基于神经网络的热采注汽锅炉蒸汽干度预测

In order to deal with the problems of steam-injection boiler predicting steam quality in shengli oil field, by analyzing the predicting principle of steam quality and investigating the internal relations of steam quality、specific enthalpy、pressure and temperature, and a new way which predicts steam quality by neural network basis on BP algorithm is proposed. The local data from shengli oil field are used for validation. The results show that the steam quality is predicted by BP neural network in the outlet of steam-injiection boiler, which obtained the higher prediction precision, it accords with local requirements.