Identification of preferential flow-paths, such as fractures, is required for various issues in geosciences. When chemicals are injected into the subsurface, monitoring the resulting structural and chemical changes remains a challenge. The ability of geophysical tomography to tackle this problem is not fully explored due to the lack of numerical methods suitable for modeling narrow structures. We explore how discrete representation of preferential flow-paths provides innovative ways to invert electrical resistivity data collected during reagent injection at a contaminated site. The data set is inverted with a scheme where a new fracture is added at every iteration. This allows identifying newly created narrow conductive structures from the field data collected before and after injection. Fracture location remains overall consistent despite using different starting points for the fracture search. A prior constraint on fracture length improves convergence. These results show the potential of discrete inversion for identifying narrow structures from electrical resistivity monitoring.

中文翻译：

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来自跨钻孔电气数据的优先路径反演


确定优先流路径，例如裂缝，对于地球科学中的各种问题都是必要的。当化学品被注入地下时，监测由此产生的结构和化学变化仍然是一项挑战。由于缺乏适用于模拟狭窄结构的数值方法，地球物理层析成像解决这个问题的能力尚未得到充分探索。我们探讨了优先流路的离散表示如何提供创新方法来反转在污染场地注入试剂期间收集的电阻率数据。数据集使用每次迭代都会添加新的断裂的方案进行反转。这允许从注射前后收集的现场数据中识别新创建的狭窄导电结构。尽管对骨折搜索使用不同的起点，但骨折位置总体上保持一致。对裂隙长度的先验约束可以提高收敛性。这些结果表明，离散反演在从电阻率监测中识别狭窄结构的潜力。