Abstract

A three-dimensional (3D) nuclear magnetic resonance (NMR) spectrum can simultaneously provide distributions of longitudinal relaxation time (T1), transverse relaxation time (T2), and diffusivity (D); thus, it greatly improves the capacity of fluid identification, typing, and quantitative evaluations. However, several challenges that significantly hinder the widespread application of this technique remain. The primary challenges are the high time and memory costs associated with the current 3D NMR inversion algorithms. In addition, an activation sequence optimization method for 3D NMR inversions has not been developed. In this paper, a novel inversion method for 3D NMR spectra and a detailed optimization method for activation sequences and acquisition parameters were proposed. The novel method, namely randomized singular value decomposition (RSVD) inversion algorithm, can reduce memory requirements and ensure computational efficiency and accuracy. Window averaging (WA) technique was also adopted in this study to further increase computational speed. The optimized method for pulse sequences is mainly based on projections of the 3D NMR spectra in the two-dimensional (2D) and one-dimensional (1D) domains. These projections can identify missing NMR properties of different fluids. Because of the efficiency and stability of this novel algorithm and the optimized strategy, the proposed methods presented in this paper could further promote the widespread application of 3D NMR.

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