Mapping complexity of spatial distribution of faults using fractal and multifractal models: vectoring towards exploration targets

In this paper, fractal and multifractal analyses are demonstrated as effective tools for mapping complexity in the spatial distribution of faults. Faults within the eastern part of Gejiu mining area, Yunnan province, west southern China were chosen to demonstrate mapping of the complexity of their spatial distributions using fractal and multifractal models. The results show that (1) the fractal dimensions of the spatial distributions of all faults, NW-trending faults, and NE-trending faults are 1.68, 1.49, and 1.42, respectively, indicating differences in spatial distributions of different sets of faults; (2) the fractal dimensions of the spatial distributions of faults in the four Sn fields in the Gejiu mining district, namely Malage, Gaosong, Laochang, and Kafang (arranged in the order of increasing proportions of surface-projected areas of Sn orebodies) are 1.38, 1.57, 1.65, and 1.41, respectively; and (3) complexity of the spatial distributions of faults, represented by fractal dimension, correlates well with surface-projected areas of Sn orebodies, and lengths of faults satisfy the multifractal statistical and singularity index α, which can be used to quantify the complexity of the spatial distributions of faults.