Algorithms for removing surface water signals from surface nuclear magnetic resonance infiltration surveys

Samuel Falzone, Kristina Keating

Research output: Contribution to journalArticlepeer-review

4 Scopus citations

Abstract

Surface nuclear magnetic resonance (surface NMR) is a geophysical method that directly detects water and can be used to determine the depth profile of water content within the subsurface. Although surface NMR has proven useful for investigating groundwater in the saturated zone, its use to study the vadose zone is still in development. A recent study for the South Avra Valley Storage and Recovery Project (SAVSARP) demonstrated that surface NMR can be used to monitor infiltrating water associated with aquifer storage and recovery, a water resource management method in which surface water is stored in local aquifers during wet periods for use during dry periods. However, one of the major issues associated with using surface NMR to monitor infiltrating water is the influence of large bodies of surface water. We have examined the effect that large bodies of surface water have on the surface NMR signal, and we have developed three algorithms (the a priori, late-signal, and long-signal-inversion [LSI] algorithms) to remove this signal. Using synthetic data sets, we have assessed the efficacy of each algorithm and determined that, although each algorithm is capable of suppressing the signal from a water layer with a thickness ≤ 5 m, the LSI algorithm provides the most accurate and consistent results. Using a field example from the SAVSARP survey, we have evaluated the use of the LSI algorithm to suppress the surface water signal. Our results have indicated that the signal from surface water detected in a surface NMR survey can be suppressed to obtain the subsurface water content without the use of new measurement techniques or additional equipment.

Original languageEnglish (US)
Pages (from-to)WB97-WB107
JournalGEOPHYSICS
Volume81
Issue number4
DOIs
StatePublished - Jul 1 2016

All Science Journal Classification (ASJC) codes

  • Geochemistry and Petrology

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