Adaptation of the CPR Preconditioner for Efficient Solution of the Adjoint Equation (Record no. 187717)

MARC details
000 -LEADER
fixed length control field 02963nab a2200253 4500
008 - CÓDIGOS DE INFORMACIÓN DE LONGITUD FIJA - INFORMACIÓN GENERAL
Campo de control de longitud fija 260224s2013 xxu ing
041 ## - IDIOMA
Idioma Inglés
100 1# - RESPONSABLE PERSONAL
Apellido, Nombre Han, Choongyong
9 (RLIN) 40403
100 1# - RESPONSABLE PERSONAL
Apellido, Nombre Wallis, John
9 (RLIN) 53242
100 1# - RESPONSABLE PERSONAL
Apellido, Nombre Sarma, Pallav
9 (RLIN) 53243
100 1# - RESPONSABLE PERSONAL
Apellido, Nombre Li, Gary
9 (RLIN) 53244
100 1# - RESPONSABLE PERSONAL
Apellido, Nombre Schrader, Mark L.
9 (RLIN) 53245
100 1# - RESPONSABLE PERSONAL
Apellido, Nombre Chen, Wen
9 (RLIN) 41014
245 00 - TITULO
Título Adaptation of the CPR Preconditioner for Efficient Solution of the Adjoint Equation
260 ## - PUBLICACION, DISTRIBUCION, ETC
Fecha de publicación, distribución, etc. abr. 2013
270 ## - FECHA DE CARGA
Fecha de carga 28/05/2013 ; 28/05/2013
300 ## - DESCRIPCION FISICA
Otra extensión 6 p. ; 207-213
520 ## - RESUMEN, ETC
Resumen Transcripción del resumen del autor: It is well known that the adjoint approach is the most efficient approach for gradient calculation, and it can be used with gradient-based optimization techniques to solve various optimization problems, such as the production-optimization problem and the history-matching problem. The adjoint equation to be solved in the approach is a linear equation formed with the "transpose" of the Jacobian matrix from a fully implicit reservoir simulator. For a large and/or complex reservoir model, generalized preconditioners often prove impractical for solving the adjoint equation. Preconditioners specialized for reservoir simulation, such as constrained pressure residual (CPR), exploit properties of the Jacobian matrix to accelerate convergence, so they cannot be applied directly to the adjoint equation. To overcome this challenge, we have developed a new two-stage preconditioner for efficient solution of the adjoint equation by adaptation of the CPR preconditioner (named CPRA: CPR preconditioner for adjoint equation). The CPRA preconditioner has been coupled with an algebraic multigrid (AMG) linear solver and implemented in Chevron's extended applications reservoir simulator (CHEARS(R)). The AMG solver is well known for its outstanding capability to solve the pressure equation of complex reservoir models; solving the linear system with the "transpose" of the pressure matrix is one of the two stages of construction of the CPRA preconditioner. Through test cases, we have confirmed that the CPRA/AMG solver with generalized minimal residual (GMRES) acceleration solves the adjoint equation very efficiently with a reasonable number of linear-solver iterations. Adjoint simulations to calculate the gradients with the CPRA/AMG solver take approximately the same amount of time (at most) as do the corresponding CPR/AMG forward simulations. Accuracy of the solutions has also been confirmed by verifying the gradients against solutions with a direct solver. A production-optimization case study for a real field using the CPRA/AMG solver has further validated its accuracy, efficiency, and the capability to perform long-term optimization for large, complex reservoir models at low computational cost.
581 ## - ESTADO DE COLECCIÓN
Estado de colección 2
773 0# - CORRECCIÓN
Título SPE Journal
Partes relacionadas 18
942 ## - DESC. DE MATERIAL
Tipo de item KOHA Artículo de Revista
Holdings
Biblioteca propietaria Biblioteca actual Fecha de adquisición Inventario Total de préstamos Inventario Fecha de carga Tipo de item KOHA
Biblioteca Alejandro Angel Bulgheroni Biblioteca Alejandro Angel Bulgheroni 06/03/2026 200059860   200059860 06/03/2026 Artículo de Revista


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