Skip to main content

Wavelet Application in Classification of Strata

  • Conference paper
Computational Intelligence and Intelligent Systems (ISICA 2012)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 316))

Included in the following conference series:

  • 2206 Accesses

Abstract

Geophysical survey needs logging data to speculate stratum situation. The classification of strata based on logging curve is the first thing for the inversion problem. Electric logging curve is a stochastic time series. Because of the complex strata structure, the time series consist of real signal and white Gaussian noise. In order to get the real logging curves, the noise should be removed. In this paper, wavelet is used to filter the electric logging curves and the filtered signal properly reserves the curve edge and effectively wipes off the mutations of noise. The classification of strata based on the wavelet pre-treatment of electric logging curve becomes more ideal than the original curve.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Zou, C., Yang, X., Pan, L., Zhu, J., Li, Y.: A new technique for denoising log curve on the basis of wavelet transform. J. Geophysical and Geochemical Exploration 23, 462–466 (1999)

    Google Scholar 

  2. Zhao, J.-J., Hu, W.-W., Gu, X.-G., Yang, P.: The Application in the Fault of High Voltage Electric Power Measurement System Based on Wavelet Analysis with the Improved Threshold Algorithm. In: 2011 3rd International Workshop on Intelligent Systems and Applications (ISA), pp. 342–345. IEEE Conference Publications, Kaifeng (2011)

    Google Scholar 

  3. Yang, H., Zhang, D., Huang, W., Gao, Z., Yang, X., Li, C., Wang, J.: Application and Evaluation of Wavelet-Based Denoising Method in Hyperspectral Imagery Data. In: Li, D., Chen, Y. (eds.) CCTA 2011, Part II. IFIP AICT, vol. 369, pp. 461–469. Springer, Heidelberg (2012)

    Google Scholar 

  4. Mallat, S.: A Wavelet Tour of Signal Processing, 3rd edn. Academic Press, Burlington (2008)

    Google Scholar 

  5. Mallat, S., Hwang, W.: Singularity detection and processing with wavelets. J. IEEE Trans. Inform. Theory 38, 617–643 (1992)

    Article  MATH  MathSciNet  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2012 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Dun, Y., Kong, Y., Zhang, W. (2012). Wavelet Application in Classification of Strata. In: Li, Z., Li, X., Liu, Y., Cai, Z. (eds) Computational Intelligence and Intelligent Systems. ISICA 2012. Communications in Computer and Information Science, vol 316. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-34289-9_54

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-34289-9_54

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-34288-2

  • Online ISBN: 978-3-642-34289-9

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics