基于神经网络的非地震综合评价
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摘要
利用神经网络,运用化探、地电及遥感资料,对镰刀弯地区进行了含油性的非地震综合评价,取得了很好的效果。在此基础上进一步分析训练结果,对参评因子的重要性进行优选,并对不同参数类型的评价效果进行了对比,对因子的优化具有指导意义。
With the neural network method, this paper used geochemical exploration and geoelectric as well as remote sensing data to evaluate hydrocarbon-bearing characteristics of Liandaowan area, with satisfactory result obtained. The trained result was further analyzed, and thus important factors were selected. The evaluation effects based on different types of factors were compared. The results are of guiding significance in factor optimization.
引文
[1] 刘天佑,师学明,侯连喜,等.综合运用模式识别方法评价塔北雅克拉地区圈闭的含油气性[J].石油地球物理勘探,1997,19(4).
    [2] 李孝安,张晓缋.神经网络与神经计算机导论[M].西安:西北工业大学出版社,1995.
    [3] PandyaAS,MacyRB.神经网络模式识别及其实现[M].徐勇,荆涛译.北京:电子工业出版社,1999.

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