Extract Characteristic Parameters of FID Signal Combining Autocorrelation Function with the Least Absolute Value

Abstract:

FID signal is the envelope of magnetic resonance signal, and the extraction accuracy of characteristic parameters directly influence the accuracy of the hydrogeologic parameters of the inverse interpretation. In order to improve the accuracy of characteristic parameters extraction, made simulation and study combined the autocorrelation function fitting with the least absolute value nonlinear fitting method in different SNR and different noise in this paper. The simulation results showed that, the characteristic parameters fitting error using this method was smaller than that using linear, nonlinear fitting method or the autocorrelation function with the least squares method, within 7% in lower SNR. The field measurement data and inversion results verified the method validity.

• Periodical: Applied Mechanics and Materials (Volumes 239-240)
• Pages: 1108-1112
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.239-240.1108
• Online since: December 2012
• Authors: Hui Cui Hao, Jun Lin, Bao Feng Tian, Qi Wan
• Keywords: Autocorrelation Function, FID Signal, Least Absolute Value, Magnetic Resonance Sounding

References

[1] Jun Lin, Qingming Duan and Yingji Wang. Theory and design of Magnetic Resonance Sounding instrument for groundwater detection and its applications (In Chinese). Beijing: Science Press(2010)

[2] Lubczynski M and Roy J. Hydrogeological interpretation and potential of the new magnetic resonance sounding (MRS) method, Journal of Hydrology ,pp.19-40 (2003)

DOI: 10.1016/s0022-1694(03)00170-7

[3] Anatoly Legchenko and Pierre Valla. Processing of Surface Proton Magnetic Resonance Signals Using Non-linear Fitting, Journal of Applied Geophysics 39,pp.77-83 (1998)

DOI: 10.1016/s0926-9851(98)00011-1

[4] Stephan Strehl. Development of Strategies for Improved Filtering and Fitting of SNMR-Signals. Technical University of Berlin, pp.34-37 (2006)

[5] Stephan Strehl. New strategies for filtering and fitting of MRS signals, pp.7-17 (2006)

[6] Yinli Liu, Jianliang Wang and Jing Chen. MATLAB numerical calculation case analysis (In Chinese). Beijing: Beijing Aerospace Aerospace University Press (2011)

[7] H.L.Li, Technical note: An efficient method for solving linear goal programming techniques, Computers and Operations Research, 25,pp.1137-1143(1998)

[8] T.E. Dielman, Computational algorithms for least absolute value regression, In L1:Statistic Analysis and Related Methods, eds. Y. Dodge., Elsevier Science, Amsterdam,pp.35-38(1992)

[9] Chunhao Zhu. The least absolute value and the least squares method: history and different (In Chinese). ZHISHICONGLIN, 6, (2007)

[10] Chuandong Jiang. NMR groundwater detection data processing software system design and application (In Chinese), Jilin University (2009)