论述了应用专家系统和人工神经网络自动识别试井解释模型的新方法．首先应用人工智能对试井解释模型的压力导数图进行识别，建立了用专家系统构成模块式识别系统；然后应用人工神经网络实现试井解释模型识别；该系统能根据新的试井资料识别试井解释模型；最后，神经网络和专家系统相结合用于试井解释．油田实际试井数据的识别结果说明该方法是一种非常有效的识别方法，对不完全的，有噪声的试井数据也能有效地识别，识别准确率较其它方法都有较大提高 Discusses the application of expert systems and artificial neural networks to automatically identify well test interpretation of the new model. First of all, artificial intelligence is used to identify pressure derivative graphs of well testing interpretation model, and a modular identification system is constructed by using expert system. Then, artificial neural network is used to recognize well testing interpretation model. Based on the new well testing data identification test Well to explain the model; finally, the neural network and expert system are combined for well test interpretation. The identification results of the actual well test data show that the method is a very effective identification method, which can effectively identify incomplete and noisy well test data, and the recognition accuracy is greatly improved compared with other methods