摘要
介绍了应用地震属性技术预测煤层厚度变化的方法.分析了钻孔处地震属性与煤厚的相关性,对地震属性进行了优选.将得到的地震属性利用多元多项式回归以及BP人工神经网络方法,求出各属性与煤厚之间的回归方程及人工神经网络回归模型.将该模型应用到非井点的地震属性上,实现了对淮南谢桥矿区13-1煤层厚度的预测,取得了较好的应用效果,证明了用地震属性技术预测煤厚是可行的.
Application of seismic attribute technology in predicting coal-bed thickness is introduced. Correlation between coal seam thickness and seismic attribute is analyzed. The BP artificial neural network regression model for seismic attribute and coal seam thickness is established, which has been applied in predicting the thickness of coal seam 13-1 in Xieqiao coal mining area. The result shows that the seismic attribute technique is feasible for predicting coal seam thickness.
出处
《中国矿业大学学报》
EI
CAS
CSCD
北大核心
2004年第5期557-562,共6页
Journal of China University of Mining & Technology
基金
教育部全国优秀博士学位论文专项基金项目(200247)
国家自然科学基金项目(40172059)
关键词
地震属性
煤层厚度
多元统计分析
BP神经网络
seismic attribute
thickness of coal seam
multivariate statistical analysis
BP neural network
