Fractal Analysis of Polarizability in Graphite Deposits: Methodological Integration for Geological Prediction and Exploration Efficiency

Yuqi Liang, Qinglin Xia, Kenan Jiang, Ercheng Pang
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Abstract

Most geophysical and geochemical data are commonly acknowledged to exhibit fractal and multifractal properties, but the fractal characteristics of polarizability have received limited attention from the literature. The present study demonstrates that the polarizability data of the graphite deposits have fractal characteristics and introduces the fractal method for its quantitative analysis to indicate and predict the properties of graphite deposits. The results show that the concentration-area (C-A) method is superior to classical interpolation in anomaly extraction but inferior to the spectrum-area (S-A) method in the coverage region. Because the type of graphite ore is sedimentary-metamorphic in this area, the graphite ore-bodies can be regarded as a special stratum, which is different from most metal deposits, and the anomaly of graphite ore are shown in the background mode of the S-A method. The high values of the background mode effectively indicate the potential areas where the graphite-bearing strata occur, while observing a decrease in the power-law exponent (β) of the background mode as the width of ore-bodies increases. The validity of this conclusion was confirmed based on the vertical profiles of the predicted area, and the uncharted ore vein was thereby identified. Furthermore, it was found that the anomaly mode can serve as a grade indicator of graphite ore rather than delineating the fault. By integrating the background and anomaly modes of the S-A method, we can quantitatively predict and effectively identify high-grade targets from sedimentary deposits containing minerals in future exploration.
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石墨矿床极化性的分形分析:地质预测与勘探效率的方法整合
一般认为,大多数地球物理和地球化学数据都具有分形和多分形特性,但极化率的分形特性在文献中受到的关注有限。本研究证明石墨矿床的极化率数据具有分形特征,并引入分形方法对其进行定量分析,以指示和预测石墨矿床的性质。结果表明,在异常提取方面,浓度-面积(C-A)法优于经典插值法,但在覆盖区域方面,浓度-面积(C-A)法不如光谱-面积(S-A)法。由于该地区的石墨矿类型为沉积-变质岩型,石墨矿体可视为一个特殊地层,与大多数金属矿床不同,石墨矿异常在 S-A 方法的背景模式中显示。背景模式的高值有效地指示了含石墨地层的潜在区域,同时观察到背景模式的幂律指数(β)随着矿体宽度的增加而减小。根据预测区域的垂直剖面证实了这一结论的正确性,并由此确定了未知矿脉。此外,研究还发现,异常模式可以作为石墨矿的品位指标,而不是划分断层。通过整合 S-A 方法的背景模式和异常模式,我们可以在未来的勘探中对含矿沉积矿床的高品位目标进行定量预测和有效识别。
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