was modelled in a Geographic Information System (GIS) for four different deposit types: (1) SEDEX (stratiform shale-hosted sedimentary exhalative Zn–Pb–Ag), (2) ‘Carbonate-Fault’ (carbonate-hosted zinc–lead–silver associated with major faults), (3) ‘Intrusion-Related’ (includes skarn, rare metals and gemstones) and (4) Carlin-Type gold as lode and/or derived placer deposits. This mineral potential modelling study integrates data collected during the Nahanni Mineral and Energy Resource Assessment (MERA) undertaken from 2003 to 2007. The results have contributed to the process of determining the geographic boundaries of the proposed expansion of the Nahanni National Park Reserve. Four mineral potential maps were produced (one for each deposit type) using a knowledge-driven approach. A weighting scheme based on integrated mineral deposit and regional geological knowledge was derived for the various evidence maps for each deposit model using expert opinion. The four potential maps were then combined into a final potential map using a maximum operator. Plots showing the efficiency of the models (mineral potential maps) for predicting the known occurrences of the four deposit types show that partial data sets provide reasonable predictions of the remaining known mineral prospects, occurrences and deposits. Hydrocarbon potential from Nahanni MERA 1 was added to the final potential map to ensure that both mineral and energy potential data were incorporated into the park configuration modelling.     

Multifractal analysis of spatial distribution of microearthquakes in the Kanto region

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The spatial distribution of earthquakes is a fractal, which is characterized by a fractal dimension. However, if a spatial distribution has a heterogeneous fractal structure, a single value of fractal dimension [e.g. D_o (capacity dimension) or D ₂ (correlation dimension)] is not enough to characterize it. From a multifractal viewpoint, we analysed the spatial distribution of microearthquakes in the Kanto region by using a local density function. Generalized dimensions, D_q , of the spatial distribution were calculated from the slopes of generalized correlation integrals, C_q(r) versus distance r , on a log-log plot, examining the self-similarity of the spatial distribution of microearthquakes. Self-similar structures are held well at scales from 1.26 to 12.6 km. Our results suggest that the spatial distribution of microearthquakes in the Kanto region is not a homogeneous fractal structure but a heterogeneous one with generalized dimensions D₂ = 2.2 ≤ D ₃≤…≤ D _∞= 1.7. The value of D _∞, the lower limit of fractal dimension, is the fractal dimension of the most intensive clustering in the heterogeneous fractal set. The fractal dimension of the most intensive clustering of microearthquakes in the Kanto region is 1.7.     

Geologically Constrained Fuzzy Mapping of Gold Mineralization Potential,Baguio District,Philippines

An application of the theory of fuzzy sets to the mapping of gold mineralization potential in the Baguio gold mining district of the Philippines is described. Proximity to geological features is translated into fuzzy membership functions based upon qualitative and quantitative knowledge of spatial associations between known gold occurrences and geological features in the area. Fuzzy sets of favorable distances to geological features and favorable lithologic formations are combined using fuzzy logic as the inference engine. The data capture, map operations, and spatial data analyses are carried out using a geographic information system. The fuzzy predictive maps delineate at least 68% of the known gold occurrences that are used to generate the model. The fuzzy predictive maps delineate at least 76% of the unknown gold occurrences that are not used to generate the model. The results are highly comparable with the results of previous stream-sediment geochemical survey in the area. The results demonstrate the usefulness of a geologically constrained fuzzy set approach to map mineral potential and to redirect surficial exploration work in the search for yet undiscovered gold mineralization in the mining district. The method described is applicable to other mining districts elsewhere.     

城市地理研究中的单分形、多分形和自仿射分形

分形几何学在城市地理研究中具有广泛的应用,然而很多基本概念却让初学者感到迷惑。如何区分单分形、自仿射分形与多分形,是一个基本而重要的问题。简单分形容易理解,而真实的地理现象很少是单分形的。城市生长过程具有自仿射特征,而城市空间格局却具有多分形性质。作者发现,各种分形的共性在于三个方面：标度律、分数维和熵守恒。论文基于标度、分维和熵守恒公式,借助隐喻城市生长的规则分形来区分单分形、多分形和自仿射分形,讨论分形系统演化的机理、分形与空间自相关和空间异质性的联系,同时澄清一些在地理分形研究中的常见错误概念。最后以城市位序-规模分布为例,说明并对比单分形和多分形在城市地理研究中的建模与应用思路。     

区位选择与人文地理系统的分形优化——关于城市区位分形理论一般原理与方法的初步探讨

以城市区位论为主线,提出区位选择的分形思想和方法,旨在探讨人文地理系统空间优化的基本理论。指出区位选择和空间优化应该遵循三个基本原则：自相似原则、匹配原则和包容原则。     

京津冀城镇用地空间结构的多分维谱分析

城市形态和城镇体系都具有分形性质,但简单分形模型不能有效揭示城市系统的复杂结构特征及其背后的问题。多分形模型及分析方法是研究城市空间复杂性和描述城市异质性的有效手段。利用城镇建设用地和总建设用地的多分维谱分析,可以发现京津冀城镇体系及主要城市的空间演化问题。主要结果如下：①京津冀总建设用地的全局谱线不正常,代表中心区的谱线收敛过快,而代表边缘区和乡村地区的谱线收敛位置严重越界;②局部谱线单峰左偏,左(趋向中心区)高密、右(趋向边缘区)低疏,且右边数值越界;③多分维增长曲线服从二次logistic函数,但不同区域和城市的增长曲线的拐点位置不同。深入分析谱线特征及其异常根源,得出如下结论：①京津冀主要城市的中心区填充过密,没有太多缓冲空间,而边缘区无序扩展,需要通过规划进行优化;②京津冀城市生长以外延扩展模式为主,但河北省总建设用地有中心集聚迹象;③京津冀地区特别是主要城市用地接近饱和,土地扩展速度高峰已经过去,只有河北省部分区域例外。     

Are Fractal Dimensions of the Spatial Distribution of Mineral Deposits Meaningful?

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.     

Geologically Constrained Probabilistic Mapping of Gold Potential, Baguio District, Philippines

Binary predictor patterns of geological features are integrated based on a probabilistic approach known as weights of evidence modeling to predict gold potential. In weights of evidence modeling, the log _e of the posterior odds of a mineral occurrence in a unit cell is obtained by adding a weight, W ⁺ or W ^– for presence of absence of a binary predictor pattern, to the log _e of the prior probability. The weights are calculated as log _e ratios of conditional probabilities. The contrast, C = W ⁺ – W ^–, provides a measure of the spatial association between the occurrences and the binary predictor patterns. Addition of weights of the input binary predictor patterns results in an integrated map of posterior probabilities representing gold potential. Combining the input binary predictor patterns assumes that they are conditionally independent from one another with respect to occurrences.     

坝上地区沙漠化过程对景观格局影响的研究

用分维数、修改分维数和景观间隙度指数等分析方法，对坝上地区正兰旗南部７０年代和８０年代的沙漠化土地空间格局进行了分析。研究结果表明：在７０年代，潜在沙漠化土地和强烈发展中沙漠化土地格局的聚集度分别为１．４９和１．１２４，随着沙漠化的发展到８０年代，上述两类型的格局趋向分散；而正在发展中沙漠化土地和严重沙漠化土地的聚集度增高，分别为１．４３７和１．０４８。在沙漠化的发展过程中，整个景观的格局和格局多样性趋向复杂，Ｄ和Ｄｍ分别从１．２７９和１．５９１增加到１．２８５和１．５９９；与此相反，不同沙漠化土地斑块的格局和格局多样性却趋向简单，Ｄ和Ｄｍ分别由１．２５９和１．５８４减少到１．１９４和１．４１４。此外，在沙漠化的发展过程中（从７０年代到８０年代），景观格局和格局多样性的变化，小于斑块格局及其格局多样性的变化     

Multifractal analysis of the spatial distribution of earthquakes in southern Italy

We evaluate the complete spectrum of the generalized fractal dimension of the spatial pattern of microearthquakes in Southern Italy, revealing a multifractal distribution structure. Our analysis is focused on the dependence of the multifractal distribution on the size of the selected area and the kind of seismicity in the area. As the size of the window varies, we observe that the capacity, information and correlation dimensions vary significantly, while both d _∞ and d _−infin; remain unchanged within their errors limits. We interpret this result in terms of the observation that our data are mainly clustered around a linear fault (the Sisifo fault). When we restrict the selected windows around the fault, clustering around a line (the fault) is highlighted. The capacity dimension changes from about 1.8 to about 1.4 and the correlation dimension decreases because we observe in detail the clustering of the seismicity along the fault, which approximates the maximum intense clustering of the whole data set. Although our results are strongly influenced by the fact that the data are dominated by the epicentres located on the fault, we can conclude that multifractal analysis can be a very useful tool to discriminate the seismicity linked to a particular fault in a given area.     

Prospecting for Clinoptilolite-Type Zeolite in a Volcano-Sedimentary Terrain Using ASTER Data: A Case Study from Alborz Mountains,Northern Iran

Zeolites are hydrated alumino-silicates of alkali metals and alkaline earth cations which occur in sedimentary and volcano-sedimentary terrains. In this study, visible–near-infrared and shortwave infrared data of ASTER were evaluated in prospecting for zeolite in part of the green tuff belt of the Alborz Mountains, northern Iran. The study area is dominantly covered by sedimentary and volcano-sedimentary rocks, in which zeolite minerals occur only in the Late Eocene vitric tuff. Principal components (PC) analysis and spectral information divergence (SID) were used to discriminate and map the sedimentary and volcano-sedimentary units and the zeolite-rich areas, respectively. The X-ray diffraction and reflectance spectroscopy results indicated that clinoptilolite is the major type of zeolite mineral in this area. Comparing a color composite image, produced from PC images 1–3–5 as R–G–B, with the published geological map and the field investigations indicated that major sedimentary and volcano-sedimentary units as well as their alluvial deposits were discriminated efficiently. Results of the SID method, using an image-derived spectrum of clinoptilolite as a reference, showed good agreements with the field observations. The results of this study indicated that ASTER data are useful for discriminating various sedimentary and volcano-sedimentary units as well as clinoptilolite-type zeolite-rich areas in arid and semiarid terrains.

     

Modeling-Based Multiscale Deep Prospectivity Mapping: A Case Study of the Haoyaoerhudong Gold Deposit,Inner Mongolia,China

The mineral system modeling approach for prospectivity mapping is an efficient and economic method to assess undiscovered mineral potential quantitatively. It is a procedure of modeling, acquiring, and coupling the proxies of footprints of mineral systems at multiple scales (e.g., regional, district, and deposit scales). In this approach, the critical issue from multiple scales is that the data collected are asymmetrical from the superficial to the deep or from mine to its brown fields, so that it is hard to employ and integrate them. To complete this study, firstly, multi-tactic 3D geological modeling methods, including the explicit, the implicit, and inversion, were used to build geological models in the condition of asymmetrical datasets at the deposit and district scales. Secondly, indicators acquired in drill-intensive fields among multisource datasets composed of geology, geochemistry, geophysics and alteration data were transferred to studies in deep and brown fields. Finally, deep (~?1,100 m) and circumjacent potentials of mine were targeted in the Haoyaoerhudong gold deposit situated in the Urad Middle Banner area, Inner Mongolia, which is one of the largest black-rock-series-type gold mines in China. This proposed procedure is more visual, clear, intuitive, and transferable to drive mineral system approach to exploration discovery than previous GIS-based studies.

     

基于晕状特征提取的化探异常信息识别及其在成矿预测中的应用

常规化探异常信息识别通常都是通过对比观测值与某一异常阈值的高低来判定某样品是否为异常样品,很多方法或者建立在经典统计学基础之上,要求数据符合一定的分布形式,或者面向整个研究区计算异常阈值,而无法顾及实际的地质环境。根据常规方法以数值大小计算异常阈值的原则,并且关注化探数据分布特征信息的分析和挖掘,提出了晕状特征提取方法,该方法能够有效识别局部异常及低缓异常。将此方法用于克拉玛依地区对金矿预测具有指示意义的化探数据的异常信息识别工作,结果表明:该方法能够有效识别化探异常信息,这些异常信息与研究区内已知金矿具有很好的对应关系。晕状特征提取方法在新疆东部的应用案例也显示出较好的结果。该方法可以作为一种有效的化探异常信息识别方法应用于成矿预测实际工作中。     

Weights of Evidence Modeling of Mineral Potential: A Case Study Using Small Number of Prospects,Abra, Philippines

Weights of evidence (WofE) modeling usually is applied to map mineral potential in areas with large number of deposits/prospects. In this paper, WofE modeling is applied to a case study area measuring about 920 km² with 12 known porphyry copper prospects. A pixel size of 100 m × 100 m was used in the spatial data analyses to represent in a raster-based GIS lateral extents of prospects and of geological features considered as spatial evidence. Predictor maps were created based on (a) estimates of studentized values of positive spatial association between prospects and spatial evidence; (b) proportion of number of prospects in zones where spatial evidence is present; and (c) geological interpretations of positive spatial association between prospects and spatial evidence. Uncertainty because of missing geochemical evidence is shown to have an influence on tests of assumption of conditional independence (CI) among predictor maps with respect to prospects. For the final predictive model, assumption of CI is rejected based on omnibus test but is accepted based on a new omnibus test. The final predictive model, which delineates 30% of study area as zones with potential for porphyry copper, has 83% success rate and 73% prediction rate. The results demonstrate plausibility of WofE modeling of mineral potential in large areas with small number of mineral prospects.     

废黄河沉积记录中来自不同河流物质的信息——基于重矿物与地球化学元素分析

在全新世时间尺度内,沉积记录主要受控于沉积物供给、输运和堆积过程等因素。对废黄河沉积记录的深入分析可以反演黄河南流夺淮过程中沉积物的“源”-“汇”关系。基于废黄河故道沉积记录中重矿物和地球化学元素特征,并结合与现代黄河沉积物的对比,揭示废黄河沉积记录中物质来源的信息。结果表明,废黄河故道沉积物中重矿物平均含量为0.19%,种类多达15余种,以稳定矿物为主,不同矿物的时空变化差异较大。废黄河故道泥质和砂质沉积物中,地球化学元素表现出明显的时空变化规律,随深度递增元素含量可分为降低、稳定和增加趋势。对比现代黄河沉积物,发现废黄河故道沉积物中稳定和极稳定矿物相对含量较高,泥质沉积物中更多地富集Zn,Ni,Al,Ba,Cu,Li,K等元素。这一差异性反映出其它不同河流物质补给而产生的影响,淮河沉积物中重矿物和地球化学元素的研究为该论断提供了佐证。     

Soil Iodine Determination in Deccan Syneclise,India: Implications for Near Surface Geochemical Hydrocarbon Prospecting

The association of iodine with organic matter in sedimentary basins is well documented. High iodine concentration in soils overlying oil and gas fields and areas with hydrocarbon microseepage has been observed and used as a geochemical exploratory tool for hydrocarbons in a few studies. In this study, we measure iodine concentration in soil samples collected from parts of Deccan Syneclise in the west central India to investigate its potential application as a geochemical indicator for hydrocarbons. The Deccan Syneclise consists of rifted depositional sites with Gondwana–Mesozoic sediments up to 3.5 km concealed under the Deccan Traps and is considered prospective for hydrocarbons. The concentration of iodine in soil samples is determined using ICP-MS and the values range between 1.1 and 19.3 ppm. High iodine values are characteristic of the northern part of the sampled region. The total organic carbon (TOC) content of the soil samples range between 0.1 and 1.3%. The TOC correlates poorly with the soil iodine (r ² < 1), indicating a lack of association of iodine with the surficial organic matter and the possibility of interaction between the seeping hydrocarbons and soil iodine. Further, the distribution pattern of iodine compares well with two surface geochemical indicators: the adsorbed light gaseous hydrocarbons (methane through butane) and the propane-oxidizing bacterial populations in the soil. The integration of geochemical observations show the occurrence of elevated values in the northern part of the study area, which is also coincident with the presence of exposed dyke swarms that probably serve as conduits for hydrocarbon microseepage. The corroboration of iodine with existing geological, geophysical, and geochemical data suggests its efficacy as one of the potential tool in surface geochemical exploration of hydrocarbons. Our study supports Deccan Syneclise to be promising in terms of its hydrocarbon prospects.     

Mineral Potential Mapping Using a Conjugate Gradient Logistic Regression Model

Mineral potential prediction is a process of establishing a statistical model that describes the relationship between evidence variables and mineral occurrences. In this study, evidence variables were constructed from geological, remote sensing, and geochemical data collected from the Lalingzaohuo district, Qinghai Province, China. Based on these evidence variables, a conjugate gradient logistic regression (CG-LR) model was established to predict exploration targets in the study area. The receiver operating characteristic (ROC) and prediction–area (P-A) curves were used to evaluate the effectiveness of the CG-LR model in mineral potential mapping. The difference between the vertical and horizontal coordinates of each point on the ROC curve was used to determine the optimal threshold for classifying the exploration targets. The optimal threshold corresponds to the point on the ROC curve where the difference between the vertical coordinate and the horizontal coordinate is the largest. In exploration target prediction in the study area, the CG algorithm was used to optimize iteratively the LR coefficients, and the prediction effectiveness was tested for different epochs. With increasing iterations, the prediction performance of the model becomes increasingly better. After 60 iterations, the LR model becomes stable and has the best performance in exploration target prediction. At this point, the exploration targets predicted by the CG-LR model occupy 14.39% of the study area and contain 93% of the known mineral deposits. The exploration targets predicted by the model are consistent with the metallogenic geological characteristics of the study area. Therefore, the CG-LR model can effectively integrate geological, remote sensing, and geochemical data for the study area to predict targets for mineral exploration.