AUTHOR=Liu Wei , Shang Lin , Gao Guangliang , Li Dan , Wang Miao , Geng Wenshuang , Jia Qian , Zhang Guodong , Zhang Haixiang , Hao Pengfei , Peng Licai 

TITLE=Microstructure characterization of tight reservoirs using micro-CT and FIB-SEM imaging technology

JOURNAL=Frontiers in Earth Science

VOLUME=Volume 13 - 2025

YEAR=2025

URL=https://www.frontiersin.org/journals/earth-science/articles/10.3389/feart.2025.1551826

DOI=10.3389/feart.2025.1551826

ISSN=2296-6463

ABSTRACT=This study presents a comprehensive investigation into the intricate microstructural characteristics of tight reservoir rocks, utilizing advanced micro-CT scanning and FIB-SEM technologies. Micro-CT scanning technology was employed to obtain clear micro-pore structures and pore-throat size distribution patterns of four typical lithologies: dolomite, sandstone, mudstone, and conglomerate. Our findings reveal that the average pore-throat dimensions in tight reservoirs are confined to several micrometers, markedly diminutive by 1-2 orders of magnitude compared to their conventional counterparts. The FIB-SEM was used to obtain the distribution patterns of nano- and micrometer-scale pore-throats in tight cores. Nano-scale pores with equivalent diameters below 200 nm accounted for 20% of the total pore area, contributing minimally to storage space and permeability, while the main storage space and flow channels were concentrated in micrometer-scale pore-throats. Three-dimensional micro-CT scanning provides a comprehensive and intuitive digital rock structure for establishing permeability models, while nano-scale two-dimensional scanning yields finer microscopic pore-throat structures and size distribution patterns. The combination of both methods leads to measurement results closer to reality. Conclusively, we propose a mathematical formulation for predicting the absolute permeability of tight reservoirs, predicated on micro-scan data. This formulation is distinguished by its generality, computational simplicity, and its potential to furnish essential data for the design of reservoir development strategies.