A new method for determining geochemical anomalies: U-N and U-A fractal models

Undoubtedly, determining the threshold of anomalies and separating geochemical anomalies from background is one of the most important stages of minerals exploration. In the discussion of the separation of geochemical anomalies from background, there are different methods that structural methods have shown much greater efficiency than nonstructural methods. Among structural methods (methods that consider the position and location of samples), U-statistic and fractal methods have a special place. In this study, by using the algorithm of the abovementioned methods and combining them, a new method as U values fractal model (U-N and U-A) is introduced for the first time. Then, the proposed method is employed to determine the boundaries of background and anomalous populations (about the gold (Au) and arsenic (As) elements in Susanvar district). Results show that in U-N and U-A fractal models, the first fracture boundary is much clearer and more accurate than previous fractal models (C-N and C-A) in the same condition. In U-N model, due to the nature of the U method algorithm, there is a discontinuity as the exact threshold between background and anomaly that in U-A model, this does not exist due to the homogenization of U values. In this method, the exact threshold between background and anomaly is determined by the U-statistic method and by its combination with the fractal method, in each population, sub-populations are identified more accurately and simply than the concentration fractal model. Finally, a lithogeochemical map of the study area is provided for Au and As which has been prepared using U-N and U-A fractal methods. In these maps (especially the prepared maps by U-A model), the delineated Au-As mineralization is closely associated with the defined Au ore indications in the study area

Comparing U-statistic and nonstructural methods for separating anomaly and generating geochemical anomaly maps of Cu and Mo in Parkam district, Kerman, Iran

© 2015, Springer-Verlag Berlin Heidelberg.In applied geochemistry, obtaining quantitative descriptions of geochemical patterns and identifying geochemical anomalies are important. To identify and separate geochemical anomalies, several statistical methodologies (nonstructural and structural) are presented by researchers. In this study, four nonstructural methods including threshold assessment method based on median and standard deviation, median absolute deviation (MAD), P.N product and Sinclair’s method are selected first and then U-statistic is considered as a structural method to compare their performance. Subsequently, the best method is used to assess prospective areas of Parkam district. Results show that P.N and Sinclair’s methods are not always efficient. MAD method reduced the background well and roughly increased the correlation factor of points. However, U-statistic method includes both mentioned advantages meaning in addition to reducing outlier data effect, it regularizes anomalous values and also their dispersion is reduced significantly. It is possible to determine anomaly areas according to anomalous samples positioning so that denser areas are more important. Finally, lithogeochemical map of study area is generated for copper and molybdenum. In this map, the Cu mineralization which is delineated by this method is closely associated with the defined potassic alteration zone (according to alteration map of the study area), and also, the delineated Mo mineralization is exactly associated with the phyllic alteration and is spatially conformable with the zone defined for it

Providing the bivariate anomaly map of Cu–Mo and Pb–Zn using combination of statistic methods in Parkam district, Iran

U-statistic method is one of the most important univariate structural methods which considers spatial situation of samples. The U-statistic method could be combined with other methods because it devotes a new value to each sample. However, this method separates anomaly based on one variable. The goal in present study is to use and extend this method in multivariate mode. For this purpose, the U-statistic method should be combined with a multivariate method which devotes a new value to each sample based on several variables. Therefore, the U-statistic was applied on Mahalanobis distance values of samples because Mahalanobis distance is calculated based on several variables. This method is a combination of efficient U-statistic and Mahalanobis distance and is used for the first time. Combination results for Cu, Mo, Pb and Zn elements in Parkam district, Kerman, Iran, led to better performance of these two methods. Results show that samples indicated by the combination of these methods as anomalous are more regular; less dispersed and are more accurate than using just one of them. Also it was observed that combination results (especially for Cu and Mo) are closely associated with the defined zone of potassic alteration in the study area. Finally, bivariate lithogeochemical maps of the study area are provided for Cu–Mo and Pb–Zn which have been prepared using combination of the U-statistic and the Mahalanobis distance methods

Assessment of prospective areas for providing the geochemical anomaly maps of lead and zinc in Parkam district, Kerman, Iran

There are several statistical methodologies presented for separating anomalous values from background leading to determination of anomalous areas. These methods range from simple approaches to complicated ones and include nonstructural and structural methods, subtraction separation method and so on. Structural methods take the sampling locations and their spatial relation into account for estimating the anomalous areas. The U-statistic method is one of the most important structural methods. It considers the location of samples and carries out the statistical analysis of the data without judging from a geochemical point of view and tries to separate subpopulations and also to determine anomalous areas. In the present study, several nonstructural methods including assessment of threshold based on median and standard deviation, median absolute deviation (MAD) and P.N product are used and U-statistic is considered as structural method to assess prospective areas of Parkam district. Results show that MAD method reduced background well and P.N method increased correlation of points. However, U-statistic method plays the role of both mentioned advantages meaning in addition to reducing outlier data effect, it regularizes anomalous values and also their dispersion is reduced significantly. It is possible to determine anomaly areas according to anomalous samples positioning so that denser areas are more important. Finally, lithogeochemical map of study area is provided for lead and zinc

Geology, geochemistry, and some genetic discussion of the Chador-Malu iron oxide-apatite deposit, Bafq District, Central Iran

© 2015, Saudi Society for Geosciences.The Chador-Malu iron oxide-apatite system (Bafq District, Central Iran) contains the largest known iron ore deposit in Iran (pre-mining reserve of 400 Mt @ 55 % Fe), and comprises the pipe-like northern (this study) and the sill-like southern orebodies of predominantly massive ore, and a sodic-calcic alteration envelope. The geology and geochemistry of the Chador-Malu deposit demonstrates its similar characteristics to the Kiruna-type deposits. There is circumstantial evidence for rare earth elements (REE) mobilization during apatite leaching by high-temperature fluids and associated monazite nucleation. Pervasive actinolitization of the rhyolitic country rocks led to the formation of actinolite-rich metasomatic host rocks, which represent another evidence for high-temperature fluids at Chador-Malu. Hydrothermal mineralization is suggested by small iron ore veins (2–3 cm thick) and breccias cemented by iron oxides, as well as a Fe-metasomatism which overprints all types of host rock alteration. Based on REE geochemistry and spatial relationships, it is proposed that a potential source for metals and P could be late-stage Fe-P melt differentiates of the Cambrian magmatism, which is consistent with the late Fe-metasomatism of the host rocks. The proposed Fe-P melts and the mineralization would be linked by hydrothermal media through the zones of ring fracture at Chador-Malu and similar parts of the Bafq district