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The feasibility of using machine learning to estimate rock permeability from nuclear magnetic resonance T2\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\odds

Alexsander M. Cunha, Rafael S. Vianna, Pedro M. Vianna, Andre Souza, Pedro C. F. Lopes, Andre M. B. Pereira, Ricardo Leiderman

2026.6.24COMPUTATIONAL GEOSCIENCES

DOI: 10.1007/s10596-026-10458-x

Abstract

Abstract is not available.

Citation format

CUNHA, Alexsander M., et al. The feasibility of using machine learning to estimate rock permeability from nuclear magnetic resonance t2\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\odds. COMPUTATIONAL GEOSCIENCES, 2026, 30.