A method of improving inversion accuracy for ultra-low signal-to-noise ratio echo train of nuclear magnetic resonance logging

Abstract

In tight reservoirs, the signal-to-noise ratio (SNR) of the echo train of nuclear magnetic resonance (NMR) logging is very low, which leads to inaccurate inversion results using the current echo train processing method. Therefore, a new processing method for improving inversion accuracy was developed, which includes four steps: echo-preferring, filtering, signal superimposition, and inversion. First, the echo-preferring method, which chooses high-quality echo trains, was studied in detail by analyzing low SNR NMR measurements. The SVD filtering method was then improved, and the echo train decomposed and filtered. Next, the echo trains of the adjacent depth points were stacked to further improve the SNR. Finally, the Butler–Reeds–Dawson (BRD) method was used to perform the inversion. Through numerical simulation experiments, the effects of echo optimization and high-efficiency filtering on inversion accuracy were studied, and the reliability of the method was verified. A case study of the gas reservoir in the Daqing oilfield shows that the porosity obtained by the new method agrees favorably with the core porosity, and the T2 distribution is also more reasonable. The new method improves inversion accuracy and is equivalent to improving the original echo train of NMR logging, which lays the foundation for the calculation of movable and bound fluid volumes in tight reservoirs.