NMR Characterization of Pore Structure and Connectivity for Nano-self-assembly γ-Al2O3 and Precursor


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Abstract

Nano-self-assembly γ-Al2O3 (NSAA) is a catalytic material and can be used as a physical model of micro–nano-porous material for understanding shale and tight formations. Herein, we describe the development of an in situ, fast, and quantitative method for the potential nuclear magnetic resonance (NMR) characterization of pore system in a nano-self-assembly precursor (NSAP) for the first time. The surface relaxivity ρ2 of small pores, which are water saturated is found to be 0.65 and 0.85 μm μs−1, while ρ2 for large pores, which are hydrocarbon saturated is 0.55 μm μs−1. This points to the interaction of water molecules with inorganic pore surface being stronger than that of hydrocarbon molecules. A new method for reconstructing the capillary pressure curve (Pc) is used to comprehensively reflect the pore structure of NSAA and predict NMR Pc. The pore network model of NSAA is proposed based on NMR quantitative characterization and SEM evaluation, and it has pore channels, which are suitable for macromolecule diffusion. A set of low-field NMR methods for evaluating the pore connectivity of nanomaterials are established. The experiments demonstrate that low-field NMR is a robust tool for characterizing pore channels for macromolecule transport in catalytic materials, with an important application field being shale oil and tight sand oil development and petroleum refining.

About the authors

Lin Wang

State Key Laboratory of Petroleum Resources and Prospecting, China University of Petroleum

Email: xiaolizhi@cup.edu.cn
China, Beijing, 102249

Lizhi Xiao

State Key Laboratory of Petroleum Resources and Prospecting, China University of Petroleum; Harvard SEAS-CUPB Joint Laboratory

Author for correspondence.
Email: xiaolizhi@cup.edu.cn
China, Beijing, 102249; Cambridge, MA, 02138

Wenzheng Yue

State Key Laboratory of Petroleum Resources and Prospecting, China University of Petroleum

Email: xiaolizhi@cup.edu.cn
China, Beijing, 102249


Copyright (c) 2018 Springer-Verlag GmbH Austria, part of Springer Nature

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