Extracting microphysical fault friction parameters from laboratory and field injection experiments

Human subsurface activities induce significant hazard by (re-)activating slip on faults, which are ubiquitous in geological reservoirs. Laboratory and field (decametric-scale) fluid injection experiments provide insights into the response of faults subjected to fluid pressure perturbations, but assessing the long-term stability of fault slip remains challenging. Numerical models offer means to investigate a range of fluid injection scenarios and fault zone complexities and require frictional parameters (and their uncertainties) constrained by experiments as an input. In this contribution, we propose a robust approach to extract relevant microphysical parameters that govern the deformation behaviour of laboratory samples. We apply this Bayesian approach to the fluid injection experiment of Cappa et al. (2019) and examine the uncertainties and trade-offs between parameters. We then continue to analyse the field injection experiment reported by Cappa et al. (2019), from which we conclude that the fault-normal displacement is much larger than expected from the adopted microphysical model (the Chen–Niemeijer–Spiers model), indicating that fault structure and poro-elastic effects dominate the observed signal. This demonstrates the importance of using a microphysical model with physically meaningful constitutive parameters, as it clearly delineates scenarios where additional mechanisms need to be considered.