Development of oil sand reserves depend on the economic analysis of potential production scenarios. This analysis relies on careful resource evaluation and knowledge about formation properties. Nuclear Magnetic Resonance (NMR) can be used as an effective tool for obtaining information about the respective reservoir fluid saturations and properties. The advantages of NMR technique applied for analysis of fluid saturations over the conventional Dean-Stark approach is in its non-destructive and non-invasive character. In addition, it is more time efficient and thus more economic.
One-dimensional NMR analysis of spin-spin relaxation time, T2, is most frequently used for characterizing oil and gas reservoirs. Although this method is fast and characterizes the reservoir saturations in an efficient way, it becomes inaccurate when the relaxation times of oil and clay bound water are very similar. We employed a two-dimensional T1– T2 low field NMR spectroscopy technique to distinguish between the fluids with similar T2 relaxation times. To separate heavy oil and water contents in the oil sand samples using T1– T2distributions, a two-dimensional local minimum approach was developed. It was seen that the estimation of oil and water saturations using the developed local minimum approach for T1– T2 distributions was much more accurate than the estimation of fluid saturations from T2distributions only with conventional constant cut-off and one-dimensional local minimum approaches. More than 50% improvement in oil and water mass estimations was achieved with the two-dimensional T1– T2 local minimum approach over T2 approaches.
Analysis of T1– T2 distributions for oil and water samples also showed that the T1/ T2 ratio approach cannot be considered as a universal tool for separation of oil and water. The T1– T2distribution of the examined oil contained a significant peak with the T1/ T2 ratio close to one.
This work showed that the conventional approaches that used only T2 cut-off values or T1/ T2 ratios for the separation of heavy oil and water did not always work properly for all oil types. It will help improve characterization and recovery of oil in diverse kinds of formations with applications in logging tools and on-line sensors.