Bayesian Quantification and Reduction of Uncertainties in 3D Geomechanical‐Numerical Models

The distance to failure of the upper crustal rock in prevalent stress field is importance better understand fault reactivation by natural and induced processes as well plan manage georeservoirs. In particular, contemporary state one key ingredients for this assessment. To provide a continuous description 3D absolute geomechanical-numerical models are used. However, magnitude data model calibration sparse incomplete thus, resulting uncertainties large. order reduce uncertainties, we incorporate additional constraints on magnitudes check plausibility different data-based states. We use formation integrity tests, borehole breakouts, drilling fractures, observations seismicity distinct seismological quiescence. This information weighted according its confidence agreement with modeled states assessed. introduced Bayesian approach estimate weights thereby identify their plausibility. A case study southern Germany shows ability from wide range small number plausible ones reject implausible significantly reduces thus lowers uncertainties.