Intelligent Identification and Quantitative Evaluation Method of Fluid Components from T2-T1 2D NMR Logging

Abstract

Summary T2-T1 2D nuclear magnetic resonance (NMR) logging plays an important role in fluid identification and reservoir evaluation. When the signal/noise ratio (SNR) is low, the response of the fluid component overlaps on the NMR 2D spectrum, and the fluid characteristic map obtained in the laboratory could not be directly applied to 2D NMR logging data. In this work, we proposed a T2-T1 2D NMR fluid identification and quantitative evaluation method based on blind source separation (BSS) and hierarchical clustering. This method fixes the number of fluid components of BSS as eight and utilizes a hierarchical clustering method to further process the 2D spectra obtained from BSS, so that each spectrum contains only one fluid component response. Subsequently, the fluid types are determined according to the response characteristics, and the fluid volumes are quantitatively calculated. Based on the synthetic data of T2-T1 2D NMR logging, this method was used to calculate the volumes of the fluid components, and the accuracy of the method was verified by comparing with the model and other four methods. This method was applied to 2D NMR logging data from Well Z and Well G and verified by oil test results. The results show that the relative error between the fluid volumes calculated by the proposed method and the model is smaller than other methods. The data processing results of Well Z and Well G are consistent with those of the oil test. Both synthetic data and actual logging data show that this method can provide the accurate fluid identification and quantitative evaluation results of T2-T1 2D NMR logging data.