ALBERT

Description: The discrete element method (DEM) provides a new modeling approach for describing sea ice dynamics. It exploits particle-based methods to characterize the physical quantities of each sea ice floe along its trajectory under Lagrangian coordinates. One major challenge in applying DEM models is the heavy computational cost when the number of floes becomes large. In this paper, an efficient Lagrangian parameterization algorithm is developed, which aims at reducing the computational cost of simulating the DEM models while preserving the key features of the sea ice. The new parameterization takes advantage of a small number of artificial ice floes, called the superfloes, to effectively approximate a considerable number of the floes, where the parameterization scheme satisfies several important physics constraints. The physics constraints guarantee the superfloe parameterized system will have short-term dynamical behavior similar to that of the full system. These constraints also allow the superfloe parameterized system to accurately quantify the long-range uncertainty, especially the non-Gaussian statistical features, of the full system. In addition, the superfloe parameterization facilitates a systematic noise inflation strategy that significantly advances an ensemble-based data assimilation algorithm for recovering the unobserved ocean field underneath the sea ice. Such a new noise inflation method avoids ad hoc tunings as in many traditional algorithms and is computationally extremely efficient. Numerical experiments based on an idealized DEM model with multiscale features illustrate the success of the superfloe parameterization in quantifying the uncertainty and assimilating both the sea ice and the associated ocean field.

Description: Natural or artificial fluid flow in deep fractured reservoirs, such as Enhanced Geothermal Systems (EGS), is primarily controlled by open fractures and faults, and is considered a key element for hydraulic performance. Flow along these fractures is strongly affected by channeling between fracture asperities and by deposits sealing the open fracture space due to mineral precipitation. Fracture asperities and fracture sealing also impact the mechanical behavior of fractures, especially their mechanical stiffness. Here, we study both the permeability and the stiffness of a rough fracture at the field scale during its closure.We base our approach on a well established self-affine geometrical model for fracture roughness. We develop a finite element model based on the MOOSE/GOLEM framework and conduct numerical flow experiments in a 256 × 256 × 256 m^3 granite reservoir hosting a single, partially sealed fracture under variable normal loading conditions. Navier-Stokes flow is solved in the embedded 3-dimensional rough aperture, and Darcy flow is solved in the surrounding poroelastic matrix. We study the evolution of the mechanical stiffness and fluid permeability of the fracture-rock system during fracture closure by considering the asperity yield and the depositing of fracture-filling material in the open space of the rough fracture. The evolution of the fault volume, fracture normal stiffness and permeability are monitored until fluid percolation thresholds are exceeded in two orthogonal directions of the imposed pressure gradient. Finally, we propose a physically based law for the stiffness and permeability evolution as a function of the fault volume. It is demonstrated that during closure, stiffness increases exponentially as the fault volume decreases. A strong anisotropy of the fracture permeability is also evidenced when reaching percolation thresholds.