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

机译:NMR中T 2 谱的低SNR反演算法研究

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摘要

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 (5SNR) 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.
机译:正则化因子选择方法确定了正则化方法的稳定性和准确性。通过分析改进的SVD与正则化方法之间的关系,提出了正则化因子的公式。改进的SVD算法和正则化方法可以适应低信噪比。在SNR小于30的情况下,正则化方法优于改进的SVD;当SNR大于30时,改进的SVD优于正则化方法。本文提出的具有正则化因子的正则化方法可以更好地应用于低SNR(5

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