Multi-method characterization of sandstone pore size distribution heterogeneity and its influence on porosity and permeability variation

被引:0
|
作者
Zhang, Junjian [1 ]
Quan, Fangkai [2 ,3 ]
Zhang, Hui [1 ,4 ]
Shao, Yinchuan [5 ]
Han, Yanning [5 ]
Yang, Yuqiang [5 ]
Chang, Xiangchun [1 ]
Zhang, Xiaoyang [1 ]
机构
[1] Shandong Univ Sci & Technol, Coll Earth Sci & Engn, Qingdao 266590, Peoples R China
[2] China Univ Min & Technol, Key Lab Coalbed Methane Resource & Reservoir Forma, Minist Educ, Xuzhou 221008, Peoples R China
[3] Anhui Univ Sci & Technol, Sch Safety Sci & Engn, Huainan 232001, Peoples R China
[4] Geophys Prospecting & Surveying Team Shandong Bur, Jinan 250104, Peoples R China
[5] Shandong Engn Res Ctr Mine Gas Disaster Prevent, Qingdao 266427, Peoples R China
来源
FRONTIERS OF EARTH SCIENCE | 2024年
关键词
tight sandstone; pore size distribution; fractal dimension; multi-fractal model; permeability-porosity; MERCURY INTRUSION POROSIMETRY; NUCLEAR-MAGNETIC-RESONANCE; HIGH RANK COALS; FRACTAL CHARACTERISTICS; MATRIX COMPRESSIBILITY; MULTIFRACTAL ANALYSIS; DEFORMED COALS; GAS-ADSORPTION; DIMENSIONS; MIDDLE;
D O I
10.1007/s11707-022-1044-8
中图分类号
P [天文学、地球科学];
学科分类号
07 ;
摘要
Pore volume/surface area and size distribution heterogeneity are two important parameters of pore structures, which restrict the gas-water-oil migration process in sandstone reservoirs. The fractal theory has been proved to be one of the most effective methods to quantify pore distribution heterogeneity. However, the dynamic variation of porosity and permeability due to fractal characteristics has been rarely studied. In this paper, physical properties, mineral composition, and pore distribution of 18 groups of sandstone samples were analyzed using scanning electron microscope (SEM) and high-pressure mercury injection tests. Then, Sierpinski model, Menger model, thermodynamic model, and multi-fractal model were used to calculate the fractal dimension of the pore volume. Thus, the relationship between fractal dimension and porosity/permeability variation rate, and pore compressibility were studied. The results are as follows. 1) All samples can be divided into three types based on pore volume (0.9 cm(3)<middle dot>g(-1)) and mercury removal efficiency (35%), i.e., Type A (< 0.9 cm(3)<middle dot>g(-1)and < 35%); Type B (> 0.9 cm(3)<middle dot>g(-1) and <35%); Type C (> 0.9 cm(3)<middle dot>g(-1) and > 35%). 2) Four fractal models had poor applicability in characterizing fractal characteristics of different sample types. The fractal dimension by the Sierpinski model had a good linear correlation with that of other models. Pores with smaller volumes dominated the overall pore distribution heterogeneity by multi-fractal dimension. The pore diameter between 200-1000 nm and larger than 1000 nm was the key pore size interval that determined the fractal characteristics. 3) With the increase of confining pressures, porosity and permeability decreased in the form of a power function. The compressibility coefficient of typical samples was 0.002-0.2 MPa-1. The compressibility of Types A and B was significantly higher than that of Type C, indicating that the total pore volume was not the key factor affecting the pore compressibility. The correlation of compressibility coefficient/porosity variation rate with pore volume (total and different size pore volume), fractal value and mineral component were not significant. This indicates that these three factors comprehensively restricted pore compression.
引用
收藏
页码:814 / 830
页数:17
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