Multi-criteria optimization model for thermal recovery processes.

Abstract

In the Loco field case study, the steam drive enhances the heavy oil recovery by decreasing the oil viscosity and increasing the injectivity; therefore, a quicker return of investment is predicted. However, the in-situ combustion has a higher thermal efficiency and the steam injection adds a high cost which makes the steam drive undesirable for the Pauls Valley Field.

The thermal process screening guide, a pilot test, or a reservoir simulation model are applied to evaluate the thermal processes. However, the evaluation is unrealistic if problems arise. Hence, a new evaluation method is necessary.

The Marx and Lagenheim solution and the oil recovery/volume burned method are used as the basic formulations to develop the performance model for steam drive and in-situ combustion processes. One hundred reservoir cases have been evaluated by the performance model for the thermal processes. (Petroleum Data System is used for reservoir data validation.) The trends of thermal processes can be generalized into regression equations which will be used as the objective functions. Priorities can be set for the objective functions to determine their achievements. A multi-criteria programming technique is applied. Both the optimal designs as well as optimized profit are obtained.