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用于解释包含记忆和超分散效应的脉冲场梯度核磁共振数据的模型。

Model to interpret pulsed-field-gradient NMR data including memory and superdispersion effects.

作者信息

Néel Marie-Christine, Bauer Daniela, Fleury Marc

机构信息

Université d'Avignon et des Pays de Vaucluse, UMR 1114 EMMAH, F-84018 Avignon Cedex, France.

IFP Energies nouvelles, 1 et 4, avenue de Bois Préau 92852, Rueil-Malmaison, France.

出版信息

Phys Rev E Stat Nonlin Soft Matter Phys. 2014 Jun;89(6):062121. doi: 10.1103/PhysRevE.89.062121. Epub 2014 Jun 13.

Abstract

We propose a versatile model specifically designed for the quantitative interpretation of NMR velocimetry data. We use the concept of mobile or immobile tracer particles applied in dispersion theory in its Lagrangian form, adding two mechanisms: (i) independent random arrests of finite average representing intermittent periods of very low velocity zones in the mean flow direction and (ii) the possibility of unexpectedly long (but rare) displacements simulating the occurrence of very high velocities in the porous medium. Based on mathematical properties related to subordinated Lévy processes, we give analytical expressions of the signals recorded in pulsed-field-gradient NMR experiments. We illustrate how to use the model for quantifying dispersion from NMR data recorded for water flowing through a homogeneous grain pack column in single- and two-phase flow conditions.

摘要

我们提出了一种专门为核磁共振测速数据的定量解释而设计的通用模型。我们采用拉格朗日形式的弥散理论中应用的移动或固定示踪粒子的概念,并增加了两种机制:(i)有限平均值的独立随机停滞,代表平均流动方向上极低速度区域的间歇期;(ii)意外长(但罕见)位移的可能性,模拟多孔介质中极高速度的出现。基于与从属列维过程相关的数学性质,我们给出了脉冲场梯度核磁共振实验中记录信号的解析表达式。我们说明了如何使用该模型从在单相和两相流动条件下流经均匀颗粒填充柱的水所记录的核磁共振数据中量化弥散。

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