首页 | 本学科首页   官方微博 | 高级检索  
     


Self-affine and ARX-models zonation of well logging data
Authors:Yousef Shiri  Behzad Tokhmechi  Zeinab Zarei  Mohammad Koneshloo
Affiliation:Shahrood University of Technology, School of Mining, Petroleum and Geophysics, Shahrood, Iran
Abstract:Zonation of time series into models which their parameters are piecewise constant are important and well-studied problems. Geophysical well logging data often show a complex pattern due to their multifractal nature. In a multifractal system, any pieces of it are established by a distinct exponent that can characterize them. This feature has the capability to cluster them. Self-affine zonation by Auto Regressive model with exogenous inputs (ARX) is a new approach which places well logging segments in the clusters which are more self-affine against the other clusters. This approach was performed and compared with a conventional ARX zonation in the well logging data of three different oilfields in southern parts of Iran. The results showed a good accuracy for detecting homogeneous lithological segments and led to a precise interpretation process to update the reservoir architecture.
Keywords:Self-similarity   ARX models   Hurst exponent   Time series data mining   Well logging zonation
本文献已被 ScienceDirect 等数据库收录!
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号