Shubhangi Gupta

Shubhangi Gupta, Barbara I. Wohlmuth, Rainer Helmig

We present an extrapolation-based semi-implicit multirate time stepping (MRT) scheme and a compound-fast MRT scheme for a naturally partitioned, multi-time-scale hydro-geomechanical hydrate reservoir model. We evaluate the performance of the two MRT methods compared to an iteratively coupled solution scheme and discuss their advantages and disadvantages. The performance of the two MRT methods is evaluated in terms of speed-up and accuracy by comparison to an iteratively coupled solution scheme. We observe that the extrapolation-based semi-implicit method gives a higher speed-up but is strongly dependent on the relative time scales of the latent (slow) and active (fast) components. On the other hand, the compound-fast method is more robust and less sensitive to the relative time scales, but gives lower speed up as compared to the semi-implicit method, especially when the relative time scales of the active and latent components are comparable.

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, Barbara Wohlmuth, Matthias Haeckel

Marine gas hydrate systems are characterized by highly dynamic transport-reaction processes in an essentially water-saturated porous medium that are coupled to thermodynamic phase transitions between solid gas hydrates, free gas and dissolved methane in the aqueous phase. These phase transitions are highly nonlinear and strongly coupled, and cause the mathematical model to rapidly switch the phase states and pose serious convergence issues for the classical Newton's method. One of the common methods of dealing with such phase transitions is the primary variable switching (PVS) method where the choice of the primary variables is adapted locally to the phase state **outside** the Newton loop. In order to ensure that the phase states are determined accurately, the PVS strategy requires an additional iterative loop, which can get quite expensive for highly nonlinear problems. For methane hydrate reservoir models, the PVS method shows poor convergence behaviour and often leads to extremely small time step sizes. In order to overcome this issue, we have developed a nonlinear complementary constraints method (NCP) for handling phase transitions, and implemented it within a non-smooth Newton's linearization scheme using an active-set strategy. Here, we present our numerical scheme and show its robustness through field scale applications based on the highly dynamic geological setting of the Black Sea.

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.

Shubhangi Gupta, Rainer Helmig, Barbara Wohlmuth

We present a hydro-geomechanical model for subsurface methane hydrate systems. Our model considers kinetic hydrate phase change and non-isothermal, multi-phase, multi-component flow in elastically deforming soils. The model accounts for the effects of hydrate phase change and pore pressure changes on the mechanical properties of the soil, and also for the effect of soil deformation on the fluid-solid interaction properties relevant to reaction and transport processes (e.g., permeability, capillary pressure, reaction surface area). We discuss a 'cause-effect' based decoupling strategy for the model and present our numerical discretization and solution scheme. We then identify the important model components and couplings which are most vital for a hydro-geomechanical hydrate simulator, namely, 1) dissociation kinetics, 2) hydrate phase change coupled with non-isothermal two phase two component flow, 3) two phase flow coupled with linear elasticity (poroelasticity coupling), and finally 4) hydrate phase change coupled with poroelasticity (kinetics-poroelasticity coupling) and present numerical examples where, for each example, one of the aforementioned model components/couplings is isolated. A special emphasis is laid on the kinetics-poroelasticity coupling. We also present a more complex 3D example based on a subsurface hydrate reservoir which is destabilized through depressurization using a low pressure gas well. In this example, we simulate the melting of hydrate, methane gas generation, and the resulting ground subsidence and stress build-up in the vicinity of the well.