Stability Assessment of CO2 Geological Storage Based on a Fracture Network Model
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摘要: 裂缝作为CO2地质封存的主要储集空间和渗流通道，直接影响CO2的封存效率及长期封存的安全性.基于无人机倾斜摄影技术，构建了鄂尔多斯盆地裂缝性砂岩储层离散裂缝网络模型，并基于多物理场耦合仿真软件COMSOL Multiphysics建立了考虑基质‒层理‒裂缝的CO2-水两相流固耦合数值模型.研究发现，CO2优先沿高渗透性的层理和裂缝运移，横向层理与低倾角、低连通性的自然裂缝阻滞垂向渗流，降低了CO2逃逸到盖层的风险；裂缝网络加速了压力传递，诱发显著位移响应，初始位移增长率是基质模型的6.2倍.因此，考虑基质‒层理‒裂缝多重介质系统对CO2地质封存的稳定性具有重要意义.Abstract: Fractures serve as the primary storage space and seepage pathways for CO2 geological storage, directly influencing storage efficiency and long-term containment security. This study employed UAV oblique photogrammetry to construct a discrete fracture network (DFN) model of a fractured sandstone reservoir within the Ordos Basin. Subsequently, a fluid-solid coupling numerical model for CO2-water two-phase flow was established using the multiphysics simulation software COMSOL Multiphysics, explicitly accounting for the matrix-bedding-fracture system. Key findings reveal that CO2 preferentially migrates along high-permeability bedding planes and fractures. Horizontal bedding, combined with low-dip, low-connectivity natural fractures, impedes vertical seepage, thereby reducing the risk of CO2 escape into the caprock. The fracture network accelerates pressure transmission, inducing significant displacement responses. The initial rate of displacement increase was found to be 6.2 times higher than that observed in the matrix model. Consequently, accurately representing the multi-porosity system encompassing the matrix, bedding, and fractures is crucial for assessing the stability of CO2 geological storage.
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图 1 (a) 鄂尔多斯盆地高程图；(b)鄂尔多斯盆地延长组柱状图
Fig. 1. (a) Elevation map of Ordos Basin; (b) strata characteristics of Chang 7 Member in Ordos Basin
图 2 基于无人机摄影测量技术的延长组砂岩露头裂缝测绘
Fig. 2. Fracture mapping from a sandstone outcrop of Yangchang Formation using unmanned aerial vehicle photogrammetry
图 5 （a）地质剖面图；（b）天然裂隙迹线空间分布（红色线段表示裂隙，蓝色线段表示层理）
Fig. 5. (a) Geological section; (b) spatial distribution of natural fracture traces with red segments representing joints and blue segments indicating bedding planes
图 6 天然裂缝上半球等面积投影图（a）和天然裂隙迹长分布（b）
Fig. 6. Upper hemisphere and equal area projection of the mapped joints (a) and distribution of joint trace length (b)
图 8 模型上边界CO2饱和度验证
Fig. 8. Verification of the CO2 saturation profiles of the present model
图 10 不同时间下三种地质模型的CO2饱和度分布
Fig. 10. CO2 saturation distribution in three geological models at different times
图 11 关井25 d后三种地质模型沿剖面深度的CO2饱和度分布
Fig. 11. CO2 saturation distribution along depth profile in three geological models after 25-day shut-in period
图 12 关井25 d后三种地质模型的表面压力
Fig. 12. Distribution of top surface pressure in three geological models after 25-day shut-in period
图 13 关井25 d后三种地质模型沿剖面深度的CO2压力
Fig. 13. Distribution of CO2 pressure along depth profile in three geological models after 25-day shut-in period
图 14 不同地质条件下注入口压力随时间演化规律
Fig. 14. Temporal evolution of wellbore pressure at injection point under three geological configurations
图 15 不同地质条件下垂向位移沿剖面深度的时间演化规律
Fig. 15. Temporal evolution of vertical displacement along depth profile under three geological configurations
图 16 三种地质模型中储盖层系统CO2体积分数时间演化规律
Fig. 16. Spatiotemporal evolution of CO2 volume fraction in reservoir-caprock systems under three geological configurations
图 17 不同地质条件下盖层CO2累计逃逸比
Fig. 17. Cumulative CO2 leakage rates through caprock under three geological configurations
表 1 模型计算参数
Table 1. Computational parameters
参数 取值 参数物理意义 取值来源 rin 0.447 5×10‒6 m/s 注入速率 Pavan et al. (2024) ρw 1 093 kg/m3 盐水密度 Nordbotten et al. (2005) ρv 723 kg/m3 CO2密度 Nordbotten et al. (2005) μw 8.485×10‒4 Pa·S 盐水粘度 Nordbotten et al. (2005) φv 0.594×10‒4 Pa·S CO2粘度 Nordbotten et al. (2005) Srw 0.2 残余盐水饱和度 Srn 0 残余CO2饱和度 T0 348.15 K 储层温度 Wang et al. (2025) P0 22 MPa 初始地层压力 Wang et al. (2025) Pec 1.9 MPa 入口毛细压力 m 0.5 本构关系常数 PL 5 MPa Langmuir吸附压力 Sun et al. (2020) VL 0.005 m3/ kg Langmuir吸附体积 Sun et al. (2020) φr 0.102 5 砂岩初始孔隙率 杜书恒等(2019) φc 0.025 8 页岩初始孔隙率 白莹等(2022) kr 2×10‒16 m2 砂岩初始渗透率 杜书恒等(2019) kc 1×10‒17 m2 页岩初始渗透率 白莹等(2022) kb 2×10‒15 m2 层理渗透率 df 0.1 mm 裂缝开度 付金华等(2020) Er 27.71 GPa 砂岩杨氏模量 Wang et al. (2025) vr 0.241 砂岩泊松比 Wang et al. (2025) ρr 2 600 kg/m3 砂岩密度 Wang et al. (2025) Ec 22 GPa 页岩杨氏模量 李帅等(2020) vc 0.25 页岩泊松比 李帅等(2020) ρc 2 650 kg/m3 页岩密度 李帅等(2020) α 0.8 Bito系数 
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