Calculating derivatives for automatic history matching |
| |
Authors: | José Roberto P Rodrigues |
| |
Institution: | 1. PETROBRAS/CENPES/PDP/TR, Cidade Universitária, QD. 7, Ilha do Fund?o, Rio de Janeiro, RJ, 21941-598, Brazil
|
| |
Abstract: | Automatic history matching is based on minimizing an objective function that quantifies the mismatch between observed and
simulated data. When using gradient-based methods for solving this optimization problem, a key point for the overall procedure
is how the simulator delivers the necessary derivative information. In this paper, forward and adjoint methods for derivative
calculation are discussed. Procedures for sensitivity matrix building, sensitivity matrix and transpose sensitivity matrix
vector products are fully described. To show the usefulness of the derivative calculation algorithms, a new variant of the
gradzone analysis, which tries to address the problem of selecting the most relevant parameters for a history matching, is
proposed using the singular value decomposition of the sensitivity matrix. Application to a simple synthetic case shows that
this procedure can reveal important information about the nature of the history-matching problem. |
| |
Keywords: | automatic history matching derivative calculation parameter identification problem gradzone analysis adjoint method truncated singular value decomposition Lanczos method |
本文献已被 SpringerLink 等数据库收录! |
|