BP神经网络在辽河坳陷太古宇潜山内幕岩性识别中的应用

The applicatioin of BP neural network in lithology identification in Liaohe depression archaeozoic era inner buried hill

太古宇基岩内幕岩性复杂,岩性划分难度较大。研究中以岩心定名为基础,挖掘太古宇不同岩性测井曲线的响应特征,抽取对基岩内幕岩性敏感的密度、中子、伽玛以及光电吸收截面指数作为输入端构建BP神经网络对太古宇岩性进行识别。识别结果与岩心测试资料对比表明,BP神经网络岩性识别结论可靠。该研究丰富了太古宇基岩岩性识别方法,为太古宇内幕深化研究奠定方法基础。

The lithological characteristic is complicated and the li thologic division is fairly difficult in archaeozoic era base rock.In the research,the author found out the response feature of different lithological logging curve based on the core name,extracted base rock inside lithogical sensitive density,neutron,gamma and photoelectric absorption coefficient as input terminal to construct BP neural network to identify archaeozoic era lithology.The result comparing core test data shows BP network lithology identification is reliable.The research enrich archaeozoic era lithology method and establish a method foundation for further study.