Evaluation of Fluid Saturation in Shale Using 2D Nuclear Magnetic Resonance

Two-dimensional (2D) nuclear magnetic resonance (NMR) has become an indispensable tool for fluid saturation evaluation in shale reservoir. NMR spectrum derived from echo data with a low signal-to-noise ratio, however, cannot be effectively used for fluid feature extraction and saturation calculation. In this study, we proposed a fluid saturation evaluation method that combines morphology, nonnegative matrix decomposition, and fully constrained least squares. Moreover, an Akaike information criterion (AIC)-based method was proposed to determine the number of fluid types. A shale formation data set with varying fluid saturation was processed to validate the effectiveness of the proposed method. The results show that the proposed method can efficiently and accurately obtain the NMR T1–T2 feature and saturation of different fluid types and has advantages over the comparable method in both computational efficiency and accuracy. Furthermore, the impact of the structure size was investigated, demonstrating that the proposed method is very fault tolerant.