2017•Geosystem EngineeringRequires access

Applying the combination of U-statistic and Mahalanobis distance as a multivariate structural method for the delineation of geochemical anomalies

Seyyed Saeed Ghannadpour, Ardeshir Hezarkhani

Open publisher page 6 citations

Abstract

There are several statistical methods 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. 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, two nonstructural methods including gap statistic and Mahalanobis distance method (as a multivariate method) are used and U-statistic is considered as a structural method to assess prospective areas of Parkam district. Results show that the samples indicated by U-statistic and gap statistic methods as anomalous are more regular and less dispersed compared to those indicated by other nonstructural methods. Both gap statistic and U-statistic methods have shown almost similar results for estimating threshold and separation, but U-statistic method is even better than gap statistic because the U-statistic method devotes a new value to each sample which can be combined with other methods. For this reason, the combination of U-statistic and Mahalanobis distance method has been employed to separate geochemical anomaly from background. Combination results show that the performance of these two methods is more accurate than using just one of them. Finally, bivariate lithogeochemical map of the study area is provided for Cu and Mo which has been prepared using combination of the U-statistic and Mahalanobis distance method. In this map, the delineated Cu-Mo mineralization is closely associated with the defined zone of potassic alteration, which is also consistent with the field and microscopic observation of the Cu mineralization in this alteration zone. Moreover, it is associated with the phyllic alteration and is spatially conformable with the zone defined for it.

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What this paper is about

There are several statistical methods 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. 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, two nonstructural methods including gap statistic and Mahalanobis distance method (as a multivariate method) are used and U-statistic is considered as a structural method to assess prospective areas of Parkam district. Results show that the samples indicated by U-statistic and gap statistic methods as anomalous are more regular and less dispersed compared to those indicated by other nonstructural methods. Both gap statistic and U-statistic methods have shown almost similar results for estimating threshold and separation, but U-statistic method is even better than gap statistic because the U-statistic method devotes a new value to each sample which can be combined with other methods. For this reason, the combination of U-statistic and Mahalanobis distance method has been employed to separate geochemical anomaly from background. Combination results show that the performance of these two methods is more accurate than using just one of them. Finally, bivariate lithogeochemical map of the study area is provided for Cu and Mo which has been prepared using combination of the U-statistic and Mahalanobis distance method. In this map, the delineated Cu-Mo mineralization is closely associated with the defined zone of potassic alteration, which is also consistent with the field and microscopic observation of the Cu mineralization in this alteration zone. Moreover, it is associated with the phyllic alteration and is spatially conformable with the zone defined for it.

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Available abstract

There are several statistical methods 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. 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, two nonstructural methods including gap statistic and Mahalanobis distance method (as a multivariate method) are used and U-statistic is considered as a structural method to assess prospective areas of Parkam district. Results show that the samples indicated by U-statistic and gap statistic methods as anomalous are more regular and less dispersed compared to those indicated by other nonstructural methods. Both gap statistic and U-statistic methods have shown almost similar results for estimating threshold and separation, but U-statistic method is even better than gap statistic because the U-statistic method devotes a new value to each sample which can be combined with other methods. For this reason, the combination of U-statistic and Mahalanobis distance method has been employed to separate geochemical anomaly from background. Combination results show that the performance of these two methods is more accurate than using just one of them. Finally, bivariate lithogeochemical map of the study area is provided for Cu and Mo which has been prepared using combination of the U-statistic and Mahalanobis distance method. In this map, the delineated Cu-Mo mineralization is closely associated with the defined zone of potassic alteration, which is also consistent with the field and microscopic observation of the Cu mineralization in this alteration zone. Moreover, it is associated with the phyllic alteration and is spatially conformable with the zone defined for it.

Key concepts: Mahalanobis distance, Statistic, Statistics, Multivariate statistics, Bivariate analysis, Completeness (order theory), Ancillary statistic, Mathematics

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