Get 20M+ Full-Text Papers For Less Than $1.50/day. Start a 14-Day Trial for You or Your Team.

Learn More →

Delineation of geochemical anomalies for mineral exploration using combining U-statistic method and fractal technique: U-N and U-A models

Delineation of geochemical anomalies for mineral exploration using combining U-statistic method... In this study, by using the algorithm of the U-statistic and fractal methods and combining them with each other, a new combined method as U values fractal model (U-N and U-A) is introduced. Then, the proposed method is employed to determine the boundaries of background and anomalous populations. Results show that in U-N and U-A fractal models, the first fracture boundary is much clearer and more accurate than previous fractal models (C-N and C-A) in the same condition. In U-N model, due to the nature of the U method algorithm, there is a discontinuity as exact threshold between background and anomaly that in U-A model, this does not exist due to the homogenization of U values. In this method, the exact threshold between background and anomaly is determined by U-statistic method and by its combination with the fractal method, in each population, sub-populations are identified more accurately and simply than concentration fractal model. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Applied Earth Science Taylor & Francis

Delineation of geochemical anomalies for mineral exploration using combining U-statistic method and fractal technique: U-N and U-A models

Download PDF

Delineation of geochemical anomalies for mineral exploration using combining U-statistic method and fractal technique: U-N and U-A models

Abstract

In this study, by using the algorithm of the U-statistic and fractal methods and combining them with each other, a new combined method as U values fractal model (U-N and U-A) is introduced. Then, the proposed method is employed to determine the boundaries of background and anomalous populations. Results show that in U-N and U-A fractal models, the first fracture boundary is much clearer and more accurate than previous fractal models (C-N and C-A) in the same condition. In U-N model, due to...
Loading next page...
 
/lp/taylor-francis/delineation-of-geochemical-anomalies-for-mineral-exploration-using-ARH5dntDns
Publisher
Taylor & Francis
Copyright
© 2022 Institute of Materials, Minerals and Mining and The AusIMM
ISSN
2572-6838
eISSN
2572-6846
DOI
10.1080/25726838.2022.2041151
Publisher site
See Article on Publisher Site

Abstract

In this study, by using the algorithm of the U-statistic and fractal methods and combining them with each other, a new combined method as U values fractal model (U-N and U-A) is introduced. Then, the proposed method is employed to determine the boundaries of background and anomalous populations. Results show that in U-N and U-A fractal models, the first fracture boundary is much clearer and more accurate than previous fractal models (C-N and C-A) in the same condition. In U-N model, due to the nature of the U method algorithm, there is a discontinuity as exact threshold between background and anomaly that in U-A model, this does not exist due to the homogenization of U values. In this method, the exact threshold between background and anomaly is determined by U-statistic method and by its combination with the fractal method, in each population, sub-populations are identified more accurately and simply than concentration fractal model.

Journal

Applied Earth Science – Taylor & Francis

Published: Jan 2, 2022

Keywords: Mineral exploration; porphyry deposits; anomalies delineation; Parkam; U-STATISTICS; U-N and U-A fractal

References

  • Delineation of mineralization zones in porphyry Cu deposits by fractal concentration–volume modeling
  • Geochemical anomaly separation by multifractal modeling in Kahang (Gor Gor) porphyry system, central Iran
  • Geochemical anomaly and mineral prospectivity mapping in GIS. In: Emmanuel John M. Carranza, editor. Handbook of exploration and environmental geochemistry, vol. 11. Amsterdam, the Netherlands (2008): Elsevier; Hardbound, 368 pp., USD 165; Eur. 135, ISBN: 987-0-444-51325-0
  • Geochemistry of stream sediments as a tool for assessing contamination by arsenic, chromium and other toxic elements: East Attica region, Greece
  • Partitioning geochemical populations by Sinclair’s method
  • Mineral prospectivity modelling using singularity mapping and multifractal analysis of stream sediment geochemical data from the auriferous Hutti-Maski schist belt, S. India
  • The legacy of John Webb and the applied geochemistry research group, imperial college of science and technology, London, to geochemical exploration in Australia
  • West African lateritic pediments: landform-regolith evolution processes and mineral exploration pitfalls
  • A spatial analysis method for geochemical anomaly separation
  • Integrated spatial and spectrum method for geochemical anomaly separation
  • A review of indicator minerals and sample processing methods for geochemical exploration
  • Investigation of Cu, Mo, Pb, and Zn geochemical behavior and geological interpretations for Parkam porphyry copper system, Kerman, Iran
  • Lead and zinc geochemical behavior based on geological characteristics in Parkam porphyry copper system, Kerman, Iran
  • Introducing 3D U-statistic method for separating anomaly from background in exploration geochemical data with associated software development
  • Exploration geochemistry data-application for anomaly separation based on discriminant function analysis in the Parkam porphyry system (Iran)
  • Comparing U-statistic and nonstructural methods for separating anomaly and generating geochemical anomaly maps of Cu and Mo in Parkam district, Kerman, Iran
  • Providing the bivariate anomaly map of Cu–Mo and Pb–Zn using combination of statistic methods in Parkam district, Iran
  • Mineral potential mapping for Au and As using gap statistic method in multivariate mode
  • Assessment of prospective areas for providing the geochemical anomaly maps of lead and zinc in Parkam district, Kerman, Iran
  • Some statistical analyses of Cu and Mo variates and geological interpretations for Parkam porphyry copper system, Kerman, Iran
  • The Parkam exploration district (Kerman, Iran): geology, alterations, and delineation of Cu- and Mo-mineralized zones using U-spatial statistic with associated software development
  • A method for extracting anomaly map of Au and As using combination of U-statistic and Euclidean distance methods in Susanvar district, Iran
  • Applying a structural multivariate method using the combination of statistical methods for the delineation of geochemical anomalies
  • Modification of Sinclair’s mixed statistical populations algorithm based on probability plots
  • Delimiting geochemical anomalies in the exploration of covered deposits with multifractal methods and using stream sediment data from the Iberian Pyrite belt, Southwest Iberia
  • Geochemical anomaly separation by multifractal modeling
  • Identification of geochemical anomalies by using of number–size (N–S) fractal model in Bardaskan area, NE Iran
  • Application of concentration–number (C-N) multifractal modeling for geochemical anomaly separation in Haftcheshmeh porphyry system, NW Iran
  • Numerical modeling of ore-forming processes within the chating Cu-Au porphyry-type deposit, China: implications for the longevity of hydrothermal systems and potential uses in mineral exploration
  • Economic geology: then and now
  • Application of limited fuzzy clusters to anomaly recognition in complex geological environments
  • Application of a fractal method relating concentrations and distances for separation of geochemical anomalies from background
  • Copper prospectivity in Tibet, China: based on the identification of geochemical anomalies
  • Lateral and vertical alteration-mineralization zoning in porphyry ore deposits
  • Geochemistry of stream sediments southwards of the SW Variscan suture in Portugal (Guadiana and Chança river basins): insights into element anomalies of variable origin and intensity
  • Estimation of the geochemical threshold and its statistical significance
  • Delineation of the Cr mineralization based on the stream sediment data utilizing fractal modeling and factor analysis in the Khoy 1:100,000 sheet, NW Iran
  • Application of multifractal models to identify geochemical anomalies in Zarshuran Au deposit, NW Iran
  • Identification of multivariate geochemical anomalies using spatial autocorrelation analysis and robust statistics
  • Factor analysis of stream sediment geochemical data from the Mount Nansen area, Yukon Territory, Canada
  • A fundamental approach to threshold estimation in exploration geochemistry: probability plots revisited
  • Relationships between porphyry Cu–Mo mineralization in the Jinshajiang–Red River metallogenic belt and tectonic activity: constraints from zircon U–Pb and molybdenite Re–Os geochronology
  • Identifying geochemical anomalies associated with Cu and Pb–Zn skarn mineralization using principal component analysis and spectrum-area fractal modeling in the Gangdese belt, Tibet (China)