SPE Journal
Volume 16,
Number 3,
September 2011,
pp. 582-593
Summary
Assisted history matching is now widely used to constrain reservoir models.
However, history matching is a complex inverse problem, and it is always a big
challenge to history match large fields with a large number of parameters.
In this paper, we present a new technique for the gradient-based
optimization methods to improve history matching for large fields. This new
technique is based on data partition for the gradient calculations. In history
matching, the objective function can be split into local components, and a
local component generally depends on fewer influential parameters. Based on
this decomposition, we can propose a perturbation design, which allows us to
calculate all derivatives of the objective function with only a few
perturbations. This method is particularly interesting for regional and well
level history matching, and it is also suitable to match geostatistical models
by introducing numerous local parameters. This new technique makes history
matching with a large number of parameters (large field) tractable.
© 2011. Society of Petroleum Engineers
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History
- Original manuscript received:
25 March 2010
- Meeting paper published:
14 June 2010
- Revised manuscript received:
20 July 2010
- Manuscript approved:
27 September 2010
- Published online:
4 April 2011
- Version of record:
15 September 2011
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