First-Pass prospectivity mapping for Au–Ag mineralization in Sikhote–Alin Superterrane, Southeast Russia through field sampling, image enhancement on ASTER data, and MaxEnt modeling

Shevyrev, Sergei; Gorobeyko, Ekaterina V.; Carranza, Emmanuel John M.; Борискина, Н. Г.

doi:10.1007/s12145-022-00906-4

Cited by 1 publication

(1 citation statement)

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“…The mechanical properties such as rock mass stability, heterogeneity, anisotropy, conductibility, permeability, connectivity, and displacement deformation are related to the distribution pattern, scale, and abundance of fracture zones and fractures [20,21]. Understanding spatial fracture distribution and space-filling patterns is a challenging task relevant to engineering applications such as underground construction, geothermal systems, petroleum reservoir exploration, unconventional shale gas production, groundwater management, CO 2 storage, radioactive waste disposal, and mining of mineral resources [22][23][24][25][26][27][28][29][30]. Therefore, knowledge and understanding of the properties of fracture systems greatly benefit the management of exploitation, design, and execution of new drill holes and the understanding of the petrophysical characteristics of rocks [7,31].…”

Section: Introductionmentioning

confidence: 99%

Fractal Characterization of Multiscale Fracture Network Distribution in Dolomites: Outcrop Analogue of Subsurface Reservoirs

Pavičić,

Duić,

Vrbaški

et al. 2023

Fractal Fract

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Fractured aquifers, especially dolomites, are important hydrocarbon reservoirs and sources of thermal and groundwater in many parts of the world, especially in the Alpine-Dinaric-Carpathian region. The most dominant porosity type is fracture porosity, which acts as the preferential fluid pathway in the subsurface, thus strongly controlling fluid flow. Outcrops provide valuable information for the characterization of fracture networks. Dolomite rock properties and structural and diagenetic processes result in fractured systems that can be considered fractals. The fracture network was analyzed on 14 vertical outcrops in 35 digitized photographs. The values of the fractal dimensions varied slightly by the software and method used, but the trends were consistent, which confirms that all methods are valid. Small values of fractal dimension indicate the dominance of a few small or large fractures, and high values of fractal dimension result from a combination of large numbers of small fractures accompanied by a few large fractures. The mean value of the fractal dimension for analyzed fracture networks was 1.648. The results indicate that the fracture network of the Upper Triassic dolomites can be approximated by fractal distribution and can be considered a natural fractal, and values can be extrapolated to higher and lower scales (1D and 3D).

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