融合微地震与水文数据的深部地热储层裂隙结构表征技术研究进展

doi:10.13745/j.esf.sf.2025.10.3

摘要/Abstract

摘要：

针对数据不完备条件下的岩体人工裂隙准确表征的挑战,结合深部地热储层裂隙表征情境,建立了融合微地震和水文数据的裂隙结构表征技术,显著提升裂隙表征可靠性和准确性,成为人工裂隙表征的新途径。本文综述融合微地震和水文数据的裂隙结构表征技术,包括等效连续介质假设下微地震和水文数据顺序反演、联合反演,以及离散裂隙介质假设下微地震和水文数据顺序反演理论与方法,结合工程尺度案例,对比分析不同方法的优势和劣势,评述技术发展所面临的挑战并总结未来发展趋势,以期建立更加完善的融合微地震和水文数据的裂隙结构表征技术体系,提升岩体裂隙刻画精度,为裂隙影响下的地质工程风险预测和管控提供支撑。

关键词: 人工裂隙, 微地震, 示踪试验, 参数反演, 水文地球物理

Abstract:

To achieve high-resolution characterization of the induced fracture network, we developed a methodology for fracture network characterization by fusing microseismic and hydraulic data, taking into account the realistic conditions of enhanced geothermal systems. Synthetic tests and field applications demonstrated that the method significantly enhanced the robustness and accuracy of fracture characterization. This study reviews the development of the method, including the sequential and joint inversion of microseismic and hydraulic data for permeability estimation in equivalent continuous media, and the sequential inversion for explicit fracture imaging in discrete fracture networks. We compare and analyze the advantages and disadvantages of these different approaches. Finally, we summarize the remaining challenges and outline directions for future research, aiming to establish a more advanced methodology for high-resolution fracture characterization and risk mitigation in subsurface engineering.

Key words: induce fractures, microseismic events, tracer test, parameter inversion, hydrogeophysics

中图分类号:

许天福, 李思源, 姜振蛟. 融合微地震与水文数据的深部地热储层裂隙结构表征技术研究进展[J]. 地学前缘, 2026, 33(1): 269-282.

XU Tianfu, LI Siyuan, JIANG Zhenjiao. Advances in characterization techniques of deep geothermal reservoir fracture structures by integrating microseismic and hydrological data[J]. Earth Science Frontiers, 2026, 33(1): 269-282.

图/表 11

图1 融合微地震与水文数据的低渗透储层改造或地下施工激发的人工裂隙网络表征技术示意图

Fig.1 Schematic diagram of the characterization method for artificial fracture networks generated by low-permeability reservoir stimulation or underground engineering activities, integrating microseismic and hydrological data

图2 基于等效连续介质模型和离散裂隙介质模型的微地震与水文数据联合反演算法体系

Fig.2 Joint inversion algorithm for microseismic and hydrological data based on the equivalent continuous medium model and the discrete fracture network model

图3 基于Autoencoder的参数降维算法示意图(据文献[32]修改)

Fig.3 Schematic diagram of the parameter dimensionality reduction algorithm based on Autoencoder. Modified after [32].

表1 融合微地震与水文数据的裂隙结构表征方法的优势和劣势汇总表

Table 1 The advantages and disadvantages of different fracture network characterization methods integrating microseismic and hydrological data

主要方法		优势	劣势
等效连续介质	参数降维条件下的水文数据反演	井周渗透率估值精度高;计算效率高	远井渗透率约束能力差,渗透率过度平滑
	微地震与水文数据顺序反演	渗透率估值精度的空间差异小;计算效率高	精度受微地震定位误差影响大;原生裂隙发育或基质渗透性强的地层不适用
	微地震与水文数据联合反演	渗透率估值的精度高、稳定性强	计算效率低
离散裂隙介质	参数降维条件下的水文数据反演	目前尚未应用	三维裂隙结构降维处理方法尚不完善
	微地震与水文数据顺序反演	三维裂隙网络几何结构精细刻画;计算效率高	在强渗透基质条件下的应用效果尚未验证;受微地震定位误差的影响大
	微地震与水文数据联合反演	目前尚未应用	裂隙介质水-热-力学耦合模型计算效率低;微地震事件正向预测精度差

图4 不同方法反演渗透率后对示踪剂浓度突破曲线的预测效果(据文献[44]修改)

Fig.4 Prediction of tracer concentration breakthrough curves using permeability values inferred from different inversion methods. Modified after [44].

图5 (a)真实渗透率、(b)参数降维后水文数据反演、(c)微地震与水文数据顺序反演、(d)微地震与水文数据联合反演获得渗透率切片对比 (据文献[44]修改)

Fig.5 Comparison between the actual permeability (a) and the permeability distributions inferred from (b) hydrological data inversion following parameter dimensionality reduction, (c) the joint inversion of microseismic and hydrological data, and (d) the coupled inversion of microseismic and hydrological data. Modified after [44].

图6 微地震与水文数据顺序反演裂隙结构收敛后的示踪剂浓度拟合效果(据文献[45]修改)

Fig.6 The effect of tracer concentration fit after the convergence of the fracture network through sequential inversion of microseismic and hydrological data. Modified after [45].

图7 (a)基于微地震数据和(b)微地震与水文数据顺序反演的三维裂隙网络结构和概率分布图(据文献[45]修改)

Fig.7 Three-dimensional fracture network and spatial distribution of fracture probability based on (a) microseismic data, and (b) sequential inversion of microseismic and hydrological data. Modified after [45].

图8 基于示踪剂浓度突破曲线的裂隙降维模型构建示意图(据文献[49]修改)

Fig.8 Schematic diagram of the fracture parameter dimensionality reduction model based on tracer breakthrough curves. Modified after [49].

图9 全耦合(a)和基于参考点温度(b)的裂隙与基质热量交换过程计算示意图

Fig.9 Schematic diagrams illustrating the calculation of the heat exchange between fractures and the rock matrix using (a) the fully-coupled method and (b) the reference temperature-based method

图10 离散裂隙模型与图结构模型之间对比图(据文献[54]修改)

Fig.10 Comparison chart between the discrete fracture network model and the graph neural network model. Modified after [54].

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