Modelling effective diffusion for accurate NMR pore size analysis in nano- and microporous rocks

This database contains the complete dataset supporting the study titled "Modelling effective diffusion for accurate NMR pore size analysis in nano- and microporous rocks". It includes raw and processed data acquired from three complementary petrophysical methods: Low-Field Nuclear Magnetic Resonance (LF-NMR), Mercury Intrusion Capillary Porosimetry (MICP), and Low-Temperature Nitrogen Adsorption (LTNA), as well as Magnetic Susceptibility (MS) data. The data were collected from a diverse set of 9 tight siliciclastic rock samples: sandstones, heteroliths and mudstones. In addition to standard measurement files, the dataset includes a numerical simulation tool for modelling the pore-size-dependent effective diffusion coefficient, D(d). By using this dataset, researchers can reproduce the data analysis presented in the associated article, test their own T2-PSD conversion models, and simulate the impact of restricted diffusion on T2 relaxation in tight porous media.

The data can be interpreted as follows:
MICP and LTNA data serve as a reference for the Pore Size Distribution. These two methods can be combined to create a comprehensive reference PSD across a wide range of pore sizes (from nano- to micrometres).
LF-NMR T2 relaxation data provides an alternative, non-destructive method for estimating PSD after T2-Pore Size transformation.
MS data can be used to calculate the magnitude of internal magnetic gradients' influence over a given PSD range.
The included effective diffusion simulation file allows users to model the relationship between the diffusion coefficient (D) and pore diameter (d). This is crucial for accurately converting T2 relaxation times into pore sizes, especially in systems where diffusion is restricted. Parameters such as time echo (TE), magnetic susceptibility, and porosity can be changed to fit the model to your data.