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A PSO-LSSVM based petroleum production model for production-injection wells system

In water flooding oilfield, petroleum production is the most crucial target for production-injection wells system. An effective, informative and accurate production prediction facilitates parameter adjustment, production optimization, fault analysis and decrease in production cost. Some effective Artificial Intelligence (AI) technologies have been widely used in various kinds of industrial fields including manufacturing, building, chemistry and medicine. In this paper, AI technologies based on least squares support vector machine (LSSVM) optimized by particle swarm optimization (PSO) are applied to model petroleum production. Finally, the proposed method is verified by using the production data from Liaohe oilfield. Empirical results show that the proposed modeling approach is more feasible and accurate than other approaches.