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Estimating T2 from surface NMR FID data using a forward model based on the full-Bloch equation

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An integral component of the surface nuclear magnetic resonance forward model involves predicting the magnitude of the transverse magnetization following excitation. To predict the transverse magnetization, the Bloch equation must be solved. Traditional surface NMR forward models solve a simplified version of the Bloch equation where the relaxation terms are neglected. A shortcoming of this approach is that it can struggle to accurately describe the impact of relaxation during pulse effects. To address this concern, an alternative forward model based on solution of the full-Bloch equation is proposed. The advantage of the proposed scheme is that it implicitly accounts for relaxation during pulse effects, increases the flexibility to implement alternative parametrizations of the inverse model, and can readily describe an arbitrary excitation protocol given that it no longer requires closed form expressions of the transverse magnetizations. To demonstrate the potential of the updated forward modelling scheme, a novel approach for the inversion of complex-valued free-induction decay (FID) data is presented. The inverse model is reparametrized in order to produce depth profiles of the water content, T2∗ and T2. This approach has great potential to enhance the ability of FID measurements to provide insights into pore size and permeability as it can provide direct sensitivity to T2. In contrast, traditional approaches that employ a forward model based on the simplified Bloch equation and estimate only T2∗ are plagued by uncertainty surrounding the link between T2∗ and pore size/permeability. Synthetic and field results are presented to demonstrate the feasibility of the proposed forward model and FID inversion framework.

Original languageEnglish
JournalGeophysical Journal International
Pages (from-to)1892-1902
Number of pages11
Publication statusPublished - 2019

    Research areas

  • Electromagnetic methods, Hydrogeophysics, Inverse problem, Numerical techniques

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