Summary
This paper describes the application of a genetic algorithm to the
development of a solvent-additive SAGD process. A review of related field
projects and key simulation studies is provided, together with a discussion of
the pros and cons of potential alkane solvents. Economics and the impact of
dynamic and ultimate retention are discussed.
A general conclusion drawn from literature is that optimal solvent
application to SAGD will likely involve time variations in both rate and
composition of the solvent. This results in an optimization problem that has a
large number of dimensions, and is nonlinear. We have found genetic algorithms,
which mimic biological evolution, have been found to be extremely effective in
addressing such problems. The general methodology of application to solvent
additives by Laricina Energy Ltd. is described.
A key product of this effort, optimized for a simple clastic reservoir, is
presented. The genetic algorithm produced an operable process, which could be
described as a new combination of preexisting concepts. The process offers
material improvements in thermal bitumen supply costs, as well as recovery
factor. Major reductions in the physical steam/oil ratio (SOR), (and therefore)
capital intensity and carbon emissions, are indicated.
© 2010. Society of Petroleum Engineers
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History
- Original manuscript received:
7 April 2009
- Meeting paper published:
17 June 2009
- Revised manuscript received:
6 July 2010
- Manuscript approved:
8 July 2010
- Published online:
1 September 2010
- Version of record:
1 September 2010
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