РЕШЕНИЕ ОПТИМИЗАЦИОННЫХ ЗАДАЧ ОПТИМАЛЬНОГО УПРАВЛЕНИЯ ЭКСПЛУАТАЦИОННЫМИ ПАРАМЕТРАМИ НЕФТЯНОГО ПЛАСТА

Abstract

The article proposes a method for solving optimization problems of oil reservoir operational parameters optimal control: placement of injection and production wells; regulation of wells in the formulation of non-stationary two-phase filtration. Depending on the planning horizon, optimization of the regimes based on the proposed method provides a forecast of an increase in production from 27 % for long-term planning to 60 % for short-term planning. It was found out that for optimal control problems for the modes of using the oil reservoir instead of the equations of state in the form of a system of ordinary differential equations, it is necessary to take partial differential equations. The complexity of the solution greatly increases with the dimension of the problem: a two-dimensional stationary, two-dimensional non-stationary, two-dimensional two-phase non-stationary, three-dimensional multi-phase non-stationary settings. Real for the solution are two-dimensional non-stationary multi-phase filtration models. In the work, the results of optimization calculations were obtained, which reveal that the definition of the problem of rational deployment and correction of well operation in the formulation of non-stationary two-phase filtration significantly increases the performance of the oil reservoir. It is not a matter of principle to determine other criteria for optimality and additional constraints. It was found that the problem of three-phase filtering in two-dimensional and quasi-three-dimensional settings is achievable. As a result of a genetic algorithm used in practice with combined coding of crossover operators and dominance operators for selection, a method for determining the problem of rational management of oil reservoir operational parameters is presented: deployment of injection and production wells; correction of well operation in the formulation of non-stationary two-phase filtration. Depending on the planning period, the optimization of the regimes gives a forecast of an increase in production from 27 % to 60 %.