Articles | Volume 22, issue 5
Nonlin. Processes Geophys., 22, 579–587, 2015
Nonlin. Processes Geophys., 22, 579–587, 2015

Research article 07 Oct 2015

Research article | 07 Oct 2015

Identification of magnetic anomalies based on ground magnetic data analysis using multifractal modelling: a case study in Qoja-Kandi, East Azerbaijan Province, Iran

E. Mansouri1, F. Feizi2, and A. A. Karbalaei Ramezanali1 E. Mansouri et al.
  • 1Young Researchers and Elite Club, South Tehran Branch, Islamic Azad University, Tehran, Iran
  • 2Mine Engineering Department, South Tehran Branch, Islamic Azad University, Tehran, Iran

Abstract. Ground magnetic anomaly separation using the reduction-to-the-pole (RTP) technique and the fractal concentration–area (CA) method has been applied to the Qoja-Kandi prospecting area in northwestern Iran. The geophysical survey resulting in the ground magnetic data was conducted for magnetic element exploration. Firstly, the RTP technique was applied to recognize underground magnetic anomalies. RTP anomalies were classified into different populations based on the current method. For this reason, drilling point area determination by the RTP technique was complicated for magnetic anomalies, which are in the center and north of the studied area. Next, the CA method was applied to the RTP magnetic anomalies (RTP-MA) to demonstrate magnetic susceptibility concentrations. This identification was appropriate for increasing the resolution of the drilling point area determination and decreasing the drilling risk issue, due to the economic costs of underground prospecting. In this study, the results of CA modelling on the RTP-MA are compared with 8 borehole data. The results show that there is a good correlation between anomalies derived via the CA method and the log report of boreholes. Two boreholes were drilled in magnetic susceptibility concentrations, based on multifractal modelling data analyses, between 63 533.1 and 66 296 nT. Drilling results showed appropriate magnetite thickness with grades greater than 20 % Fe. The total associated with anomalies containing andesite units hosts iron mineralization.