摘要
岩心描述资料、地面自然伽马曲线资料与井下自然伽马曲线资料三者进行一定程度上的刻度对应后，再结合BP神经网络构建出比较合理的正演模型，此模型用于其它非取心井的自然伽马曲线预测，把预测出的具有较高分辨率并能够反映出薄互层的自然伽马曲线最后应用于测井精细解释，再结合其它测井曲线，能够分辨出厚度为0.3米或0.4米的薄储层,从而在一定程度上达到提高常规测井纵向分辨率的目的。
A reasonable forward model can be established after core data, ground and downhole spontaneous gamma curve data calibration with combination of BP neural network.It can be used to forecast the spontaneous gamma curves of non-cored wells. Then the forecasted curves that have high resolution and can reflect thin interlayers can be used in well logging interpretation. Combined with other logging curves, thin reservoir of 0.3m or 0.4m can be distinguished, which can achieve the goal of increasing axial resolution of conventional well logging to a certain degree.
出处
《国外测井技术》
2008年第1期14-16,27,共4页
World Well Logging Technology
关键词
地面自然伽马曲线
正演模型
BP神经网络
高分辨率
测井精细解释
ground spontaneous gamma curve
forward model
BP neural network
high resolution
delicate well logging interpretation
