关键词: Elman神经网络, 遗传算法, 油田指标预测

Abstract: Based on the application of the index prediction in oil field actual development, this paper puts forward a method combining neural network and genetic algorithm build a forecasting model. Neural network using a dynamic feedback Elman network, gives full play to the advantages of its dynamic prediction, and at the same time, by the help of a genetic algorithm compensates for its slow training speed and easy to fall into the local minimum points. By improving genetic algorithm’s selection operator it not only can save fine individual but also can improve the search efficiency. This paper organically combines neural network with genetic algorithm and realizes the complementary advantages. Taking the oilfield real data for example to test and verify model, the results show that this model can achieve good prediction effect, the method is efficient and feasible.
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Key words: Elman neural network, genetic algorithm, index prediction in oil field