Design Scheme of Proximal Adaptive Noise Cancellation in Shallow Hydrological Monitoring Using a Multichannel Nuclear Magnetic Resonance Logging Tool

Small diameter nuclear magnetic resonance (NMR) logging tools are used to detect hydrologic characteristics, soil moisture, and migration of petroleum hydrocarbon contaminants near-surface in the existing hydrologic monitoring wells. However, the majority of hydrologic monitoring wells are located in densely populated areas with high electromagnetic noise levels, seriously affecting the monitoring accuracy. Consequently, decreasing electromagnetic noise is a critical component in expanding the use of small-diameter NMR logging tools. In this study, a proximal adaptive noise cancellation (PANC) method was introduced for a small-diameter NMR tool. A simulation model is used to evaluate the performance of various ANC algorithms in different conditions. The effect of coil size and position on the PANC method was then analyzed. Subsequently, a static experiment is conducted to demonstrate the validity of the method. The results show that the PANC method achieves 55% noise energy suppression without affecting the target signal intensity and bandwidth.