A Joint Inversion Method Algorithm for T2-Pc two Dimensional NMR based on Logistic Functions

• Published in: Journal of Electrical Systems Vol. 20; no. 3; pp. 1189 - 1199
• Main Authors: Su, Jing, Liu, Caiguang, Zhang, Rong, Wang, Zhenlin, Qin, Yingyao, Zhang, Gong
• Format: Journal Article
• Language: English
• Published: Paris Engineering and Scientific Research Groups 08.05.2024
• Subjects: Algorithms; Capillary pressure; Data processing; Kernel functions; NMR; Nuclear magnetic resonance; Relaxation time; Signal to noise ratio
• ISSN: 1112-5209
• DOI: 10.52783/jes.3522

Data processing is a key step in the analysis of nuclear magnetic resonance (NMR) experimental data, and efficient and accurate computer inversion algorithms are the core of the T2-Pc two-dimensional NMR experiment. T2-Pc two-dimensional NMR experiment is an advanced experimental method that characterizes reservoir connectivity through two dimensions: relaxation time and capillary pressure, and can obtain irreducible water saturation under different pressure differences. However, the algorithm currently used for T2-Pc two-dimensional spectrum inversion uses a mutation kernel function, resulting in low accuracy of calculation results. This paper uses the Logistic function as the two-dimensional inversion kernel function, rewrites the inversion algorithm, and obtains more accurate inversion results. Numerical simulations have proven that the T2-Pc two-dimensional map obtained by this method not only has higher resolution, but also has greater applicability in the case of low signal-to-noise ratio and a small number of centrifugal echo groups. Practice has found that the proposed method can reduce the number of centrifugations during the experiment and significantly improve the efficiency of T2-Pc two-dimensional nuclear magnetic resonance experiments.