A SELF-ORGANIZING NERVE-TREE MODEL OF VARIOUS SEIMIC INFORMATION FOR HYDROCARBON PREDICTION
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摘要: 本文提出油气预测的自组织神经树模型,并选取一组标样作为研究对象,预测成功率达100%,结果表明,该方法性能良好,可望成为利用地震信息预测油气的一种有效辅助手段。Abstract: A self-organizing nerve tree model for hydrocarbon standard prediction was presented and a group of training samples were selected as study objective in the paper, in which the successful rate for prediction is 100%. Could be with high quantity, the model therefore could be a potential for hydrocarbon predition on seismic information.
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[1] 高如曾等.预测油气富集的数理统计法.石油地球物理勘探,1984,(4) [2] 张运陶等.利用微机实现Fuzzy综合评判.石油地球物理勘探,1986,(3) [3] R. Hecht-Nilsen. Theory of the Backpropagation Neural Network. Int. J. Conf. on Neural Network, Washington D.C. June, 1989 [4] T. Li, L. Fang and K. Q. Li. Hierarchical classification and vector quantization with neural network treca. Neurcomputing,1893,5(2-3) [5] 尹红风,戴汝南.模式识别与人工智能,1990,3(1),1 [6] 肖辞源等.综合多种地震信息预测油气富集区的模糊数学方法.石油地球物理勘探,1990,(2) -
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