Co-simulated Size Number: An Elegant Novel Algorithm for Identification of Multivariate Geochemical Anomalies
| dc.contributor.author | Madani, Nasser | |
| dc.contributor.author | Carranza, John | |
| dc.date.accessioned | 2020-03-02T06:24:56Z | |
| dc.date.available | 2020-03-02T06:24:56Z | |
| dc.date.issued | 2020-02-01 | |
| dc.description.abstract | Identification of geochemical anomalies is of particular importance for tracing the footprints of anomalies. This can be implemented by advanced techniques of exploratory data analysis, such as fractal/multi-fractal approaches based on priori or posteriori distribution of geochemical elements. The latter workflow involves analysis of 2D/3D produced maps, which can be mostly obtained by geostatistical algorithms. There are two challenging issues for such an analysis. The first one corresponds to handling the cross-correlation structures among the data, and the second one relates to the compositional nature of data. To tackle these problems, this paper investigates the application of Gaussian co-simulation for modeling the cross-correlated compositional data in order to recognize the multivariate geochemical anomalies in integration with fractal analysis. In this context, an innovative algorithm, namely co-simulated size number (CoSS-N), is introduced for this purpose. The compositional nature of data is addressed by additive log-ratio transformation of original data while the Gaussian co-simulation handles the reproduction of cross-correlation among the components. The co-simulated outputs are then taken into account for capturing different geochemical populations, showing different levels of backgrounds and anomalies. The algorithm is illustrated via a real case study located in Philippine wherever seven geochemical components are required to be considered. The accuracy of results is examined by statistical validation techniques, indicating the capability of the CoSS-N algorithm for multivariate identification of geochemical anomalies. | en_US |
| dc.description.sponsorship | Nazarbayev University for through Faculty Development Competitive Research Grants for 2018–2020 under Contract No. 090118FD5336. | en_US |
| dc.identifier.citation | Madani, N., Carranza, E.J.M. Co-simulated Size Number: An Elegant Novel Algorithm for Identification of Multivariate Geochemical Anomalies. Nat Resour Res 29, 13–40 (2020). https://doi.org/10.1007/s11053-019-09547-9 | en_US |
| dc.identifier.issn | 1520-7439 | |
| dc.identifier.uri | http://nur.nu.edu.kz/handle/123456789/4503 | |
| dc.language.iso | en_US | 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/multi-fractal analysis, Turning bands co-simulation, Geostatistical analysis, Cosimulated size number, Compositional data. | en_US |
| dc.title | Co-simulated Size Number: An Elegant Novel Algorithm for Identification of Multivariate Geochemical Anomalies | en_US |
| dc.type | Article | en_US |
| workflow.import.source | science |