Summary
Numerous steam-assisted gravity-drainage (SAGD) optimization studies
published in the literature combined numerical simulation with graphical or
analytical techniques for design and performance evaluation. Efforts have
integrated the simulation exercise with global optimization algorithms. Some
studies focused on optimization of cumulative steam/oil ratio (cSOR) in SAGD by
altering steam-injection rates, while others focused on optimization of net
cumulative energy/oil ratio (cEOR) in solvent-additive SAGD by altering
injection pressures and fraction of solvent in the injection stream. Several
studies also considered total project net-present-value (NPV) calculation by
changing total project area, capital-cost intensities, solvent prices, and risk
factors to determine the well spacing and drilling schedule. Optimization
techniques commonly used in those studies were scattered search, simulated
annealing, and genetic algorithm (GA). However, applications of hybrid GA were
rarely found.
In this paper, we focused on optimization of solvent-assisted SAGD using
various GA implementations. In our models, hexane was selected to be coinjected
with steam. The objective function, defined on the basis of cSOR and recovery
factor, was optimized by changing injection pressures, production pressures,
and injected solvent/steam ratio. Techniques, including orthogonal arrays (OA)
for experimental design (e.g., Taguchi's arrays) and proxy models for
objective-function (F) evaluations, were incorporated with the GA method to
improve computational and convergence efficiency. Results from these hybrid
approaches revealed that an optimized solution could be achieved with less
central-processing-unit time (e.g., fewer number of iterations) compared with
the conventional GA method. Sensitivity analysis was also conducted on the
choice of proxy model to study the robustness of the proposed methods.
To investigate the effects of heterogeneity in the design process,
optimization of solvent-assisted SAGD was performed on various synthetic
heterogeneous reservoir models of porosity, permeability, and shale
distributions. Our results highlight the potential application of the proposed
techniques in other solvent-enhanced heavy-oil-recovery processes.
© 2012. Society of Petroleum Engineers
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History
- Original manuscript received:
30 January 2012
- Meeting paper published:
16 November 2011
- Revised manuscript received:
17 May 2012
- Manuscript approved:
7 August 2012
- Published online:
1 November 2012
- Version of record:
20 November 2012
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