摘要
在新兴的信息处理技术中，灰色系统预测法和神经网络预测法都可用来解决精细测井解释和油藏描述中的模式识别和参数预测等问题。基于灰色ＧＭ（０，Ｎ）静态模型和ＢＰ神经网络模型，提出了一种新的参数估算方法即灰色神经网络判释法，由此分析了利用测井资料预测地层破裂压力的可行性。以Ｈ盆地中部气田为实例，综合应用现场试采测压资料和测井资料，建立了该气田石盒子组马家沟组地层破裂压力的灰色ＢＰ神经网络预测模型，成功地处理了该区２５口气井（油井）资料。结果表明，该法简便好用，预测精度高，为应用测井资料预测地破裂层压力开拓了一条新的途径。
Of the mew information processing techniques, both grey mode and artificial neural network mode can be used to solve the problems of pattern-recognition and parameter calculation in fine log interpretation and reservoir description. On the basis of GM(U,N)mode and BPANN mode, this paper introduces an improved method (GMUNBPANN)to estimate parameter, and then analyzes the feasibibity of formation fracture pressure prediction by using well logging data. Taking the central gas field in H basin as an example, we have built a special grey BPANN mode to calculate the rock fracture pressure of Ahihezi andd Majiagou formation by making full use of test data and log information, and applied it successfully to 25 oil-gas wells. The result shows that this method is easy, practical and can make an accurate prediction,thus providing a new approach for the prediction of formation fracture pressure from well logging curves.
出处
《西南石油学院学报》
CSCD
1996年第4期1-8,共8页
Journal of Southwest Petroleum Institute
