Preferential Pathways Inversion From Cross‐Borehole Electrical Data.

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. Plain Language Summary: In some geoscience activities, such as water extraction, geological storage, and contaminant fate, chemical solutions are injected into wells, which potentially leads to modify the system properties. Identifying preferential flow‐paths is therefore necessary even though monitoring structural and chemical changes in the subsurface remains a challenge. Electrical geophysical imaging techniques may be adapted to provide information for this purpose. However, their potential is not fully explored due to the limitations of numerical models to represent small‐scale structures. In this work, we explore the representation of preferential flow‐paths by discrete elements for the inversion of electrical resistivity data collected during a reagent injection at a contaminated site. The inversion scheme based on discrete forward simulations successively identifies small‐scale structures and focuses on evaluating their localization and length. The results show the need for further efforts to use discrete electrical resistivity inversion in the presence of narrow structures. Key Points: Standard modeling strategies are not well suited to identify narrow geological structures from cross‐borehole electrical data inversionInversion scheme based on discrete‐dual‐porosity forward simulations enable to image narrow preferential flow‐paths from electrical dataPrior assumptions are needed to invert the position and length of narrow preferential flow‐paths [ABSTRACT FROM AUTHOR]