Quantitative predictions of natural and induced phenomena in fractured rock is one of the great challenges in the Earth and Energy Sciences with far-reaching economic and environmental impacts. Fractures occupy a very small volume of a subsurface formation but often dominate fluid flow, solute transport and mechanical deformation behavior. They play a central role in CO₂ sequestration, nuclear waste disposal, hydrogen storage, geothermal energy production, nuclear nonproliferation, and hydrocarbon extraction. These applications require predictions of fracture-dependent quantities of interest such as CO₂ leakage rate, hydrocarbon production, radionuclide plume migration, and seismicity; to be useful, these predictions must account for uncertainty inherent in subsurface systems. Here, we review recent advances in fractured rock research covering field- and laboratory-scale experimentation, numerical simulations, and uncertainty quantification. We discuss how these have greatly improved the fundamental understanding of fractures and one's ability to predict flow and transport in fractured systems. Dedicated field sites provide quantitative measurements of fracture flow that can be used to identify dominant coupled processes and to validate models. Laboratory-scale experiments fill critical knowledge gaps by providing direct observations and measurements of fracture geometry and flow under controlled conditions that cannot be obtained in the field. Physics-based simulation of flow and transport provide a bridge in understanding between controlled simple laboratory experiments and the massively complex field-scale fracture systems. Finally, we review the use of machine learning-based emulators to rapidly investigate different fracture property scenarios and accelerate physics-based models by orders of magnitude to enable uncertainty quantification and near real-time analysis.

中文翻译：

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从流体流动到裂隙岩石中的耦合过程：最新进展和新领域

对裂隙岩石中的自然现象和诱发现象进行定量预测是地球和能源科学面临的重大挑战之一，具有深远的经济和环境影响。裂缝占地下地层的很小体积，但通常主导流体流动、溶质传输和机械变形行为。_{它们在 CO 2}封存、核废料处理、氢储存、地热能生产、核不扩散和碳氢化合物提取中发挥着核心作用。这些应用需要预测与裂缝相关的感兴趣量，例如 CO ₂泄漏率、碳氢化合物产量、放射性核素羽流迁移和地震活动；为了有用，这些预测必须考虑到地下系统固有的不确定性。在这里，我们回顾了裂缝岩石研究的最新进展，包括现场和实验室规模的实验、数值模拟和不确定性量化。我们讨论了这些如何极大地提高了对裂缝的基本理解以及预测裂缝系统中流动和传输的能力。专用现场站点提供裂缝流动的定量测量，可用于识别主要耦合过程和验证模型。实验室规模的实验通过提供在现场无法获得的受控条件下的裂缝几何形状和流动的直接观察和测量来填补关键的知识空白。基于物理的流动和传输模拟为理解受控的简单实验室实验和大规模复杂的现场规模裂缝系统提供了一座桥梁。最后，我们回顾了使用基于机器学习的仿真器来快速研究不同的裂缝特性场景，并将基于物理的模型加速几个数量级，以实现不确定性量化和近实时分析。