Abstract

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 modelling 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 dataset 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 priori constraints on fracture length improve convergence. These results show the potential of discrete inversion for identifying narrow structures from electrical resistivity monitoring.