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本文应用多项式自组织方法，以１０个特征参数建立了中部气田马五１段储层气、水、干层判识的非线性网络模型，９２个已知样本的吻合率达９８．９％，为储层识别探索了又一新的方法，可供矿场参考
In this paper, a polynomial self-organizing method was used to establish a nonlinear network model for gas, water and dry layer identification of Ma5-1 reservoir in Central Gas Field with 10 characteristic parameters. The coincidence rate of 92 known samples was 98.9% A new method has been explored for reservoir identification for mine reference