Self-affine and ARX-models zonation of well logging data

Yousef Shiri, Behzad Tokhmechi, Zeinab Zarei and Mohammad Koneshloo

Physica A: Statistical Mechanics and its Applications, 2012, vol. 391, issue 21, 5208-5214

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 (search for similar items in EconPapers)
Date: 2012
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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:391:y:2012:i:21:p:5208-5214

DOI: 10.1016/j.physa.2012.05.025

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