A new peak fitting method for 1D solid-state 29Si NMR spectra based on singular spectrum analysis

Abstract

[Formula: see text]Si Nuclear Magnetic Resonance (NMR) can measure the molecular structure of silicate in oilfield reinjection water. However, noise in [Formula: see text]Si NMR spectra (NMRS) affects the determination of silicate molecular structure type. To solve this problem, a new peak fitting method (Two-step Greedy-Singular Spectrum Analysis-Gaussian Fitting Method, TSG-SSA-GFM) is proposed in this paper. This method first uses TSG to determine the embedding dimension, then uses SSA to determine the characteristic peak position. Finally, GFM is used to calculate the molar ratio of characteristic peaks. The results show that TSG can quickly determine the embedding dimension and reduce computation by at least 50% vs. the global ergodic method. The mean deviation of characteristic peak positions determined by SSA is 0.07 ppm, while Discrete Wavelet Transform (DWT) and Empirical Mode Decomposition (EMD) cannot determine characteristic peaks of [Formula: see text]Si NMRS containing overlapping peak. The average [Formula: see text]-squared of Gaussian fitting of [Formula: see text]Si NMRS is 98.4% while Lorentzian is 90.6%. Therefore, this study provides an important method for quantitative analysis of [Formula: see text]Si NMRS.