摘要
苏北盆地高邮凹陷CA油田微裂缝比较发育,但由于微裂缝发育规模、开度和延伸长度均较小而不易识别,研究方法和手段受到很大限制,研究起来难度较大。利用测井的声波曲线、微梯度曲线、微电位曲线、6 m电阻曲线和冲洗带电阻率曲线,采用神经网络的方法,建立该区裂缝分布的三维模型,从而实现对裂缝参数的预测。通过动态资料分析,证实了运用神经网络法获得的裂缝预测结果是较为可靠的。
There are many micro-fractures in the CA Oilfield in Gaoyou Sag, the North Jiangsu Basin. The aperture and extension length of these micro-fractures are too small to identify easily. The methods and means being used to study are limited. Based on the acoustic logging curve, the microinverse, the micronormal,the 6 m electric resistance curve and the resistivity curve in flushing zone, the 3D mathematical model about the distribution of the micro-fractures in this area can be established by using the method of artificial neural network. In this paper, the micro-fracture parameters were predicted by this way. The predict result was verified by the dynamic data analysis. It is reliable to predict the distribution of micro-fractures by using the mathod of artificial neural network.
出处
《石油实验地质》
CAS
CSCD
北大核心
2006年第4期395-398,共4页
Petroleum Geology & Experiment
关键词
微裂缝
三维分布模型
神经网络
高邮凹陷
苏北盆地
micro-fracture
3D distribution model
artificial neural network
the Gaoyou Sag
the NorthJiangsu Basin
