Christian Deusner

Mario Teixeira Parente, Steven Mattis, Shubhangi Gupta et al.

Methane gas hydrates have increasingly become a topic of interest because of their potential as a future energy resource. There are significant economical and environmental risks associated with extraction from hydrate reservoirs, so a variety of multiphysics models have been developed to analyze prospective risks and benefits. These models generally have a large number of empirical parameters which are not known a priori. Traditional optimization-based parameter estimation frameworks may be ill-posed or computationally prohibitive. Bayesian inference methods have increasingly been found effective for estimating parameters in complex geophysical systems. These methods often are not viable in cases of computationally expensive models and high-dimensional parameter spaces. Recently, methods have been developed to effectively reduce the dimension of Bayesian inverse problems by identifying low-dimensional structures that are most informed by data. Active subspaces is one of the most generally applicable methods of performing this dimension reduction. In this paper, Bayesian inference of the parameters of a state-of-the-art mathematical model for methane hydrates based on experimental data from a triaxial compression test with gas hydrate-bearing sand is performed in an efficient way by utilizing active subspaces. Active subspaces are used to identify low-dimensional structure in the parameter space which is exploited by generating a cheap regression-based surrogate model and implementing a modified Markov chain Monte Carlo algorithm. Posterior densities having means that match the experimental data are approximated in a computationally efficient way.

Shubhangi Gupta, Christian Deusner, Matthias Haeckel et al.

Natural gas hydrates are considered a potential resource for gas production on industrial scales. Gas hydrates contribute to the strength and stiffness of the hydrate-bearing sediments. During gas production, the geomechanical stability of the sediment is compromised. Due to the potential geotechnical risks and process management issues, the mechanical behavior of the gas hydrate-bearing sediments needs to be carefully considered. In this study, we describe a coupling concept that simplifies the mathematical description of the complex interactions occuring during gas production by isolating the effects of sediment deformation and hydrate phase changes. Central to this coupling concept is the assumption that the soil grains form the load-bearing solid skeleton, while the gas hydrate enhances the mechanical properties of this skeleton. We focus on testing this coupling concept in capturing the overall impact of geomechanics on gas production behavior though numerical simulation of a high-pressure isotropic compression experiment combined with methane hydrate formation and dissociation. We consider a linear-elastic stress-strain relationship because it is uniquely defined and easy to calibrate. Since, in reality, the geomechanical response of the hydrate bearing sediment is typically inelastic and is characterized by a significant shear-volumetric coupling, we control the experiment very carefully in order to keep the sample deformations small and well within the assumptions of poro-elasticity. The closely co-ordinated experimental and numerical procedures enable us to validate the proposed simplified geomechanics-to-flow coupling, and set an important precursor towards enhancing our coupled hydro-geomechanical hydrate reservoir simulator with more suitable elasto-plastic constitutive models.