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1.
干旱区TM图像蚀变信息提取方法研究   总被引:3,自引:0,他引:3  
围岩蚀变是成矿作用发生的重要标志之一,从遥感图像中提取蚀变信息是遥感找矿的难点和重要手段。遥感TM数据以其丰富的光谱和连续的空间信息被广泛地应用在地质找矿中,在分析TM影像数据的光谱特征的基础上,根据岩矿光谱特征和遥感信息提取理论,利用全波段主成份分析,选择主成份分析和比值增强、主成份分析相结合的直接主成份法分别对研究区进行了提取,并进行了对比分析和探讨,最终表明直接主成份分析在干旱区可以起到良好的应用效果。  相似文献   

2.
Research on processing geochemical data and identifying geochemical anomalies has made important progress in recent decades. Fractal/multi-fractal models, compositional data analysis, and machine learning (ML) are three widely used techniques in the field of geochemical data processing. In recent years, ML has been applied to model the complex and unknown multivariate geochemical distribution and extract meaningful elemental associations related to mineralization or environmental pollution. It is expected that ML will have a more significant role in geochemical mapping with the development of big data science and artificial intelligence in the near future. In this study, state-of-the-art applications of ML in identifying geochemical anomalies were reviewed, and the advantages and disadvantages of ML for geochemical prospecting were investigated. More applications are needed to demonstrate the advantage of ML in solving complex problems in the geosciences.  相似文献   

3.
In this study, stream sediment geochemical data have been subjected to robust principal components analysis (RPCA) and singularity mapping (SM) to enhance and map significant multivariate geochemical anomalies (i.e., mineralization-related) in Ahar area, NW Iran. The RPCA was applied to (a) account for the compositional nature of stream sediment geochemical data using suitable log-ratio transformation, (b) modulate the effect of outliers in component estimation and (c) derive a multivariate geochemical footprint of mineralization. The SM was applied to extract anomalous patterns of the multivariate geochemical footprint of mineralization. The exploration targets were then delineated using Student’s t-statistics analysis. The correlations of mapped exploration targets with the known mineral occurrences and mineralization-related patterns were further evaluated using normalized density index and overall accuracy analyses.  相似文献   

4.
This study involves the integration of information interpreted from data sets such as LandsatTM, Airborne magnetic, geochemical, geological, and ground-based data of Rajpura—Dariba,Rajasthan, India through GIS with the help of (1) Bayesian statistics based on the weights ofevidence method and (2) a fuzzy logic algorithm to derive spatial models to target potentialbase-metal mineralized areas for future exploration. Of the 24 layers considered, five layers(graphite mica schist (GMS), calc-silicate marble (CALC), NE-SW lineament 0–2000 mcorridor (L4-NESW), Cu 200–250 ppm, and Pb 200–250 ppm) have been identified from theBayesian approach on the basis of contrast. Thus, unique conditions were formed based onthe presence and absence of these five map patterns, which are converted to estimate posteriorprobabilities. The final map, based on the same data used to determine the relationships, showsfour classes of potential zones of sulfide mineralization on the basis of posterior probability.In the fuzzy set approach, membership functions of the layers such as CALC, GMS, NE-SWlineament corridor maps, Pb, and Cu geochemical maps have been integrated to obtain thefinal potential map showing four classes of favorability index.  相似文献   

5.
Using conventional visual interpretation in lineament analysis presents two main problems. The first is subjectivity, introduced because of the bias of various interpreters. The second problem is that lineaments detected from satellite images are constrained by the direction of the illumination source. Since lineament identification mainly involves recognition of diagnostic morphological features, the use of digital elevation can contribute significant information about these features. Further, in generating images using digital elevation data, the direction of illumination can easily be controlled. Thus, the use of digital elevation data offers the possibility of revealing features not apparent in regular satellite images.We discuss a sequential line detection method for extraction of linear features from digital elevation data. In this method, raw elevation data is used for generating shaded relief images using the Lambertian reflection model, wherein the illumination direction is controlled by the user. The Directional Segment Detection Algorithm (DSDA) is used for detecting linear topographic features in user-defined trends. Locational information about these linear features is stored in the computer as coordinate pairs amenable to editing and subsequent analysis. Finally, three-dimensional terrain models are generated by combining the digital elevation data and satellite images. The experiments were carried out using digital elevation data of southwest Japan and Landsat MSS data.  相似文献   

6.
A prospective lithochemical survey (scale 1:50,000) was carried out at the Um Garayat gold mine area within the central wadi Allaqi shear zone. The metavolcanic samples were analyzed for Ti, P, Zr, Nb, Y, La, Nd, and Ce. The background and threshold values were determined using histograms, box-plots, and Q-mode cluster analysis. Discriminant analysis classifies the samples into four groups: Group 1 (Au mineralization) characterizes Phase III of the hydrothermal stage; Group 2 (Cu?CAu mineralization) characterizes Phases I and II; Groups 3 and 4 comprise the least altered samples. Cubic trend surface and residual maps display groups of elements: (P, Ti, Zr), (Nb, Y), and (La, Nd, Ce) each group has similar areal distribution pattern. R-mode factor analysis, using the cubic residuals, produces a model with three factors. Factors 1 (P, Ti, Zr) and 2 (Nb, Y) are referred to the magmatic minerals of the least altered volcanic rocks. In addition, Factor 1 associates with the Au-rich site at the shafts area, whereas Factor 2 is referred to albitization western to the shafts area with high contents of Nb and Y. In Factors 1 and 2, major P and Ti with traces Nb and Y are attributed to the accessories rutile, sphene, anatase, and calcite that were developed during propylitization as well as apatite and calcite-accompanying Phase I of the hydrothermal stage. Phosphorous could be considered as an indicator element for the Au mineralization at the study area. The principal elements of Factor 3 (La, Nd, Ce) associate with the Cu?CAu-rich site at the southern adits area, and attributed to the secondary Ca-bearing accessories calcite, sphene, and apatite. In general, these elements associate with the regional propylitization and the three phases of hydrothermal stage in zones of alkali metasomatism. In these alteration zones, La, Nd, and Ce could be used as indicators during geochemical exploration at the study area. In general, the secondary accessory minerals calcite, apatite, rutile, sphene, and anatase associating with zones of alkali metasomatism are significant carriers for the investigated elements. These accessories are possible indicators during geochemical exploration in the adjacent similar mineralizations of the central Allaqi shear zone area.  相似文献   

7.
GIS techniques have been used in the evaluation of favorability for base-metal mineralization in an area comprising the Cerro Azul and Apiaí quadrangles (SG.22-X-B-IV and V, scale 1:100.000), Ribeira Valley, São Paulo and Paraná States, Brazil. Methods have been employed for selection and weighting of prospective variables when applying GIS techniques to a digital database consisting of geological, geochemical and airborne geophysics, and mineral occurrence information. The exploration variable selection and analysis were based on two mineralization models: (1) Panelas type, vein-type carbonate hosted, and (2) Perau type, sedimentary-exhalative. The overlay was performed by weighted linear combination (WLC) and order weighted average (OWA) methods. Both methods proved suitable for the study area, yielding similar results. The ordered weighted averaging analysis provided the best results, with favorability maps showing a large number of classes occupying relatively minor areas. In comparison, the weighted linear combination analysis produced more coherent results but without details for minor areas. The prospective parameters obtained are considered suitable for both Perau and Panelas types. Both methods are inexpensive, and are suitable for selection of prospective areas during geological surveys in areas similar to the studied one.  相似文献   

8.
Logistic regression has been used in the study to integrate indicator patterns for estimation of the probability of occurrence of gold deposits in a part of the auriferous Archaean Hutti–Maski schist belt. Data used consist of categorical and continuous variables obtained from a coded lineament map and geochemical anomaly maps of the pathfinder elements of gold in soil and groundwater. Main effects and interactions of the variables studied were used in formulating the logistic regression model. Regression models using lineament-proximity data, combined with soil and groundwater geochemical anomalies were tested on parts of the schist belt with data not used in estimation of model parameters. Predicted probabilities greater than 0.9 identified known deposit locations in the area.  相似文献   

9.
翟培  王俊  魏子鑫 《西部资源》2014,(4):144-150
在内蒙古克什克腾旗——白音查干地区,运用土壤地球化学测量方法发现了诸多以银锡为主的成矿元素异常带及找矿靶区,找矿潜力较大。通过1∶5万土壤地球化学测量工作,圈出了成矿元素异常靶区3处,经过1∶1万土壤地球化学测量,进一步缩小了找矿靶区,确定了成矿有利地段12处。经过地质填图及地表工程揭露,发现银、锡、铅锌矿(化)蚀变带20余条,其中,达到边界及工业品位的矿体5条,充分说明了土壤地球化学测量方法在半干旱风成砂覆盖的草原丘陵地区具有良好的找矿效果。  相似文献   

10.

Bétaré-Oya is one of the gold mining districts in the eastern region of Cameroon. Structural controls on gold mineralization were examined along the Bétaré-Oya Shear Zone, providing further clues on favorable areas for mineral exploration. GIS-based methods combining point pattern (i.e., quadrat count, Fry analysis) and distance distribution analysis were employed here to delineate the spatial patterns of known gold deposits and to evaluate their spatial association with geological structures. Results show that the gold deposits in this area are spatially clustered. At the regional scale, the Fry plot indicates an alignment of deposits, suggesting that gold mineralization is controlled by structures oriented NNE–SSW and NE–SW. At the deposit scale, an alignment is also evident, indicating that the mineralization is also controlled by ENE–WSW-trending structures. The cumulative relative frequency distribution of distances from lineament features to gold occurrence points (DM) and to non-occurrence points (DN) ratio (DM/DN) was used to rank these two major structural trends and their relative importance as mineralization control. The yielded grades show that NE–SW-trending lineaments, akin to P-type structures, play a major role in controlling the gold mineralization in the area compared to other structures. Beyond the goal to foster mineral prospection in the Bétaré-Oya gold district, information yielded in the present study provides relevant criteria for further exploration in the eastern region of Cameroon.

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11.
Using the analytic hierarchy process (AHP) method for multi-index evaluation has special advantages, while the use of geographic information systems (GIS) is suitable for spatial analysis. Combining AHP with GIS provides an effective approach for studies of mineral potential mapping evaluation. Selection of potential areas for exploration is a complex process in which many diverse criteria are to be considered. In this article, AHP and GIS are used for providing potential maps for Cu porphyry mineralization on the basis of criteria derived from geologic, geochemical, and geophysical, and remote sensing data including alteration and faults. Each criterion was evaluated with the aid of AHP and the result mapped by GIS. This approach allows the use of a mixture of quantitative and qualitative information for decision-making. The results of application in this article provide acceptable outcomes for copper porphyry exploration.  相似文献   

12.
In this paper, a pixel-based mapping of geochemical anomalies is proposed to avoid estimation errors resulting from using interpolation methods in the modeling of anomalies. The pixel-based method is a discrete field modeling of geochemical landscapes for mapping lithogeochemical anomalies. In this method, the influence area of each composite rock sample is the whole area covered by a pixel where the materials of the sample were taken from. In addition to the pixel-based method, because delineation of mineral exploration target areas using geochemical data is a challenging task, the application of metal zoning concept is demonstrated for vectoring into porphyry mineralization systems. In this regard, different geochemical signatures of the deposit-type sought were mapped in a model. Application of the proposed pixel-based method and the metal zoning concept is a powerful tool for targeting areas with potential for porphyry copper deposits.  相似文献   

13.

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.

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14.
Most regional geochemistry data reflect processes that can produce superfluous bits of noise and, perhaps, information about the mineralization process of interest. There are two end-member approaches to finding patterns in geochemical data—unsupervised learning and supervised learning. In unsupervised learning, data are processed and the geochemist is given the task of interpreting and identifying possible sources of any patterns. In supervised learning, data from known subgroups such as rock type, mineralized and nonmineralized, and types of mineralization are used to train the system which then is given unknown samples to classify into these subgroups.To locate patterns of interest, it is helpful to transform the data and to remove unwanted masking patterns. With trace elements use of a logarithmic transformation is recommended. In many situations, missing censored data can be estimated using multiple regression of other uncensored variables on the variable with censored values.In unsupervised learning, transformed values can be standardized, or normalized, to a Z-score by subtracting the subset's mean and dividing by its standard deviation. Subsets include any source of differences that might be related to processes unrelated to the target sought such as different laboratories, regional alteration, analytical procedures, or rock types. Normalization removes effects of different means and measurement scales as well as facilitates comparison of spatial patterns of elements. These adjustments remove effects of different subgroups and hopefully leave on the map the simple and uncluttered pattern(s) related to the mineralization only.Supervised learning methods, such as discriminant analysis and neural networks, offer the promise of consistent and, in certain situations, unbiased estimates of where mineralization might exist. These methods critically rely on being trained with data that encompasses all populations fairly and that can possibly fall into only the identified populations.  相似文献   

15.
Shang  Zhi  Chen  Yongqing  Xu  Xiaoting  Zhao  Binbin 《Natural Resources Research》2022,31(4):1963-1979

The method of bi-dimensional empirical mode decomposition (BEMD) and the combined methods of entropy weight–Technique for Order of Preference by Similarity to an Ideal Solution (TOPSIS) were used to decompose gravity–magnetic data and evaluate targets in the Luziyuan Pb–Zn–Fe polymetallic ore field and surrounding areas. Three meaningful bi-dimensional intrinsic mode function (BIMF) images were obtained by BEMD at different wavelengths, depicting different layers of geological architectures in the study area. The results are as follows. (1) The BIMF2 images depict the shallow local geological architecture and show positive gravity–magnetic anomalies of the skarn alteration and Pb–Zn–Fe mineralization distributed around concealed granites. (2) The BIMF3 images depict the medium-depth geological architecture, indicating that concealed granitic stocks, which are shallow extensions of a deeply concealed pluton, intruded along the NE-trending fault. (3) The BIMF4 images depict gravity–magnetic anomalies at greater depth, which likely reflect regional geological architectures, indicating the potential presence of a large, concealed intermediate-acid pluton in the negative anomaly zone. Three potential targets (A, B, and C) were delineated based on BEMD results of the original gravity–magnetic data. The entropy weight–TOPSIS evaluation results show that the ranking of the metallogenic potential of the delineated targets in the study area is B, A, and C, with relative proximity values of 0.4576, 0.3925, and 0.1499, respectively. The results of this study can be used to guide future exploration.

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16.

This paper describes the application of an unsupervised clustering method, fuzzy c-means (FCM), to generate mineral prospectivity models for Cu?±?Au?±?Fe mineralization in the Feizabad District of NE Iran. Various evidence layers relevant to indicators or potential controls on mineralization, including geochemical data, geological–structural maps and remote sensing data, were used. The FCM clustering approach was employed to reduce the dimensions of nine key attribute vectors derived from different exploration criteria. Multifractal inverse distance weighting interpolation coupled with factor analysis was used to generate enhanced multi-element geochemical signatures of areas with Cu?±?Au?±?Fe mineralization. The GIS-based fuzzy membership function MSLarge was used to transform values of the different evidence layers, including geological–structural controls as well as alteration, into a [0–1] range. Four FCM-based validation indices, including Bezdek’s partition coefficient (VPc) and partition entropy (VPe) indices, the Fukuyama and Sugeno (VFS) index and the Xie and Beni (VXB) index, were employed to derive the optimum number of clusters and subsequently generate prospectivity maps. Normalized density indices were applied for quantitative evaluation of the classes of the FCM prospectivity maps. The quantitative evaluation of the results demonstrates that the higher favorability classes derived from VFS and VXB (Nd?=?9.19) appear more reliable than those derived from VPc and VPe (Nd?=?6.12) in detecting existing mineral deposits and defining new zones of potential Cu?±?Au?±?Fe mineralization in the study area.

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17.
The Bodie mining district in Mono County, California, is zoned with a core polymetallic-quartz vein system and silver- and gold-bearing quartz-adularia veins north and south of the core. The veins formed as a result of repeated normal faulting during doming shortly after extrusion of felsic flows and tuffs, and the magmatic-hydrothermal event seems to span at least 2 Ma.Epithermal mineralization accompanied repeated movement of the normal faults, resulting in vein development in the planes of the faults. The veins occur in a very large area of argillic alteration. Individual mineralized structures commonly formed new fracture planes during separate fault movements, with resulting broad zones of veinlets growing in the walls of the major vein-faults. The veinlet swarms have been found to constitute a target estimated at 75,000,000 tons, averaging 0.037 ounce gold per ton. The target is amenable to bulkmining exploitation.The epithermal mineralogy is simple, with electrum being the most important precious metal mineral. The host veins are typical low-sulfide banded epithermal quartz and adularia structures that filled voids created by the faulting. Historical data show that beneficiation of the simple vein mineralogy is very efficient. On the cover: Southeast view of Bodie mining district in Mono County, California, one of the more famous pioneer epithermal gold producers in the western U.S. Recent exploration drilling suggests an additional resource of 2 million ounces of gold. The townsite is at the intersection of roads near the center of the photo. The foreground is mainly tuff breccia of the Bodie Hills volcanic field. Arcuate lines in the valley beyond the hills are old Mono Lake shorelines. The White Mountains form the ridge on the skyline. Photo by Frank Kleinhampl, about 1970.  相似文献   

18.
The type, strength, and spatial distributions of hydrocarbon alteration of the surface soil are studied in two sections in East Sichuan area through the simultaneous analysis of soil organic geochemistry, soil mineralogy, and soil chemistry. The spectral response and remote-sensing mechanism are studied through the soil spectral analysis in the range of VIS--NIR bands. The results of this study demonstrate that long-time hydrocarbon microseepage can induce mineral and chemical alteration of surface soil, including the increase of clay-mineral content and carbonate-mineral content, the increase of ferrous-iron content, and decrease of ferric-iron content. Soil mineral components related to hydrocarbon alteration have spatial coincidence with soil organic geochemical components. Increase of clay- and carbonate-mineral contents in the soil can cause decrease of reflectance in VIS–NIR bands and increase of Landsat band ratio TM5/TM7. Increase of ferrous-iron content and decrease of ferric-iron content in the soil may cause increase of reflectance in the range of 400 nm to 600 nm, and higher reflectance of Landsat band ratios of TM1/TM3 and TM2/TM3.  相似文献   

19.
The metallogeny of Central Iran is characterized mainly by the presence of several iron, apatite, and uranium deposits of Proterozoic age. Radial Basis Function Link Networks (RBFLN) were used as a data-driven method for GIS-based predictive mapping of Proterozoic mineralization in this area. To generate the input data for RBFLN, the evidential maps comprising stratigraphic, structural, geophysical, and geochemical data were used. Fifty-eight deposits and 58 ‘nondeposits’ were used to train the network. The operations for the application of neural networks employed in this study involve both multiclass and binary representation of evidential maps. Running RBFLN on different input data showed that an increase in the number of evidential maps and classes leads to a larger classification sum of squared error (SSE). As a whole, an increase in the number of iterations resulted in the improvement of training SSE. The results of applying RBFLN showed that a successful classification depends on the existence of spatially well distributed deposits and nondeposits throughout the study area. An erratum to this article can be found at  相似文献   

20.
Posterior probabilities of occurrence for Zn-Pb Mississippi Valley Type (MVT) mineralization were calculated based on evidence maps derived from regional geology, Landsat-TM, RADARSAT-1, a digital elevation model and aeromagnetic data sets in the Borden Basin of northern Baffin Island, Canada. The vector representation of geological contacts and fault traces were refined according to their characteristics identified in Landsat-TM, RADARSAT-1, DEM, slope, aspect, and shaded relief data layers. Within the study area, there is an association between the occurrence of MVT mineralization and proximity to the contact of platformal carbonates and shale units of the adjacent geological formation. A spatial association also tends to exist between mineralization and proximity to E-W and NW-SE trending faults. The relationships of known MVT occurrences with the geological features were investigated by spatial statistical techniques to generate evidence maps. Supervised classification and filtering were applied to Landsat-TM data to divide the Society Cliffs Formation into major stratigraphic subunits. Because iron oxides have been observed at some of the MVT occurrences within the Borden Basin, Landsat-TM data band ratio (3/1) was calculated to highlight the potential presence of iron-oxides as another evidence map. Processed Landsat-TM data and other derived geological evidence maps provided useful indicators for identifying areas of potential MVT mineralization. Weights of evidence and logistic regression were used independently to integrate and generate posterior probability maps showing areas of potential mineralization based on all derived evidence maps. Results indicate that in spite of the lack of important data sets such as stream or lake sediment geochemistry, Landsat-TM data and regional geological data can be useful for MVT mineral-potential mapping.  相似文献   

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