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The accuracy of nuclear magnetic resonance (NMR) logging data inversion directly affects the reliability of reservoir evaluation. Aiming at the problem of low reliability of T2 spectrum inversion from NMR data with a low signal-to-noise ratio (SNR), a hybrid denoising method based on empirical mode decomposition-singular value decomposition (EMD-SVD) is proposed to process NMR data before inversion. This method can not only effectively extract the trend component and avoid removing the useful signal in the high frequency signal, but also adaptively select the singular value for signal reconstruction through the singular value difference spectrum, which contains the advantages of the EMD and SVD methods. Numerical simulation experiments were performed to verify the effectiveness of the EMD-SVD method. The results show that the inverted T2 spectrum with the EMD-SVD denoising method is closer to the T2 model than that with the EMD denoising method and the SVD denoising method.