摘要
介绍了利用地震属性预测延川南三维地震勘探工区煤层厚度的方法。先将钻井处的煤层厚度与归一化后地震属性进行相关,以此为根据对地震属性进行优选。利用已知钻井的煤层厚度和相应的属性分别求出相应的线性回归模型和BP神经网络模型,然后比较多元线性回归方法和BP神经网络方法预测效果,最后将效果较好的BP神经网络模型应用到非井点的地震属性上。延川南地区2号煤层厚度的预测结果表明:地震属性可以用于煤层厚度的预测。
This paper mainly introduces the method of coalbed thickness prediction of three-dimensional (3D) seismic exploration work area in South Yanchuan block by using seismic attributes. Based on the relations between coalbed thickness of drilling locations and normalized seismic attributes, seismic attributes were selected. Afterwards, the corresponding linear regression model and BP neural network model were calculated. Compared with these two models, the BP neural network model was selected and applied to non-well point seismic attributes. The prediction results of No.2 coalbed in south Yanchuan block show that seismic attributes can be used to predict coalbed thickness.
出处
《油气藏评价与开发》
2014年第2期65-69,75,共6页
Petroleum Reservoir Evaluation and Development
关键词
地震属性
BP神经网络
煤层厚度
seismic attributes
BP neural network model
coalbed thickness