Harmonic Noise-Elimination Method Based on the Synchroextracting Transform for Magnetic-Resonance Sounding Data

Magnetic-resonance sounding (MRS) is a direct, quantitative, accurate, and efficient technology that has been applied in the fields of groundwater detection, regional water-resource investigation, and geological-disaster-risk early warning. However, owing to strong environmental noise, the signal-to-noise ratio (SNR) of data collected by MRS instruments is low; thus, providing reliable results for subsequent hydrological interpretation is difficult. To solve this issue, we propose a method based on the synchroextracting transform (SET) to eliminate harmonic noise from MRS data in an environment with strong noise. Compared with the harmonic modeling cancellation (HMC) and three existing data processing algorithms, the SET can effectively eliminate the harmonic noise in a single record and process multiple types of harmonic noise in stacked data at a time. The calculation amount and time are much lower than those of the HMC algorithm, and the calculation accuracy is similar to that of the HMC algorithm. More importantly, after the harmonics are eliminated by the SET method, the impact on the free induced decay (FID) signal is small, whereas the other three methods severely distort the FID signal. Considering that FID signals may exhibit the characteristics of multiexponential decay and that its Larmor frequency is close to a certain harmonic frequency, we study the applicable scope of the SET. Finally, by processing the results of field-measured data, the validity and practicability of SET are further verified. We also discuss the advantages of the SET method and existing problems to provide future research directions.

Automated summary

Magnetic-resonance sounding (MRS) is widely used in hydrogeological applications, but faces challenges due to environmental noise. The synchroextracting transform (SET) method proposed in this study effectively eliminates harmonic noise, improving data quality and processing efficiency.