Application of NMR Logs in the Classification of Tight Sandstone Reservoirs
- State Key Laboratory of Petroleum Resource and Prospecting, China University of Petroleum, Beijing, China
Tight sandstone reservoirs have complicated pore structures and strong heterogeneity, so it is difficult to classify the reservoirs accurately using traditional classification methods. Nuclear magnetic resonance (NMR) transverse relaxation time (T2) distribution is closely related to the pore size distribution, thus is commonly used to characterize the reservoir pore structures. At present, empirical formula established between NMR T2 distribution and mercury injection capillary pressure curves is generally used to calculate reservoir pore structure parameters and indirectly classify reservoirs. However, mercury injection experiments are time consuming and expensive, what else, the poor universal applicability of the empirical formula leads it difficult to be widely applied in all regions. In fact, lognormal density function has been routinely used for modeling pore and grain size distribution of rocks, as well as characterizing reservoir pore-system attributes quantitatively [1] . In this report, we firstly fitted NMR T2 distribution using the bimodal lognormal distribution density function to get the six parameters, which are used for charactering the pore distribution and heterogeneity properties of reservoirs. Then we combined the calculated six parameters with the NMR porosity to classify the reservoirs based on clustering analysis. Results from both core samples analysis and NMR log data processing show that this method has a good performance in the classification of tight sandstone reservoirs.
Acknowledgements
This project was funded by the National Natural Science Foundation of China (41272163) and the National Natural Science Foundation of China-China National Petroleum Corporation Petrochemical Engineering United Fund (U1262114).
