• KSII Transactions on Internet and Information Systems
    Monthly Online Journal (eISSN: 1976-7277)

Improved Correlation Identification of Subsurface Using All Phase FFT Algorithm

Vol. 14, No. 2, February 29, 2020
10.3837/tiis.2020.02.002, Download Paper (Free):

Abstract

The correlation identification of the subsurface is a novel electrical prospecting method which could suppress stochastic noise. This method is increasingly being utilized by geophysicists. It achieves the frequency response of the underground media through division of the cross spectrum of the input & output signal and the auto spectrum of the input signal. This is subject to the spectral leakage when the cross spectrum and the auto spectrum are computed from cross correlation and autocorrelation function by Discrete Fourier Transformation (DFT, “To obtain an accurate frequency response of the earth system, we propose an improved correlation identification method which uses all phase Fast Fourier Transform (APFFT) to acquire the cross spectrum and the auto spectrum. Simulation and engineering application results show that compared to existing correlation identification algorithm the new approach demonstrates more precise frequency response, especially the phase response of the system under identification


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Cite this article

[IEEE Style]
Q. Zhang, K. Hao, M. Li, "Improved Correlation Identification of Subsurface Using All Phase FFT Algorithm," KSII Transactions on Internet and Information Systems, vol. 14, no. 2, pp. 495-513, 2020. DOI: 10.3837/tiis.2020.02.002.

[ACM Style]
Qiaodan Zhang, Kaixue Hao, and Mei Li. 2020. Improved Correlation Identification of Subsurface Using All Phase FFT Algorithm. KSII Transactions on Internet and Information Systems, 14, 2, (2020), 495-513. DOI: 10.3837/tiis.2020.02.002.

[BibTeX Style]
@article{tiis:23261, title="Improved Correlation Identification of Subsurface Using All Phase FFT Algorithm", author="Qiaodan Zhang and Kaixue Hao and Mei Li and ", journal="KSII Transactions on Internet and Information Systems", DOI={10.3837/tiis.2020.02.002}, volume={14}, number={2}, year="2020", month={February}, pages={495-513}}