Study on algorithms of low SNR inversion of T ^sub 2^ spectrum in NMR

Furkejuvvon:
Bibliográfalaš dieđut
Publikašuvnnas:Applied Geophysics vol. 8, no. 3 (Sep 2011), p. 233
Váldodahkki: Lin, Feng
Eará dahkkit: Wang, Zhu-wen, Li, Jing-ye, Zhang, Xue-ang, Jiang, Yu-long
Almmustuhtton:
Springer Nature B.V.
Fáttát:
Liŋkkat:Citation/Abstract
Full Text
Full Text - PDF
Fáddágilkorat: Lasit fáddágilkoriid
Eai fáddágilkorat, Lasit vuosttaš fáddágilkora!

MARC

LEADER 00000nab a2200000uu 4500
001 898403456
003 UK-CbPIL
022 |a 1672-7975 
022 |a 1993-0658 
024 7 |a 10.1007/s11770-011-0294-0  |2 doi 
035 |a 898403456 
045 2 |b d20110901  |b d20110930 
084 |a 109012  |2 nlm 
100 1 |a Lin, Feng 
245 1 |a Study on algorithms of low SNR inversion of T ^sub 2^ spectrum in NMR 
260 |b Springer Nature B.V.  |c Sep 2011 
513 |a Feature 
520 3 |a The method of regularization factor selection determines stability and accuracy of the regularization method. A formula of regularization factor was proposed by analyzing the relationship between the improved SVD and regularization method. The improved SVD algorithm and regularization method could adapt to low SNR. The regularization method is better than the improved SVD in the case that SNR is below 30 and the improved SVD is better than the regularization method when SNR is higher than 30. The regularization method with the regularization factor proposed in this paper can be better applied into low SNR (5<SNR) NMR logging. The numerical simulations and real NMR data process results indicated that the improved SVD algorithm and regularization method could adapt to the low signal to noise ratio and reduce the amount of computation greatly. These algorithms can be applied in NMR logging.[PUBLICATION ABSTRACT] 
653 |a Nuclear magnetic resonance--NMR 
653 |a Algorithms 
653 |a Geophysics 
653 |a Signal to noise ratio 
653 |a Environmental 
700 1 |a Wang, Zhu-wen 
700 1 |a Li, Jing-ye 
700 1 |a Zhang, Xue-ang 
700 1 |a Jiang, Yu-long 
773 0 |t Applied Geophysics  |g vol. 8, no. 3 (Sep 2011), p. 233 
786 0 |d ProQuest  |t Science Database 
856 4 1 |3 Citation/Abstract  |u https://www.proquest.com/docview/898403456/abstract/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch 
856 4 0 |3 Full Text  |u https://www.proquest.com/docview/898403456/fulltext/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch 
856 4 0 |3 Full Text - PDF  |u https://www.proquest.com/docview/898403456/fulltextPDF/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch