Numerical simulation method on the impact of the difference of rock composition and structure on the development mechanism of fractured reservoirs: A case study from the granitoids in Jiyang Depression

doi:10.13745/j.esf.sf.2025.2.7

Abstract

Abstract:

Fractured oil and gas reservoirs represent a significant source of growth for global oil and gas reserves. Their proven geological reserves constitute more than 30% of the global total. These reservoirs are widely distributed and possess substantial exploration potential. Rock composition and structure (mineral composition, grain size, texture) are fundamental factors controlling fracture development. While the particle discrete element method has been applied to study the mechanical properties of brittle minerals and microfracture mechanisms, the influence of variations in rock composition and structure on fracture development degree and its underlying mechanism have received relatively little attention. This study addresses the key scientific issue regarding the fracture mechanism in granitic bedrock considering variations in composition and structure. To address this issue, discrete element numerical models incorporating mineral content, grain size, orientation, macroscopic mechanical properties, and fracture development patterns were constructed to clarify the control mechanism of rock composition and structure on fracture development, thereby providing valuable insights for the exploration of fractured reservoirs. Using the fractured granitic bedrock reservoir in the Jiyang Depression as a case study, we quantitatively characterized the rock composition and structure through core observation, petrographic thin section analysis, and XRD. Based on these results, an initial discrete element numerical model for predicting rock composition and fractures was established. The microscopic parameters of the initial model were calibrated and verified using uniaxial compression tests and acoustic emission monitoring. Subsequently, a comprehensive quantitative model predicting the impact of rock composition and structure on mechanical properties and fracture development was developed. The main findings are as follows: (1) Quantification of intracrystalline fractures revealed that alkali feldspar makes the greatest contribution to reservoir fracture development, with its content showing a positive correlation with total microfracture density, followed by plagioclase. Quartz exhibits the lowest contribution, with its content negatively correlated. (2) As granite grain size increases from 2.0 mm to 5.0 mm, uniaxial compressive strength decreases. Consequently, smaller tectonic stresses are required to initiate microfractures, facilitating the development of fractured reservoirs. However, under sufficiently large tectonic stresses, microfracture density decreases. (3) Quantification of intercrystalline fractures showed that the inclination angle between mineral orientation and the tectonic stress direction is positively correlated with the proportion of intercrystalline microfractures. Compared to massive granite, gneissic granite exhibits lower compressive strength and enhanced microfracture connectivity, which favors the development of high-quality reservoirs. These findings provide an important theoretical basis for predicting fractured reservoirs.

Key words: fractured oil and gas reservoir, rock composition and structure, numerical simulation, quantitative prediction

CLC Number:

HE Xiao, NIU Huapeng, ZHAO Xian, ZHOU Haoyan, LIN Weijun, ZHANG Guanlong, MENG Tao, MU Xing. Numerical simulation method on the impact of the difference of rock composition and structure on the development mechanism of fractured reservoirs: A case study from the granitoids in Jiyang Depression[J]. Earth Science Frontiers, 2025, 32(5): 361-376.

Figures/Tables 18

References 63

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样品编号	岩性	石英含量/%	石英粒径/mm	斜长石含量/%	斜长石粒径/mm	碱性长石含量/%	碱性长石粒径/mm	暗色矿物含量/%	暗色矿物粒径/mm
0920	花岗闪长岩	29.6	1.0~3.0	52.2	1.0~3.0	13.5	1.0~2.0	4.7	1.0~2.0
1041	花岗闪长岩	38.2	1.0~4.0	39.8	1.0~3.0	18.6	1.0~4.0	3.4	1.0左右
1717	花岗闪长岩	22.0	1.0~2.5	62.3	1.0~3.5	14.8	1.0~2.0	0.9	1.0左右
1722	二长花岗岩	25.6	1.0~4.0	28.9	1.0~3.5	43.5	1.0~5.0	2.0	1.0左右
T15	英云闪长岩	17.7	1.0左右	55.0	1.0~3.5	0.0		27.3	1.0~4.5

样品编号	岩性	石英含量/%	石英粒径/mm	斜长石含量/%	斜长石粒径/mm	碱性长石含量/%	碱性长石粒径/mm	暗色矿物含量/%	暗色矿物粒径/mm
0920	花岗闪长岩	29.6	1.0~3.0	52.2	1.0~3.0	13.5	1.0~2.0	4.7	1.0~2.0
1041	花岗闪长岩	38.2	1.0~4.0	39.8	1.0~3.0	18.6	1.0~4.0	3.4	1.0左右
1717	花岗闪长岩	22.0	1.0~2.5	62.3	1.0~3.5	14.8	1.0~2.0	0.9	1.0左右
1722	二长花岗岩	25.6	1.0~4.0	28.9	1.0~3.5	43.5	1.0~5.0	2.0	1.0左右
T15	英云闪长岩	17.7	1.0左右	55.0	1.0~3.5	0.0		27.3	1.0~4.5

矿物	有效模量/GPa	键有效模量/GPa	抗拉强度/MPa	黏聚力/MPa	摩擦角/(°)	摩擦系数	法向-切向刚度比
石英	55.0	55.0	90.0	162.0	55.0	0.5	1.41
斜长石	22.0	22.0	74.5	134.1	45.0	0.5	2.26
碱性长石	28.0	28.0	70.5	126.9	45.0	0.5	2.26
暗色矿物	16.0	16.0	47.0	84.6	37.0	0.5	2.82
晶界	29.0	29.0	54.0	97.2	53.0	0.5	2.26

矿物	有效模量/GPa	键有效模量/GPa	抗拉强度/MPa	黏聚力/MPa	摩擦角/(°)	摩擦系数	法向-切向刚度比
石英	55.0	55.0	90.0	162.0	55.0	0.5	1.41
斜长石	22.0	22.0	74.5	134.1	45.0	0.5	2.26
碱性长石	28.0	28.0	70.5	126.9	45.0	0.5	2.26
暗色矿物	16.0	16.0	47.0	84.6	37.0	0.5	2.82
晶界	29.0	29.0	54.0	97.2	53.0	0.5	2.26

模型风化系数	k
有效模量	0.75
键有效模量	0.75
抗拉强度	0.75
黏聚力	0.75
摩擦角	1
摩擦系数	1
法向-切向刚度比	1