Output details
15 - General Engineering
Heriot-Watt University (joint submission with University of Edinburgh)
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Output 0 of 0 in the submission
Article title
Bayesian optimization algorithm applied to uncertainty quantification
Type
D - Journal article
Title of journal
SPE Journal
Article number
-
Volume number
17
Issue number
3
First page of article
865
ISSN of journal
1086-055X
Year of publication
2012
URL
-
Number of additional authors
5
Additional information
This paper is the first application in the oil industry of the Bayesian optimization Algorithm (BOA) to history matching reservoir models. This paper, and its companion on real field applications (DOI:10.2118/141161-PA) were funded by TSB (TP-BE056A £697k), and show that the studied algorithm outperforms evolutionary stochastic algorithms employed in history matching and uncertainty quantification on both synthetic and real cases. As a result of the performance demonstrated in this paper, the algorithm has been coded up in the commercial software Raven (www.useraven.com), with 3 licences sold to date (further details in the associated impact case study).
Interdisciplinary
Yes
Cross-referral requested
-
Research group
C - Energy & Resource Management
Proposed double-weighted
No
Double-weighted statement
-
Reserve for a double-weighted output
No
Non-English
No
English abstract
-
