Fractal Characterization of Nanoscale Pores of Volcanic Reservoirs in the Dongling Area, Changling Fault Depression, Songliao Basin

• Published in: Natural resources research (New York, N.Y.) N.Y.), 2021-10, Vol.30 (5), p.3483-3502
• Main Authors: Cang, Zhengyi, Shan, Xuanlong, Yi, Jian, Yue, Qingyou, Xu, Chuan, Zou, Xintong, Ren, Xianjun, Han, Jiaoyan
• Format: Article
• Language: English
• Subjects: Chemistry and Earth Sciences; Cluster analysis; Clustering; Computer Science; Earth and Environmental Science; Earth Sciences; Fossil Fuels (incl. Carbon Capture); Fractal geometry; Fractal models; Fractals; Geography; Low temperature; Mathematical Modeling and Industrial Mathematics; Mercury; Mineral Resources; Original Paper; Percolation; Physical characteristics; Physics; Pore size; Pore size distribution; Pores; Porosity; Reservoirs; Resource development; Rocks; Size distribution; Statistics for Engineering; Surface roughness; Sustainable Development; Volcanic rocks
• ISSN: 1520-7439; 1573-8981
• DOI: 10.1007/s11053-021-09867-9

Fractal theory is an efficient method to characterize quantitatively tight rocks. Volcanic rocks are very promising reservoirs, and their pore structures have considerable influence on the occurrence and percolation mechanisms of oil and gas. Therefore, the research topics of pore structure and fractal characteristics are important for sustainable volcanic resource development. The pore structure and fractal characteristics of microscopic pores of volcanic reservoirs in the Changling Fault Depression, Songliao Basin, were studied by combining fractal theory with mercury intrusion porosimetry and low-temperature nitrogen adsorption technique. After quantitative characterization of the nanoscale pore size distribution (PSD), four fractal dimensions were calculated. Subsequently, the relationships between fractal dimensions and pore structure parameters were evaluated. Three types of PSD models of volcanic reservoirs in the study area were established. The relationships between fractal dimensions and PSD models, as well as the clustering characteristics of the fractal dimensions, were investigated. The study revealed that the volcanic reservoirs developed a certain proportion of nanoscale pores with morphological characteristics dominated by wedge-shaped pores and slit pores. D 4 is relatively strongly negatively correlated with pore size, illustrating that it can better reflect pore structure compared to the other fractal dimensions. Additionally, D 4 can reflect pore surface roughness. This study shows that D 1 and D 2 can distinguish PSD models well, but D 3 and D 4 are more effective for the identification of the Type II PSD model. The fractal dimensions were divided into four clusters via hierarchical cluster analysis, each corresponding well to a certain PSD model or PSD model combination.