Geophysical nuclear magnetic resonance (NMR) applications are used to estimate pore size distributions (PSDs) of rocks and sediments. This is commonly realized by empirical calibration using information about the surface‐to‐volume ratio of the material. Recent research has developed joint inversion concepts for NMR relaxation data that provides the PSD with a minimum of information. The application requires the NMR signal of a sample at saturation and at least one at partial saturation and at known suction. The new inversion concept physically simulates the desaturation process as part of the forward operator. The cross‐section of the model capillaries in the underlying bundle can be either circular or triangular. Our study investigates the performance of the NMR joint inversion to predict water retention function (WRF) and capillary‐based hydraulic conductivity (K_cap) as functions of saturation for different sands. The angularity of the pores has no significant impact on the estimated WRF but affects the K_cap estimation significantly. Our study shows that the WRF is predicted reliably for sand samples under fast diffusion conditions. The K_cap estimations are also plausible but tend to systematic overestimation, for which we identified the tortuosity being the main reason. Because NMR relaxation data generally do not provide tortuosity information, a plausible tortuosity model remains an issue of classical calibration. Further development of the approach will thus consider tortuosity measurements (e.g., by electrical resistivity measurements and/or gradient NMR) and will consider the relaxation mechanisms outside fast diffusion conditions to enhance its applicability for coarse soils.

中文翻译：

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基于圆形和三角形毛细管模型的核磁共振测量的土壤水力解释

地球物理核磁共振（NMR）应用程序用于估算岩石和沉积物的孔径分布（PSD）。这通常通过使用材料表面体积比信息进行经验校准来实现。最近的研究为NMR弛豫数据开发了联合反演概念，为PSD提供了最少的信息。该应用要求样品的NMR信号处于饱和状态，至少一个处于部分饱和状态且处于已知吸力下。新的反演概念在物理上模拟了去饱和过程，作为正向算子的一部分。基础束中的模型毛细管的横截面可以是圆形或三角形。K _cap）是不同沙子饱和度的函数。孔的角度对估计的WRF没有明显影响，但对K _cap估计有很大影响。我们的研究表明，在快速扩散条件下，砂粒样品的WRF是可靠的。该ķ_帽估计也是合理的，但倾向于系统性的高估，为此，我们确定了曲折是主要原因。由于NMR弛豫数据通常不提供曲折度信息，因此，合理的曲折度模型仍然是经典校准的问题。因此，该方法的进一步发展将考虑曲折度测量（例如，通过电阻率测量和/或梯度NMR），并将考虑快速扩散条件之外的松弛机制，以增强其在粗糙土壤中的适用性。