Springer Science and Business Media LLC

Numerical simulation based on fine-scale reservoir models helps petroleum engineers in understanding fluid flow in porous media and achieving higher recovery ratio. Fine-scale models give rise to large-scale linear systems, and thus require effective solvers for solving these linear systems to finish simulation in reasonable turn-around time. In this paper, we study convergence, robustness, and efficiency of a class of multi-stage preconditioners accelerated by Krylov subspace methods for solving Jacobian systems from a fully implicit discretization. We compare components of these preconditioners, including decoupling and sub-problem solvers, for fine-scale reservoir simulation. Several benchmark and real-world problems, including a ten-million-cell reservoir problem, were simulated on a desktop computer. Numerical tests show that the combination of the alternating block factorization method and multi-stage subspace correction preconditioner gives a robust and memory-efficient solver for fine-scale reservoir simulation.

The hydrocarbon migration can be described by a coupled set of partial differential equations describing the dynamics of the temperature, component flow, pressure and velocity. A sequential solution procedure where the component flow is solved explicitly, gives severe restrictions on the time step given by the CFL condition. In this paper an implicit solution procedure is given and results from numerical tests are presented. The results are compared with the explicit solutions. As expected the implicit algorithm allows for substantially larger time steps.

The basis of mapped finite element methods are reference elements where the components of a local finite element are defined. The local finite element on an arbitrary mesh cell will be given by a map from the reference mesh cell. This paper describes some concepts of the implementation of mapped finite element methods. From the definition of mapped finite elements, only local degrees of freedom are available. These local degrees of freedom have to be assigned to the global degrees of freedom which define the finite element space. We will present an algorithm which computes this assignment. The second part of the paper shows examples of algorithms which are implemented with the help of mapped finite elements. In particular, we explain how the evaluation of integrals and the transfer between arbitrary finite element spaces can be implemented easily and computed efficiently.

This paper discusses the effects that partitioning has on the convergence rate of Domain Decomposition. When Finite Elements are employed to solve a second order elliptic partial differential equation with strong convection and/or anisotropic diffusion, the shape and alignment of a partition’s parts significantly affect the Domain Decomposition convergence rate. Given a PDE, if b is the direction of convection or the prominent direction of anisotropic diffusion, then if one considers traversing the domain in the direction of b, partitions having fewer parts to traverse in this direction converge faster while partitions having more converge slower.

In this paper we will present an algorithm to perform free surface flow simulations with the lattice Boltzmann method on adaptive grids. This reduces the required computational time by more than a factor of three for simulations with large volumes of fluid. To achieve this, the simulation of large fluid regions is performed with coarser grid resolutions. We have developed a set of rules to dynamically adapt the coarse regions to the movement of the free surface, while ensuring the consistency of all grids. Furthermore, the free surface treatment is combined with a Smagorinsky turbulence model and a technique for adaptive time steps to ensure stable simulations. The method is validated by comparing the position of the free surface with an uncoarsened simulation. It yields speedup factors of up to 3.85 for a simulation with a resolution of 4803 cells and three coarser grid levels, and thus enables efficient and stable simulations of free surface flows, e.g. for highly detailed physically based animations of fluids.

“PostDock”, a new visualization tool for the analysis and comparison of molecular docking results is described. It processes a docking results database and displays an interactive pseudo-3D snapshot of multiple ligand docking poses such that their docking energies and docking poses are visually encoded for rapid assessment. The docking energies are represented by a transparency scale whereas the docking poses are encoded by a color scale. The applications of PostDock for ligand–protein docking and for a novel molecular design approach termed “reverse-docking” are presented.

We investigate numerically a mathematical model of a consolidation process of a dense, flocculated suspension. The suspension is treated as a two-constituent mixture of a fluid and solid particles by an Eulerian two-phase fluid model. We characterize the suspension by constitutive relations concerning the stresses, interaction forces and inter-particle forces. A numerical solver for a two dimensional test case is developed using finite difference methods both in time and space. In the numerical experiments, the suspension is confined to a closed box and consolidates due to a constant gravity field directed toward the bottom. To study the effect of shear, 2D simulations are performed where the bottom wall of the box is moving with a constant speed.