TY - JOUR

T1 - An alternative approach to handling co-frequency harmonics in surface nuclear magnetic resonance data

AU - Wang, Qi

AU - Jiang, Chuandong

AU - Müller-Petke, Mike

N1 - Funding information: We would like to acknowledge all of the people who contributed to the field data used in this paper. This work was supported by the Natural Science Foundation of China (41604083 and 41704103) and the International Postdoctoral Exchange Fellowship Program (20160057).

PY - 2018/12/1

Y1 - 2018/12/1

N2 - Surface nuclear magnetic resonance (SNMR) data typically suffer from very low signal-tonoise ratio. Two of the main sources of noise that generate low signal-to-noise ratios are powerlines and railways that create harmonic noise. Some noise cancellation strategies for mitigating this harmonic noise have been presented. However, when the frequency of one source of harmonics is close to the SNMR (Larmor) frequency value and thus when cofrequency harmonics are present, either the SNMR signal is significantly affected or harmonic noise cannot be effectively cancelled. Recently, a new approach to handling the issue of co-frequency harmonics that utilizes additional reference loops has been presented. In this paper, we propose an alternative approach to the elimination of co-frequency harmonics that involves using a processing-based, data-driven fitting method to avoid using additional reference loops.We investigate the accuracy and stability of the proposed fitting-based method and compare our results to those of other processing approaches using synthetic data. We find that the fitting-based approach to preserving the SNMR signal is superior to all other processing-based algorithms while effectively cancelling co-frequency harmonics. We apply the proposed fitting method to field data and demonstrate that even two different noise sources, both generating co-frequency harmonics, can be handled. Finally, an efficient approach to determine the fundamental frequency of harmonics that allows acceleration of the processing of large volumes of data is given.

AB - Surface nuclear magnetic resonance (SNMR) data typically suffer from very low signal-tonoise ratio. Two of the main sources of noise that generate low signal-to-noise ratios are powerlines and railways that create harmonic noise. Some noise cancellation strategies for mitigating this harmonic noise have been presented. However, when the frequency of one source of harmonics is close to the SNMR (Larmor) frequency value and thus when cofrequency harmonics are present, either the SNMR signal is significantly affected or harmonic noise cannot be effectively cancelled. Recently, a new approach to handling the issue of co-frequency harmonics that utilizes additional reference loops has been presented. In this paper, we propose an alternative approach to the elimination of co-frequency harmonics that involves using a processing-based, data-driven fitting method to avoid using additional reference loops.We investigate the accuracy and stability of the proposed fitting-based method and compare our results to those of other processing approaches using synthetic data. We find that the fitting-based approach to preserving the SNMR signal is superior to all other processing-based algorithms while effectively cancelling co-frequency harmonics. We apply the proposed fitting method to field data and demonstrate that even two different noise sources, both generating co-frequency harmonics, can be handled. Finally, an efficient approach to determine the fundamental frequency of harmonics that allows acceleration of the processing of large volumes of data is given.

KW - Fourier analysis

KW - Hydrogeophysics

KW - Numerical modelling

KW - Time series analysis

UR - http://www.scopus.com/inward/record.url?scp=85055706776&partnerID=8YFLogxK

U2 - 10.1093/gji/ggy389

DO - 10.1093/gji/ggy389

M3 - Article

AN - SCOPUS:85055706776

VL - 215

SP - 1962

EP - 1973

JO - Geophysical journal international

JF - Geophysical journal international

SN - 0956-540X

IS - 3

ER -