## Abstract

Geochemical anomaly recognition of target elements, classified from background to high concentrations, has an important role in geochemical exploration projects. In addition to geological and geochemical studies, we need to generate the geochemical anomaly models and evaluate their accuracy mathematically and geologically. Fractal/multi-fractal modeling is one of the most important methods to recognize geochemical anomalies. In our research, we studied the Cu geochemical anomalies in Sweden (as an example), mainly related to the volcanogenic massive sulfide (VMS) ore deposits as one of the most significant sources of base-metals. We analyzed the geochemical data of 2578 till samples from 75% of the country. The sampling density is one sample per 150 km^{2}, and the samples were spaced approximately 12.5 km apart. A "concentration-distance from centroids (C-DC)" fractal model was developed based on the concentration-distance (C-D) fractal model, which was originally developed based on the radial-density (R-D) model. In our proposed model, the individual C-DC fractal models/log-log plots are generated based on the relation between the cumulative distance of the samples from each base-metal centroid point and the element concentration. Each Cu C-DC model was generated for each base-metal. Then we generated the mean model of all C-DC fractal models. Considering this model, the main geochemical anomalies of Cu in the study area are mostly located in the Northern and NW Sweden (i.e., Caledonides and Northern Norrbotten areas) although there are also smaller anomalies in SW and SE and Central Sweden (i.e., Goteborg, Ostergotland and Jämtland to Bergslagen areas). To quantify the overall accuracy (OA) of the C-DC fractal model, we compared it with existing geological evidence, the Cu geochemical map, published by Geological Survey of Sweden (SGU) in 2014. The comparison demonstrated similar overlap of the Cu geochemical anomalies recognized by the C-DC fractal model with the Cu published geochemical map, resulting in an OA of 0.84. This OA is very close to the OA quantified for the number-size (N-S) fractal model, as a well-established fractal model, applied to the same data.

Original language | English |
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Pages | 49-53 |

Number of pages | 5 |

State | Published - 2019 |

Externally published | Yes |

Event | 20th Annual Conference of the International Association for Mathematical Geosciences, IAMG 2019 - State College, United States Duration: 10 Aug 2019 → 16 Aug 2019 |

### Conference

Conference | 20th Annual Conference of the International Association for Mathematical Geosciences, IAMG 2019 |
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Country/Territory | United States |

City | State College |

Period | 10/08/19 → 16/08/19 |

### Bibliographical note

Publisher Copyright:© Proceedings of IAMG 2019 - 20th Annual Conference of the International Association for Mathematical Geosciences. All rights reserved.