ISSN 1000-3665 CN 11-2202/P

    地下水地球物理研究进展

    Research progress on groundwater geophysics

    • 摘要: 地下水地球物理是水文地质学与地球物理学交叉形成的重要学科方向,在地下水系统结构识别、水文参数反演及动态监测中发挥着关键作用。结合电阻率法、地震法、电磁法、探地雷达及核磁共振等技术,概述了地下水地球物理主要的探测方法、应用进展及发展方向。这些技术各具适用尺度与灵敏度,多方法联合监测与岩石物理建模是实现定量解释的核心。当前,研究已从单一方法的结构识别拓展至多方法联合约束下的动态监测与过程量化,注重建立地球物理参数与含水层参数间的岩石物理联系,推动对地层非均质性、流体运移及多场耦合机制的深入理解。复杂地表环境下的高分辨率探测、时移监测的数据一致性与反演多解性仍是主要挑战,突破这些瓶颈需发展信号增强技术、岩石物理普适模型及多场联合反演框架,实现从定性解释向定量刻画的跃升。未来应重点发展高精度探测装备、岩石物理定量模型、时移监测技术、联合反演框架及人工智能融合方法。

       

      Abstract: Groundwater geophysics is a crucial interdisciplinary field connecting hydrogeology and geophysics, playing a pivotal role in aquifer structure identification, hydrological parameter inversion, and dynamic process monitoring. This paper reviews its primary methods, application advancements, and development directions based on techniques such as resistivity, seismic, electromagnetic, ground-penetrating radar, and nuclear magnetic resonance. These technologies each possess typical scales and sensitivities, with multi-method joint monitoring and petrophysics modeling serving as the core for quantitative interpretation. Current research has expanded from single-method structural identification to dynamic monitoring and process quantification under joint constraints, emphasizing the establishment of petrophysics relationship between geophysical and aquifer parameters to deepen understanding of aquifer heterogeneity, fluid transport, and multi-field coupling mechanisms. High-resolution detection in complex surface environments, data consistency in time-lapse monitoring, and non-uniqueness remain major challenges. Overcoming these bottlenecks requires advancements in signal enhancement technologies, better petrophysics models, and multi-field joint inversion frameworks to achieve a leap from qualitative interpretation to quantitative characterization. Future efforts should prioritize the development of high-resolution detection equipment, quantitative petrophysics models, time-lapse monitoring technologies, joint inversion frameworks, and AI-integrated methods.

       

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