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Introducing 3D U-statistic method for separating anomaly from background in exploration geochemical data with associated software development

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Abstract

The U-statistic method is one of the most important structural methods to separate the anomaly from the background. 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 determine anomalous areas. In the present study, to use U-statistic method in three-dimensional (3D) condition, U-statistic is applied on the grade of two ideal test examples, by considering sample Z values (elevation). So far, this is the first time that this method has been applied on a 3D condition. To evaluate the performance of 3D U-statistic method and in order to compare U-statistic with one non-structural method, the method of threshold assessment based on median and standard deviation (MSD method) is applied on the two example tests. Results show that the samples indicated by U-statistic method as anomalous are more regular and involve less dispersion than those indicated by the MSD method. So that, according to the location of anomalous samples, denser areas of them can be determined as promising zones. Moreover, results show that at a threshold of U = 0, the total error of misclassification for U-statistic method is much smaller than the total error of criteria of \(\bar {x}+n\times s\). Finally, 3D model of two test examples for separating anomaly from background using 3D U-statistic method is provided. The source code for a software program, which was developed in the MATLAB programming language in order to perform the calculations of the 3D U-spatial statistic method, is additionally provided. This software is compatible with all the geochemical varieties and can be used in similar exploration projects.

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Correspondence to Ardeshir Hezarkhani.

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Ghannadpour, S.S., Hezarkhani, A. Introducing 3D U-statistic method for separating anomaly from background in exploration geochemical data with associated software development. J Earth Syst Sci 125, 387–401 (2016). https://doi.org/10.1007/s12040-016-0657-2

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  • DOI: https://doi.org/10.1007/s12040-016-0657-2

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