Characterizing Spatial Heterogeneity of Hydraulic Conductivity Using Borehole NMR in a Complex Groundwater Flow System

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Abstract

Borehole nuclear magnetic resonance (NMR) logging can yield estimates of hydraulic conductivity (K) in unconsolidated sediments. Previous studies focused on establishing petrophysical models relating NMR responses to K and calibrating model constants for optimized K estimation. However, research has yet to explore the potential of NMR logging to derive spatial K distributions, which would enable its utilization in numerical groundwater flow and transport models. In this study, we construct various spatial K models based on NMR logging data. Characterization of spatial heterogeneity between NMR logs is explored using: (a) geostatistical interpolation approaches, including ordinary kriging and indicator kriging, (b) a zonation approach using clustering with spatial constraints for improved extraction of zone geometry, and (c) a hybrid model of multi-level spatial heterogeneity nesting a zonal representation with zonally kriged K. The representativeness of NMR-derived spatial K models is evaluated by reproducing a permeameter-based K profile at an unsampled location and by comparing the numerically simulated drawdown responses with field observations of ten pumping tests. Results reveal that the spatially associated zonation model can effectively represent the K patterns between boreholes. Incorporating intralayer heterogeneity further refines the characterization of K heterogeneity, achieving optimal drawdown predictions. More importantly, its drawdown prediction performance remains stable with a limited NMR data set. This study provides a framework for using high-resolution NMR-derived K profiles from multiple boreholes to characterize spatial heterogeneity at sub-meter scales in a highly heterogeneous, layered geologic deposit.

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Wang, C., Steelman, C. M., & Illman, W. A. (2025). Characterizing Spatial Heterogeneity of Hydraulic Conductivity Using Borehole NMR in a Complex Groundwater Flow System. Water Resources Research, 61(10). https://doi.org/10.1029/2024WR039717

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