Multi-scaling Properties of 2D Reservoir Micro-pore Heterogeneity Based on Digital Casting Thin-Section Images

• Published in: Natural resources research (New York, N.Y.) Vol. 30; no. 1; pp. 359 - 370
• Main Authors: Zhou, Lihong, Qin, Mutian, Xiao, Dunqing, Leng, Chongbiao, Li, Hongjun, Xie, Shuyun, Carranza, E. J. M., Zhang, Jinning
• Format: Journal Article
• Language: English
• Published: New York Springer US 01.02.2021; Springer Nature B.V
• Subjects: Algorithms; Chemistry and Earth Sciences; Cluster analysis; Computer Science; Digital imaging; Earth and Environmental Science; Earth Sciences; Fossil Fuels (incl. Carbon Capture); Fractal analysis; Fractals; Geography; Heterogeneity; Igneous rocks; Image analysis; Image processing; Mathematical Modeling and Industrial Mathematics; Method of moments; Microstructure; Mineral Resources; Original Paper; Parameters; Physics; Reservoirs; Scanning electron microscopy; Sedimentary rocks; Spatial analysis; Statistics for Engineering; Sustainable Development; Volcanic activity; Volcanoes; Heterogeneity; Dagang area; Pore image analysis; Igneous rock; Multifractal
• ISSN: 1520-7439; 1573-8981
• DOI: 10.1007/s11053-020-09747-8

In recent years, in order to study the micro-pore structures of reservoirs, to define the types of reservoir space and to classify and evaluate reservoir capabilities, the technology of numerical image analysis has been concerned widely with the study of pore heterogeneity with fractals and multifractals. This is of great challenge due to developments in image resolutions and quantitative characterization methods. In this paper, the pore structure of digital casting thin-section images of six samples of volcanic and volcano-sedimentary rocks from the Dagang area (Huanghua depression, China) was studied, and then the pore spaces of the reservoir samples were characterized automatically using multifractal parameters advantageous to describe the irregularity and disorder of geometric objects. The method of moments was used to derive the parameters of multifractality and heterogeneity of pore structures. The results show well that, together with cluster analysis, 12 fractal and multifractal parameters can be applied to describe effectively the irregular degrees of pore spaces. The six rock samples have been classified into three groups with various reservoir capabilities. The work presented here can provide new avenues for analysis of the spatial arrangement of mineral particles, aggregates and pores in spaces, and that the multi-scaling nature of casting thin-section images of rocks suggests using these algorithms as a basis for reservoir capability assessment.