Journal of Information Processing Systems

  • 제14권4호
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  • Pages.941-947
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  • 2018
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  • 1976-913X(pISSN)
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  • 2092-805X(eISSN)
한국정보처리학회 (Korea Information Processing Society)
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An Improved Spin Echo Train De-noising Algorithm in NMRL

  • Liu, Feng (College of Electronic and Electrical Engineering, Wuhan Textile University) ;
  • Ma, Shuangbao (College of Mechanical Engineering and Automation, Wuhan Textile University)
  • 투고 : 2018.03.30
  • 심사 : 2018.05.12
  • 발행 : 2018.08.31
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초록

Since the amplitudes of spin echo train in nuclear magnetic resonance logging (NMRL) are small and the signal to noise ratio (SNR) is also very low, this paper puts forward an improved de-noising algorithm based on wavelet transformation. The steps of this improved algorithm are designed and realized based on the characteristics of spin echo train in NMRL. To test this improved de-noising algorithm, a 32 points forward model of big porosity is build, the signal of spin echo sequence with adjustable SNR are generated by this forward model in an experiment, then the median filtering, wavelet hard threshold de-noising, wavelet soft threshold de-noising and the improved de-noising algorithm are compared to de-noising these signals, the filtering effects of these four algorithms are analyzed while the SNR and the root mean square error (RMSE) are also calculated out. The results of this experiment show that the improved de-noising algorithm can improve SNR from 10 to 27.57, which is very useful to enhance signal and de-nosing noise for spin echo train in NMRL.

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참고문헌

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