Predicting <i>T</i>₂ Cutoffs from NMR Logging Based on Multifractal Theory: A Case Study of a Shale Reservoir in the Songliao Basin, China

The Songliao Basin’s unconventional reservoirs are rich in shale oil and gas but exhibit complex pore structures and strong heterogeneity, complicating accurate field evaluations. NMR technology, which provides detailed reservoir and fluid information, has become a popular evaluation method. The T2 cutoff (T2C) value is a key parameter in NMR applications, and its accuracy is critical for precise evaluations. Based on multifractal theory, the NMR T2 spectra of saturated fluids were analyzed, revealing that the NMR T2 distribution of saturated fluid samples exhibits multifractal characteristics. A method for predicting the T2C value using multifractal theory was established, and corrections were made to both core T2C values and well logging data T2C values. A well logging NMR T2C value model based on core experiments was proposed. This model can accurately predict the T2C value at corresponding depths. The research outcomes are of significant importance for enhancing the accuracy of reservoir evaluations using field NMR logging.