Nonlinear analysis of natural folds using wavelet transforms and recurrence plots.

Philos Trans A Math Phys Eng Sci

Centre for Exploration Targeting, School of Earth Sciences, University of Western Australia, 35 Stirling Highway, Crawley, Western Australia 6009, Australia.

Published: August 2018

AI Article Synopsis

  • This study uses three-dimensional models created by photogrammetry to analyze natural geological fold systems and understand how they form.
  • The research quantifies these folds by applying concepts from nonlinear dynamical systems, specifically focusing on their multifractal geometry and recurrence quantification.
  • Results suggest that the analyzed natural folds exhibit characteristics of periodic signals combined with chaotic elements, aligning with nonlinear dynamics theories.

Article Abstract

Three-dimensional models of natural geological fold systems established by photogrammetry are quantified in order to constrain the processes responsible for their formation. The folds are treated as nonlinear dynamical systems and the quantification is based on the two features that characterize such systems, namely their multifractal geometry and recurrence quantification. The multifractal spectrum is established using wavelet transforms and the wavelet transform modulus maxima method, the generalized fractal or Renyi dimensions and the Hurst exponents for longitudinal and orthogonal sections of the folds. Recurrence is established through recurrence quantification analysis (RQA). We not only examine natural folds but also compare their signals with synthetic signals comprising periodic patterns with superimposed noise, and quasi-periodic and chaotic signals. These results indicate that the natural fold systems analysed resemble periodic signals with superimposed chaotic signals consistent with the nonlinear dynamical theory of folding. Prediction based on nonlinear dynamics, in this case through RQA, takes into account the full mechanics of the formation of the geological system.This article is part of the theme issue 'Redundancy rules: the continuous wavelet transform comes of age'.

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Source
http://dx.doi.org/10.1098/rsta.2017.0257DOI Listing

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