Abstract Fracture-scale heterogeneity plays an important role in driving dispersion, mixing and heat transfer in fractured rocks. Current approaches to characterize fracture scale flow and transport processes largely rely on indirect information based on the interpretation of tracer tests. Geophysical techniques used in parallel with tracer tests can offer time-lapse images indicative of the migration of electrically-conductive tracers away from the injection location. In this study, we present a methodology to invert time-lapse ground penetrating radar reflection monitoring data acquired during a push-pull tracer test to infer fracture-scale transport patterns and aperture distribution. We do this by using a probabilistic inversion based on a Markov chain Monte Carlo algorithm. After demonstration on a synthetic dataset, we apply the new inversion method to field data. Our main findings are that the marginal distribution of local fracture apertures is well resolved and that the field site is characterized by strong flow channeling, which is consistent with interpretations of heat tracer tests in the same injection fracture.

中文翻译：

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从水文地球物理监测示踪剂测试中对裂缝尺度流动路径和孔径分布的概率推断

摘要 裂缝尺度非均质性在驱动裂缝岩石弥散、混合和传热方面起着重要作用。当前表征裂缝尺度流动和传输过程的方法主要依赖于基于示踪剂测试解释的间接信息。与示踪剂测试并行使用的地球物理技术可以提供延时图像，指示导电示踪剂远离注入位置的迁移。在这项研究中，我们提出了一种方法来反演推拉示踪剂测试期间获得的延时探地雷达反射监测数据，以推断裂缝尺度传输模式和孔径分布。我们通过使用基于马尔可夫链蒙特卡罗算法的概率反演来做到这一点。在合成数据集上演示后，我们将新的反演方法应用于现场数据。我们的主要发现是局部裂缝孔径的边缘分布得到了很好的解决，并且现场具有强烈的流道特征，这与同一注入裂缝中伴热测试的解释一致。