摘要
地震资料与测井资料联合反演技术用于反演地震剖面 ,得到了由测井曲线构成的剖面。文章研究基于近年来得到不断发展和应用的非线性理论中的神经网络算法 ,其目的是为了得到高分辨率、高精度的反演剖面。方法具有自适应子波调整的特点 ,克服了传统反演方法在这一方面的缺陷 ;能够反演多种测井曲线 ,比传统反演方法具有明显优势 ;可获得纵、横向上分辨率均较高、与实际资料吻合程度高的反演剖面 ,有利于储层的高精度、综合性的研究。方法在初步应用中取得了较好效果 。
By use of the joint inversion technique of seismic and log data, the seismic section can be inversed into a section constituted by logging traces. In order to obtain the inversion section with high-resolution and high-accuracy, the neural network algorithm of nonlinear theory, which has been unceasingly developed and applied in recent years, is studied in the paper. This method is of the character of adaptive wavelet adjustment, thus overcoming the defect of the traditional inversion method in such an aspect; it has obvious superiority as compared with the traditional method, being able to inverse many kinds of logs; and the inversion section with high-resolution on the vertical and horizontal and coinciding with the practical data to a considerable degree may be achieved so as to be favorable to a comprehensive research on reservoirs with high accuracy. A good result has been achieved in the primary application of such a method, thus revealing a vast range of prospects for making use of it.
出处
《天然气工业》
EI
CAS
CSCD
北大核心
2004年第3期55-57,共3页
Natural Gas Industry
关键词
地震资料
测井资料
联合反演技术
地震剖面
神经网络算法
储层预测
Algorithms
Natural gas
Neural networks
Nonlinear systems
Petroleum reservoirs
Research and development management
Seismology
Well logging
