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Comparison of NMR-Derived Hydraulic Conductivity with Various Hydraulic Testing Methods.

Chenxi Wang, Colby M Steelman¹, Zeren Ning¹

¹Department of Earth and Environmental Sciences, University of Waterloo, Waterloo, ON, N2L 3G1, Canada.

|September 8, 2025

Summary

Borehole nuclear magnetic resonance (NMR) logging reliably estimates hydraulic conductivity (K) in heterogeneous glaciofluvial deposits. The Kozeny-Godefroy model showed optimal performance, offering valuable insights for hydrogeological assessments.

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Area of Science:

Geophysics
Hydrogeology
Petrophysics

Background:

Borehole nuclear magnetic resonance (NMR) is a valuable tool for estimating hydraulic conductivity (K) in unconsolidated materials.
Existing petrophysical models require optimization of site-specific constants for accurate K prediction.
Highly heterogeneous glaciofluvial deposits present challenges for traditional hydraulic conductivity assessment.

Purpose of the Study:

To assess the utility of NMR logs for estimating hydraulic conductivity (K) in heterogeneous glaciofluvial deposits.
To compare NMR-derived K estimates with measurements from multiple hydraulic testing methods.
To evaluate the performance of four different NMR petrophysical models (SDR, Seevers, SOE, KGM).

Main Methods:

Applied four NMR petrophysical models (SDR, Seevers, SOE, KGM) to NMR logs.
Optimized model constants using permeameter-based hydraulic conductivity (K) measurements.
Compared NMR-derived K profiles with co-located hydraulic testing data (permeameter, multi-level slug, HPT).

Main Results:

NMR logging provided reliable K estimates for interbedded sand/gravel, silt, and clay layers.
NMR-derived K profiles successfully mapped trends and magnitudes of aquifers and aquitards.
Quantitative agreement between NMR-derived and hydraulic-testing K was within one order of magnitude.
The Kozeny-Godefroy (KGM) model demonstrated optimal performance, particularly with slug-based K data.

Conclusions:

NMR logging is a viable method for estimating hydraulic conductivity in complex glaciofluvial environments.
The Kozeny-Godefroy (KGM) model is recommended for its reliable performance in these deposits.
Optimized NMR models provide valuable insights for hydrogeological characterization and site assessment.