Abstract
The nuclear magnetic resonance (NMR) T₂ distributions of free fluid are widely used to characterize the bulk relaxation properties of fluids. However, in the heavy crude oil of reservoirs in the western South China Sea, solid-phase impurities such as waxes, asphaltenes, and colloids result in multi-peak, broad-spectrum T₂ distributions. This complexity hinders accurate peak identification and fluid property analysis. To address this, typical crude oils from the study area were selected, and their free-fluid T₂ distributions were measured under reservoir-temperature conditions. The observed multi-peak patterns were analyzed to determine their physical and chemical origins. Based on the Gaussian distribution function, a fast Gaussian picking method is proposed to search for representative distribution peaks in crude oil in conjunction with extreme points. The non-negative least squares (NNLS) method is utilized to fit the data, and the complex T₂ distribution was decomposed into components representing different phases and viscosities. After mathematical-physical tests and demonstrations, the rapid classification of the T(2) distribution of the free-fluid state of impurity-containing viscous crude oil is realized. Applied to downhole NMR data, the method accurately captured the T₂ characteristics of such crude oils, offering a fast and reliable tool for analyzing complex bulk relaxation behaviors and fluid identification. Finally, the method's performance, influencing factors, and applicability were discussed.