Block compressed storage and computation in the large-scale reservoir simulation

The block compressed storage and solving methods in reservoir simulation are explored to resolve large sparse linear equations emerging in three-phase black oil model. In this paper, the active nodes are compressed firstly, and then the block main diagonal elements, nonzero block elements in lower triangular and upper triangular are separately stored into three real arrays. Owing to the coefficient matrix arising in the reservoir simulation being symmetrical, the addresses of block elements in lower triangular are deposited in three integer arrays. This block compressed storage method can save lots of memory and reduce the search frequencies of non-zero elements. On the basis of such compression storage, the block incomplete LU preconditioned generalized minimal residual method (GMRES) is adopted to solve the equations, showing that it is an effective method possessing fast convergence and good stability. Testing of black oil model example reveals that the block compressed storage and solving methods are effective in solving the large-scale reservoir simulation. Key words: reservoir simulation, black oil model, active nodes compression, block compressed storage, block ILU factorization, block generalized minimal residual metho