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The study of 2D NMR logging inversion method based on the maximum entropy-Bayesian theory

Two-dimensional nuclear magnetic resonance logging has a clear advantage in the aspect of reservoir fluid identification and evaluation through measuring transverse relaxation time T2 and diffusion coefficient D of formation hydrogen nuclear simultaneously. Truncated singular value decomposition and standard Tikhonov inversion method are often applied to obtain the relaxation-diffusion spectra, but both methods must make nonnegative constraints, which not only increase the amount of calculation but also make the information loss easy. This paper proposes the maximum entropy-Bayesian inversion method of two-dimensional nuclear magnetic resonance, which adds a priori information in the process of inversion, and makes all solutions nonnegative at the same time, on the basic of relaxation-diffusion model of nuclear magnetic resonance. The measurement information is acquired to the greatest extent. Through simulation and experimental verification, the relative error of the transverse relaxation time T2 and diffusion coefficient D improve from 22.65% and 28.35% to 11.26% and 6.91% respectively. This method can be applied to the two-dimensional nuclear magnetic resonance logging.