Abstract

Abstract. The aim of this study is to delineate and identify various mineralized zones and barren host rocks based on surface and subsurface lithogeochemical data from the Pulang porphyry copper deposit, southwestern China, utilizing the number–size (N-S), concentration–volume (C-V) and power-spectrum–volume (S-V) fractal models. The N-S model reveals three mineralized zones characterized by Cu thresholds of 0.28 % and 1.45 %: <0.28 % Cu represents weakly mineralized zones and barren host rocks, 0.28 %–1.45 % Cu represents moderately mineralized zones, and > 1.45 % Cu represents highly mineralized zones. The results obtained by the C-V model depict four geochemical zones defined by Cu thresholds of 0.25 %, 1.48 % and 1.88 %, representing nonmineralized wall rocks (Cu<0.25 %), weakly mineralized zones (0.25 %–1.48 %), moderately mineralized zones (1.48 %–1.88 %) and highly mineralized zones (Cu>1.88 %). The S-V model is used by performing a 3-D fast Fourier transformation of assay data in the frequency domain. The S-V model reveals three mineralized zones characterized by Cu thresholds of 0.23 % and 1.33 %: <0.23 % Cu represents leached zones and barren host rocks, 0.23 %–1.33 % Cu represents hypogene zones, and >1.33 % Cu represents supergene enrichment zones. All the multifractal models indicate that high-grade mineralization occurs in the central and southern parts of the ore deposit. Their results are compared with the alteration and mineralogical models resulting from the 3-D geological model using a log-ratio matrix. The results show that the S-V model is best at identifying highly mineralized zones in the deposit. However, the results of the C-V model for moderately and weakly mineralized zones are also more accurate than those obtained from the N-S and S-V models.

Highlights

  • The definition and delineation of different mineralized zones and non–mineralized wall rocks are the main goal in economic geology and mineral exploration

  • Drill hole logging is dealing with the lack of proper diagnosis of geological phenomena, which can undermine the delineation of mineralized zones because it depends on the subjective interpretation of individual loggers, and no two loggers provide the same interpretations

  • The Cu threshold values of highly mineralized zones are 1.45 % and 1.88 % based on the N-S and concentration– volume (C-V) fractal models

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Summary

Introduction

The definition and delineation of different mineralized zones and non–mineralized wall rocks are the main goal in economic geology and mineral exploration. Methods of fractal analysis illustrate the relationships between geological, geochemical and mineralogical settings and spatial information derived from the analysis of mineral deposit occurrence data (Carranza, 2008, 2010; Carranza et al, 2009; Goncalves et al, 2001). Afzal et al (2011) considered that the log–log plots obtained by fractal methods are useful tools to delineate different geological populations of geochemical data, and the thresholds could be determined as some breakpoints in those plots. Afzal et al (2011, 2012) proposed a C-V and S-V fractal model to delineate different porphyryCu mineralized zones and barren host rocks. N-S, C-V and S-V fractal models were applied to delineate various mineralized zones and barren host rocks in the Pulang porphyry copper deposit, Yunnan, southwestern China

Fractal models
Geological setting of the Pulang porphyry copper deposit
Fractal modeling
Comparison of the fractal models and geological model of the deposit
Findings
Conclusions
Full Text
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