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

Abstract

Abstract. Ground magnetic anomaly separation using the reduction-to-the-pole (RTP) technique and the fractal concentration-area (C-A) 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 C-A 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 C-A 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 C-A 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.

Crustal Density and Susceptibility Structure beneath Achankovil Shear Zone, India

“…The studies pertaining to the palaeomagnetism and rock magnetism from the charnockite belts of South India [49] allow us to define the average susceptibility value in the AKSZ and its surrounding region (0.021 to 0.024 in SI unit). In order to carryout modeling, the magnetic field is reduced to pole to decipher the preserved remnant magnetization [50][51][52], as any remanence present in the area will generally show weak signature of magnetic field as also noted as a NS trend in RTP map (Figure 2(c)). This is also corroborated by previous studies in SGT which specifies a remnant magnetization ranging from 0.240 to 0.243 A/m [49,53].…”

Adaptive Interpolation Method for Generalized Triangular Prism (GTP) Geological Model Based on the Geometric Smoothness Rule

“…Recently, the development of human activities in underground spaces has gradually intensified. Due to the subsurface informationization basis, geology (Mansouri et al, 2015;Feizi et al, 2021), water conservancy (Oliveira et al, 2021), hydropower engineering (Bai and Tahmasebi, 2020), mines (Che and Jia, 2019), economic geology (Cuma et al, 2012), hydrology, underground engineering, city ground water, and many other subsurface fields are in urgent need of accurate geometric expressions of underground structures (Ghaleshahi et al, 2015). As a result, many true 3D geological modeling software are becoming a platform to show dynamically geometric structure shape and numerical analysis simulations of the subspace (Hodkiewicz, 2014;Jacquemyn et al, 2018).…”

reply to Referee comment 1

“…The complexities of mineral exploration can be solved by using remote-sensing techniques in the early stages of mineral exploration for the reconnaissance of target areas with the goal of continuing exploratory operations. One of the most recognizable uses with remote sensing is mineral exploration and the identification of various geological structures, faults and lineaments, geological units, alterations, indicator, and tracer minerals (Melesse et al, 2007;Carranza, 2008;Abedi et al, 2013;Golshadi et al, 2016 andMansouri, 2012). The factors mentioned play important roles for recognizing mineralization in the region of interest; so the identification of these factors saves time and cost as well as giving a more precise result (Xiong and Zuo, 2017).…”