Self-affine and ARX-models zonation of well logging data
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.
Year of publication: |
2012
|
---|---|
Authors: | Shiri, Yousef ; Tokhmechi, Behzad ; Zarei, Zeinab ; Koneshloo, Mohammad |
Published in: |
Physica A: Statistical Mechanics and its Applications. - Elsevier, ISSN 0378-4371. - Vol. 391.2012, 21, p. 5208-5214
|
Publisher: |
Elsevier |
Subject: | Self-similarity | ARX models | Hurst exponent | Time series data mining | Well logging zonation |
Saved in:
Online Resource
Saved in favorites
Similar items by subject
-
Touretzky, Cara R., (2015)
-
Temporary rules of retail product sales time series based on the matrix profile
Li, Hailin, (2021)
-
Scaling properties of financial time series
Schreier, David, (2007)
- More ...