摘要
本文简单介绍了智能信息处理中新出现的RoughSet(RS)理论及属性选择方法,从双相介质地震波传播理论角度,探讨了地震数据油气预测属性优化原理,提出了基于RS理论的地震数据油气预测属性优化方法。实际应用表明;本方法速度快、易实现,而且在优选属性、最大程度地减少提取地震属性种数、提高分类正确率等方面,明显优于其它方法。本方法将成为地震数据油气预测的一种有效手段。
In the paper we briefly introduce the Rough Set (RS) theory, which is a new theory in intelligent information processing, and the attribllte selection method. From the angle of seismic wave propagation theory in two-phase media, we rnake an approach to the attribute optimization principle in oil and gas prediction with seismic data and put forward an attribute optimization method on the basis of the RS theory. The application result indicates that the rnethod is fast in speed and can be realized easily. Moreover, the method is superior to other methods in selecting the attribute, decreasing the number of seismic attributes to be extracted, and improving the classification correctness. It can become an effective means for oil and gas prediction with seismic data.
出处
《石油物探》
EI
CSCD
北大核心
1998年第4期32-40,共9页
Geophysical Prospecting For Petroleum
基金
国家自然科学基金
湖北省自然科学基金
关键词
属性优化
地震数据
油气勘探
储集层
油气预测
attribute optimization, oil and gas prediction, seismic reservoir prediction, artificial neural network, pattern recognition