Advances in characterization techniques of deep geothermal reservoir fracture structures by integrating microseismic and hydrological data

doi:10.13745/j.esf.sf.2025.10.3

Abstract

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

CLC Number:

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.

Figures/Tables 11

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

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

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

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

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

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].

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].

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].

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

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

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

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