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Title: Optimization of an enhanced oil recovery process with boundary controls: a large-scale nonlinear maximization

Thesis/Dissertation ·
OSTI ID:6913375

The theoretical and computational problem of optimally determining the injected concentration histories for a micellar/polymer flooding enhanced oil recovery system is considered so as to maximize the net profitability of the project. The state dynamics are described by a set of highly nonlinear partial differential equations with boundary control inputs. The design performance functional is defined as the difference between gross revenue and cost of chemical injected. The theoretical characterization of the optimal control policy is obtained using both a continuous and discrete variational formulation. The numerical optimum-seeking algorithm is formulated based on generating a maximizing sequence which converges to the optimal control policy. This sequence is generated by employing gradient or conjugate directions of search on the performance measure. Numerical calculations are presented to illustrate optimal policies. Specific results depend upon the physical chemistry as well as reservoir parameters. The method has been tested on the realistic core experiment used to design the Sloss field test of Amoco. Optimization studies yield optimum injection strategies which improve the core flood performance by over 21%. The optimum value of the performance measure is about 81% of the greatest attainable economic value which corresponds to complete oil recovery at no chemical cost. This work emphasizes the applicability of optimal control theory to a problem which is highly nonlinear, mathematically complex, and extensively large. The effectiveness of the approach has been established by numerical results.

Research Organization:
Colorado Univ., Boulder (USA)
OSTI ID:
6913375
Resource Relation:
Other Information: Thesis (Ph. D.)
Country of Publication:
United States
Language:
English