Automatic History Matching with Variable-Metric Methods

  • Yang P
  • Watson A
  • 12


    Mendeley users who have this article in their library.
  • 43


    Citations of this article.


The use of variable-metric (or quasi-Newton) methods with optimal
control theory is an attractive method for automatic history matching.
Optimal control theory provides for an efficient calculation of the
gradient of the performance index, and variable-metric methods are
the most efficient and accurate of the minimization methods that
require only the evaluation of the performance index and its gradient.
In addition, variable-metric methods can be used effectively with
parameter inequality constraints. Four variable-metric methods--
the BFGS method, Fletcher's switch algorithm, a self-scaling variable-metric
method, and an optimally conditioned self-scaling variable-metric
methodare tested with hypothetical single-phase reservoir history
matching problems. All four methods yield significantly more accurate
estimates with less computer effort than a previous history matching
algorithm which uses the steepest decent method. A constrained BFGS
algorithm is further tested with hypothetical waterfloods of one-
and two-dimensional reservoir models.

Get free article suggestions today

Mendeley saves you time finding and organizing research

Sign up here
Already have an account ?Sign in

Find this document

Get full text


  • Pin-Huel Yang

  • A Ted Watson

Cite this document

Choose a citation style from the tabs below

Save time finding and organizing research with Mendeley

Sign up for free