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Capturing Hidden Geochemical Anomalies in Scarce Data by Fractal Analysis and Stochastic Modeling

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dc.contributor.author Madani, Nasser
dc.contributor.author Sadeghi, Behnam
dc.contributor.editor John, Carranza
dc.date.accessioned 2018-10-25T03:10:15Z
dc.date.available 2018-10-25T03:10:15Z
dc.date.issued 2018
dc.identifier.citation 1) Madani, N., Sadeghi, B. (2018). “Capturing Hidden Geochemical Anomalies in Scarce Data by Fractal Analysis and Stochastic Modeling”. Natural Resources Research, DOI: 10.1007/s11053-018-9421-4. In press. en_US
dc.identifier.other https://doi.org/10.1007/s11053-018-9421-4
dc.identifier.uri http://nur.nu.edu.kz/handle/123456789/3551
dc.description.abstract Fractal/multifractal modeling is a widely used geomathematical approach to capturing different populations in geochemical mapping. The rationale of this methodology is based on empirical frequency density functions attained from global or local distributions. This approach is quite popular because of its simplicity and versatility; it accounts for the frequency and spatial distribution of geochemical data considering self-similarity across a range of scales. Using this technique for detection of geochemical anomalies in scarce data, however, is problematic and can lead to systematic bias in the characterization of the underlying populations. In this paper, an innovative technique is presented that provides good results without a priori assumptions. A simulation approach is adopted for fractal analysis by generating different possible distribution scenarios for the variable under study to reveal the underlying populations that are frequently hidden due to lack of data. The proposed technique is called the global simulated size–number method, and it is validated in a case study with two synthetic datasets and another case study with real dataset from the Ushtagan gold deposit in northeast Kazakhstan. en_US
dc.description.sponsorship Nazarbayev University en_US
dc.language.iso en en_US
dc.publisher Natural Resources Research en_US
dc.rights CC0 1.0 Universal *
dc.rights.uri http://creativecommons.org/publicdomain/zero/1.0/ *
dc.subject Fractal modeling en_US
dc.subject Monte Carlo simulation en_US
dc.subject Kernel density function en_US
dc.subject Ushtagan gold deposit en_US
dc.title Capturing Hidden Geochemical Anomalies in Scarce Data by Fractal Analysis and Stochastic Modeling en_US
dc.type Article en_US
workflow.import.source science

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