Natural logarithm transformed EEMD instantaneous attributes of reflection data

Chih Sung Chen, Yih Jeng

    Research output: Contribution to journalArticlepeer-review

    12 Citations (Scopus)

    Abstract

    Instantaneous attributes (IAs) derived from complex trace analysis using the Hilbert transform have been applied to reflection data since the late 1970s. However, the assumption of single-valued attribute is still an issue of interest. In search of an alternative solution, we use a nonlinear adaptive method, the ensemble empirical mode decomposition (EEMD), to decompose the signal into a series of intrinsic mode functions (IMFs), and then select significant components from the IMFs extracted from the original data to compute the IAs. This process overcomes the difficulties of obtaining a mono-component, zero mean signal in deriving IAs. When processing real data, we incorporate the natural logarithmic transform (NLT) into the computation to compensate the attenuation of the reflection data. The NLT EEMD algorithm yields more reliable IMFs for IAs computation than the original empirical mode decomposition (EMD); however a relevant correction is still required to limit the unexpected fluctuations occurring on IAs computation. For this reason, a local averaging technique with end effect removal is proposed to derive more interpretable IAs. Compared with other standard methods, the proposed processing scheme derives reliable IAs showing more details of the events with significant physical meaning.

    Original languageEnglish
    Pages (from-to)53-65
    Number of pages13
    JournalJournal of Applied Geophysics
    Volume95
    DOIs
    Publication statusPublished - 2013 Jul 5

    Keywords

    • EEMD
    • EMD
    • Hilbert transform
    • Instantaneous attributes
    • Natural logarithmic transform
    • Reflection

    ASJC Scopus subject areas

    • Geophysics

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