  In this work, Bayesian inversion with global-local forwards models is used to
identify the parameters based on hydraulic fractures in porous media. It is
well-known that using Bayesian inversion to identify material parameters is
computationally expensive. Although each sampling may take more than one hour,
thousands of samples are required to capture the target density. Thus, instead
of using fine-scale high-fidelity simulations, we use a non-intrusive
global-local (GL) approach for the forward model. We further extend prior work
to a large deformation setting based on the Neo-Hookean strain energy function.
The resulting framework is described in detail and substantiated with some
numerical tests.
