A novel iterative approach for mapping local singularities from geochemical data
- 1State Key Laboratory of Geological Processes and Mineral Resources, Wuhan 430074, Beijing 100083, China
- 2Faculty of Earth Resources, China University of Geosciences, Wuhan Hubei 430074, China
- 3Department of Earth and Space Science, Department of Geography, York University, Toronto, M3J 1P3, Canada
- 4Faculty of Earth Sciences, China University of Geosciences, Wuhan Hubei 430074, China
Abstract. There are many phenomena in nature, such as earthquakes, landslides, floods, and large-scale mineralization that are characterized by singular functions exhibiting scale invariant properties. A local singularity analysis based on multifractal modeling was developed for detection of local anomalies for mineral exploration. An iterative approach is proposed in the current paper for improvement of parameter estimations involved in the local singularity analysis. The advantage of this new approach is demonstrated with de Wijs's zinc data from a sphalerite-quartz vein near Pulacayo in Bolivia. The semivariogram method was used to illustrate the differences between the raw data and the estimated data by the new algorithm. It has been shown that the outcome of the local singularity analysis consists of two components: singularity component characterized by local singularity index and the non-singular component by prefractal parameter.