TY - JOUR

T1 - Signal Processing Steady-State Surface NMR Data

AU - Liu, Lichao

AU - Grombacher, Denys

AU - Griffiths, Matthew

AU - Vang, Mathias

AU - Larsen, Jakob Juul

N1 - Publisher Copyright: © 1963-2012 IEEE.

PY - 2023/4

Y1 - 2023/4

N2 - Surface nuclear magnetic resonance (NMR) is a unique technique to study groundwater, as it provides direct insights into water content and pore-scale properties. However, surface NMR suffers from an extremely weak signal that limits mapping speeds and can prohibit measurements in high ambient noise environments. It has recently been demonstrated that steady-state sequences can deliver orders of magnitude signal-to-noise ratio (S/N) enhancement in comparison with standard methods. Most notably, the steady-state approach collapses the surface NMR signal into an extremely narrow frequency band, which leads to vastly improved noise rejection. In this article, we develop the signal processing chain for steady-state surface NMR data. Each step in the signal processing chain, transient culling, pulse windowing, de-spiking, powerline harmonics subtraction, and spectral analysis are explained in detail. We demonstrate how error estimation can be efficiently performed using the power spectral density in the vicinity of the transmitting frequency. We also demonstrate how off-resonance excitation can be determined by locating the peak spectrum of surface NMR signal with an array of phase-corrected discrete Fourier transforms (DFTs). The presented signal processing methods can be easily implemented and applied to extract signal features for quality control and inversion procedures. We give a field example where data collected with steady-state pulse sequences are processed and inverted.

AB - Surface nuclear magnetic resonance (NMR) is a unique technique to study groundwater, as it provides direct insights into water content and pore-scale properties. However, surface NMR suffers from an extremely weak signal that limits mapping speeds and can prohibit measurements in high ambient noise environments. It has recently been demonstrated that steady-state sequences can deliver orders of magnitude signal-to-noise ratio (S/N) enhancement in comparison with standard methods. Most notably, the steady-state approach collapses the surface NMR signal into an extremely narrow frequency band, which leads to vastly improved noise rejection. In this article, we develop the signal processing chain for steady-state surface NMR data. Each step in the signal processing chain, transient culling, pulse windowing, de-spiking, powerline harmonics subtraction, and spectral analysis are explained in detail. We demonstrate how error estimation can be efficiently performed using the power spectral density in the vicinity of the transmitting frequency. We also demonstrate how off-resonance excitation can be determined by locating the peak spectrum of surface NMR signal with an array of phase-corrected discrete Fourier transforms (DFTs). The presented signal processing methods can be easily implemented and applied to extract signal features for quality control and inversion procedures. We give a field example where data collected with steady-state pulse sequences are processed and inverted.

KW - Digital signal processing

KW - hydrogeophysics

KW - measurement

KW - steady state

KW - surface nuclear magnetic resonance (NMR)

UR - http://www.scopus.com/inward/record.url?scp=85153337827&partnerID=8YFLogxK

U2 - 10.1109/TIM.2023.3264033

DO - 10.1109/TIM.2023.3264033

M3 - Journal article

AN - SCOPUS:85153337827

VL - 72

JO - IEEE Transactions on Instrumentation and Measurement

JF - IEEE Transactions on Instrumentation and Measurement

SN - 0018-9456

M1 - 6502313

ER -