A novel method for NMR data denoising based on discrete cosine transform and variable length windows

Abstract

Raw nuclear magnetic resonance (NMR) data detected exhibits a low signal-to-noise ratio (SNR). The inversion results suffer from the low SNR of echo data. It is therefore essential to denoise the data before NMR data inversion, to improve the accuracy of inverted NMR spectrum. In this paper, a denoising method was firstly proposed based on discrete cosine transform (DCT), whereby four window schemes were designed into one window, multiple non-overlapping windows of equal length, multiple overlapping windows of equal length, and variable length windows. The effectiveness of four schemes was verified and compared by numerical simulations, and it indicates that Denoising Fig. 5 with variable length windows is the optimum. Core experimental data and NMR logging data were used to verify the practicality of Denoising Fig. 5. The results indicated that Denoising Fig. 5 can be effectively used to reduce the noise of actual NMR data, and the processed NMR spectrum with Denoising Fig. 5 is more reliable. • Discrete Cosine Transform was first applied to the noise reduction of NMR echo data. • Variable Length Windows scheme can achieve the best denoising effect. • The proposed method can effectively improve the application effect of NMR logging.