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Direct numerical simulations (DNS) are used to study non constant density reacting turbulent Couette flow. The objectives are to understand the interaction of wall turbulence and premixed flames, to study wall heat flux from the flame, and to identify mechanisms and correlations that can help in model development for engineering calculations. A variety of turbulent mechanisms were found to increase the wall heat flux. It was found that turbulent boundary layer sweeps, which are normally the main mechanism in turbulent production, push the flame toward the wall and increase wall heat flux. At the same time, a quadrant analysis of the Reynolds stresses shows that they switch from their normal second and fourth quadrants to first and third quadrants. Since the flame is sensitive to stretch for nonadiabatic flow near a wall, low speed streaks decrease the stretch on the flame and increase the wall heat flux. High-speed streaks increase flame stretch and decrease wall heat flux. Streamwise vortex structures convect the flame toward the wall increasing the wall heat flux. Studying the instantaneous wall heat flux shows peak values approximately 1.25 times the laminar value. These repeat on a time scale of $3.2 outer time units (based on mean velocity and channel half width). Larger

Giant reservoirs of the Middle East are crucial for the supply of oil and gas to the world market. Proper simulation of these giant reservoirs with long history and large amount of static and dynamic data requires efficient parallel simulation technologies, powerful visualization and data processing capabilities. This paper describes GigaPOWERS, a new parallel reservoir simulator capable of simulating hundreds of millions of cells to a billion cells with long production history in practical times. The new simulator uses unstructured grids. A distributed unstructured grid infrastructure has been developed for models using unstructured or complex structured grids. Unconventional wells such as maximum reservoir contact wells and fish-bone wells, as well as faults and fractures are handled by the new gridding system. A new parallel linear solver has been developed to solve the resulting linear system of equations. Load balancing issues are also discussed. A unified compositional formulation has been implemented. The simulator is designed to handle n-porosity systems. An optimization-based well management system has been developed by using mixed integer nonlinear programming. In addition to the core computational algorithms, the paper will present the pre- and post-processing software system to handle large amount of data. Visualization techniques for billions of cells are also presented. Introduction For many oil and gas reservoirs, especially large reservoirs in the Middle East, availability of vast amount of seismic, geological and dynamic reservoir data result in high-resolution geological models. But despite the many benefits of parallel simulation technology for large reservoirs, average cell size still remains in the order of hundreds of meters for large reservoirs. In order to fully utilize the seismic data, smaller grid blocks such as 25 to 50 meters in length are required. This size of grid blocks results in billion (Giga) cell models for giant reservoirs. In order to simulate such models with reasonable turnaround time, new innovations in the main components of the simulator such as linear equation solvers and equation of state computations are essential. Also, next generation pre- and post-processing tools are needed in order to build and analyze giga-cell models in practical times.

The solution of the linear system of equations for a large scale reservoir simulation has several challenges. Preconditioners are used to speed up the convergence rate of the solution of such systems. In theory, a preconditioner defines a matrix M that can be inexpensively inverted and represents a good approximation of a given matrix A. In this work, two-stage preconditioners consisting of the approximated inverses M 1 and M 2 are investigated for multiphase flow in porous media. The first-stage preconditioner, M 1 , is approximated from A using four different solution methods: (1) constrained pressure residuals (CPR), (2) lower block Gauss-Seidel, (3) upper block Gauss-Seidel, and (4) one iteration of block Gauss-Seidel. The pressure block solution in each of these different schemes is calculated using the Algebraic Multi Grid (AMG) method. The inverse of the saturation (or more generally, the nonpressure) blocks are approximated using Line Successive Over Relaxation (LSOR). The second stage preconditioner, M 2 , is a global preconditioner based on LSOR iterations for the matrix A, that captures part of the original interaction of different coefficient blocks. Several techniques are also employed to weaken the coupling between the pressure block and the nonpressure blocks. Effective decoupling is achieved by: (1) an Implicit Pressure Explicit Saturation (IMPES) like approach designed to preserve the integrity of pressure coefficients, (2) Householder transformations, (3) the alternate block factorization (ABF), and (4) the BDS based on least squares. The fourth method is a new technique developed in this work. The aforementioned preconditioning techniques were implemented in a parallel reservoir simulation environment, and tested for large-scale two-phase and three-phase black oil simulation models. This study demonstrates that a two-stage preconditioner based on BDS or ABF combined with Gauss-Seidel sweeps, that also incorporate nonpressure solutions for M, delivers both the fastest convergence rate and the most robust option overall without compromising parallel scalability.

TX 75083-3836, U.S.A., fax 01-972-952-9435. AbstractModeling Middle East giant carbonate reservoirs with fractures and super-k conductivity present unique challenges to conventional simulation approaches. Fractures in these giant oil fields can exist as fracture swamp neighboring fault zones. These regional/local fractures can interact with Super-K layers (high permeability stratiform) which form extremely high conductivity to fluid flow. Typically, meaningful simulation for such an oil field requires the use of millions of grid cells involving thousands of wells. These reservoirs are not the classical dual porosity where matrix permeability is poor and does not form a part of the global flow path. Dual porosity dual permeability (DPDP) formulation allowing a flexible regional representation of both single porosity and dual porosity behavior on a cell by cell basis is more suitable.A parallel dual porosity dual permeability simulator has been developed to efficiently solve multi-million grid cell fractured reservoirs problems with super-k fracture permeability. To be effective, the simulator has to engage tens to hundreds of processors in a highly scalable manner. This paper discusses the formulation, the data design and solution procedures involved in this development.The parallelization paradigm is the mixed approach with MPI (Message Passing Interface) and OpenMP (Open Message Passing). These parallelization approaches are open standards supported by most major hardware vendors. This allows for easy portability among various hardware architectures. However, the data design and solution methods discussed herein are amenable to MPI only or other parallelization approaches as well. The mixed paradigm approach is flexible and allows various combination and permutation of MPI processes and OpenMP threads to be used to solve a problem.Results are presented for a multi-million cell fractured reservoir simulation with super-k involving thousands of wells and over 60 years of history match. We present simulation results, computational efficiency and parallel scalability on the IBM Nighthawk II, as well as on the PC Xeon Linux cluster hardware.