Szczegóły publikacji

Opis bibliograficzny

Modelling effective diffusion for accurate NMR pore size analysis in nano- and microporous rocks / Michał FAJT, Grzegorz MACHOWSKI, Bartosz PUZIO, Artur T. KRZYŻAK // Scientific Reports [Dokument elektroniczny]. — Czasopismo elektroniczne ; ISSN  2045-2322 . — 2025 — vol. 15 iss. 1 art. no. 36688, s. 1–17. — Wymagania systemowe: Adobe Reader. — Bibliogr. s. 15–16, Abstr. — Publikacja dostępna online od: 2025-10-21

Autorzy (4)

Słowa kluczowe

surface relaxivityinternal gradientspore size distributiondiffusionlow field NMRPSDLF-NMR

Dane bibliometryczne

ID BaDAP163972
Data dodania do BaDAP2025-11-14
Tekst źródłowyURL
DOI10.1038/s41598-025-20379-x
Rok publikacji2025
Typ publikacjiartykuł w czasopiśmie
Otwarty dostęptak
Creative Commons
Czasopismo/seriaScientific Reports

Abstract

Low-field NMR (LF-NMR) is a widely applied technique for evaluating pore size distribution (PSD) in porous materials. Conventional approaches typically assume surface-controlled spin-spin relaxation and negligible diffusion contributions under the fast-diffusion regime, which introduces systematic errors when applied to nano- and microporous systems. In this work, we present the Effective Diffusion Cubic (EDC) model, a new framework for LF-NMR-based PSD estimation in tight rocks. The EDC method incorporates pore-size dependence of both the effective diffusion coefficient and the induced internal magnetic field gradient. Crucially, the effective diffusion coefficient, D(d), is parameterized by a logistic function that faithfully approximates the Padé form, enabling a precise quantification of diffusion-related effects on T2 relaxation. Applied to nine siliciclastic core samples, the EDC approach produced PSDs corrected for diffusion-induced distortions and in closer agreement with independent reference data compared to conventional models. These results demonstrate that the EDC methodology provides a physically consistent and more accurate means of quantifying pore systems, thereby enhancing NMR-based petrophysical characterization of tight rock formations.

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