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Comparison of Preconditioners for the Conjugate Gradient Method in Reservoir Simulation

Brian Francis Towler, John Edwin Killough

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Abstract

ABSTRACT Five methods of partial decomposition are compared as preconditioners for the conjugate gradient method for solving the pressure matrix equation of a sequential mode reservoir simulator. Three unsymmetric decompositions, Strongly Implicit Procedure; Dupont, Kendall, Rachford method; and Additional Bands (AB) proved effective and comparable, with AB being the most efficient when used on a scalar computer. The two symmetric Incomplete Cholesky methods did not prove as effective as the three unsymmetric methods. On the CRAY-1 computer, the SIP-conjugate gradient method was most efficient because it could be vectorized, and in comparison to Red-Black LSOR it was far superior for the example problem considered here. The insensitivity of the SIP-conjugate gradient method to the iteration parameter was an additional advantage of the method.

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ABSTRACT Five methods of partial decomposition are compared as preconditioners for the conjugate gradient method for solving the pressure matrix equation of a sequential mode reservoir simulator. Three unsymmetric decompositions, Strongly Implicit Procedure; Dupont, Kendall, Rachford method; and Additional Bands (AB) proved effective and comparable, with AB being the most efficient when used on a scalar computer. The two symmetric Incomplete Cholesky methods did not prove as effective as the three unsymmetric methods. On the CRAY-1 computer, the SIP-conjugate gradient method was most efficient because it could be vectorized, and in comparison to Red-Black LSOR it was far superior for the example problem considered here. The insensitivity of the SIP-conjugate gradient method to the iteration parameter was an additional advantage of the method.

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Available abstract

ABSTRACT Five methods of partial decomposition are compared as preconditioners for the conjugate gradient method for solving the pressure matrix equation of a sequential mode reservoir simulator. Three unsymmetric decompositions, Strongly Implicit Procedure; Dupont, Kendall, Rachford method; and Additional Bands (AB) proved effective and comparable, with AB being the most efficient when used on a scalar computer. The two symmetric Incomplete Cholesky methods did not prove as effective as the three unsymmetric methods. On the CRAY-1 computer, the SIP-conjugate gradient method was most efficient because it could be vectorized, and in comparison to Red-Black LSOR it was far superior for the example problem considered here. The insensitivity of the SIP-conjugate gradient method to the iteration parameter was an additional advantage of the method.

Key concepts: Cholesky decomposition, Conjugate gradient method, Derivation of the conjugate gradient method, Conjugate, Computer science, Applied mathematics, Conjugate residual method, Nonlinear conjugate gradient method

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