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Applied Sciences
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New Insights into the Physics of Digital Porous Media
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New Insights into the Physics of Digital Porous Media

A Special Issue of Applied Sciences (ISSN 2076-3417) belonging to the section "Earth Sciences".

Deadline for manuscript submissions: 31 October 2026 | Viewed by 838

Editors

Dr. Hongyang Ni

E-Mail Website
Guest Editor
State Key Laboratory for GeoMechanics and Deep Underground Engineering, China University of Mining and Technology, Xuzhou, China
Interests: digital rocks; multi-scale; pore structure; macroscopic characterization
Special Issues, Collections and Topics in MDPI journals
Dr. Chengpeng Zhang

E-Mail Website
Guest Editor
State Key Laboratory of Coal Mine Disaster Dynamics and Control, Chongqing University, Chongqing 400044, China
Interests: unconventional reservoirs stimulation; rock micromechanics; microproppants
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Porous media are ubiquitous in both natural and engineered systems, and their macroscopic behavior is fundamentally governed by complex pore structures spanning multiple length scales. Understanding and predicting transport, reaction, and mechanical responses in such materials remain challenging because heterogeneity, connectivity, and multiphase/multiphysics couplings are difficult to quantify and model in a consistent manner. With rapid advances in digital imaging and computational techniques, pore-scale imaging, visualization, and quantitative analysis are enabling more rigorous links between microstructure and effective properties, thereby supporting both scientific discovery and engineering design.

Digital approaches to porous media bridge multiple disciplines, including geoscience, materials science, physics, mechanics, computational modeling, and machine learning. Over the past decades, major progress in imaging, reconstruction, segmentation, simulation, and upscaling has had a significant impact on both academic research and industrial practice. Nevertheless, key challenges remain, such as (i) accurate and efficient multiscale image acquisition and registration, (ii) robust phase/mineral identification and quantitative microstructural descriptors, (iii) physics-consistent numerical modeling and uncertainty quantification, and (iv) trustworthy integration of machine learning with pore-scale physics for prediction, optimization, and design.

Therefore, this Special Issue aims to collect original research articles and comprehensive review papers that clarify the state of the art in digital porous media—from image acquisition and reconstruction to pore-scale/multiscale modeling and final characterization of effective properties. All relevant contributions are welcome.

Dr. Hongyang Ni
Dr. Chengpeng Zhang
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-anonymized peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Applied Sciences is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • rock physics
  • reservoir characterization
  • image segmentation methods
  • multi-scale
  • pore structure
  • digital rock analysis
  • machine learning
  • macroscopic characterization

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Related Special Issue

Published Papers (2 papers)

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Research

20 pages, 23143 KB  
Article
An Effective Method for Digital Rock Reconstruction with Enhanced Pore Connectivity
by Junxian Li, Chuanyou Zhou and Ruoyu Li
Appl. Sci. 2026, 16(17), 8612; https://doi.org/10.3390/app16178612 - 29 Aug 2026
Viewed by 181
Abstract
Digital rock technology is essential for characterizing the petrophysical properties of tight reservoirs. However, conventional construction methods often yield models with insufficient pore connectivity due to low porosity and complex nanopore structures. To address this limitation, we propose a novel connectivity algorithm for [...] Read more.
Digital rock technology is essential for characterizing the petrophysical properties of tight reservoirs. However, conventional construction methods often yield models with insufficient pore connectivity due to low porosity and complex nanopore structures. To address this limitation, we propose a novel connectivity algorithm for isolated pore systems. First, a digital rock model is constructed using a random particle packing algorithm that integrates high-resolution SEM parameters, including kaolinite particle morphologies and randomly distributed microfractures. Subsequently, the connectivity algorithm sequentially links isolated pore clusters to the largest continuous pore system, forming an interconnected channel. Pore network extraction reveals that the algorithm produces significantly denser and more continuous structures, with pore–throat size distributions aligning well with experimental observations. Single-phase flow simulations demonstrate that the enhanced model yields porosity and permeability values consistent with laboratory measurements, whereas unenhanced models deviate substantially. To further advance microscale flow characterization, we derive explicit fitting formulas for the dimensionless conductivity of canonical pore cross-sections (equilateral triangle, square, and circle) considering water film boundary layer (WFBL) effects. These formulations are based on a comprehensive parametric study using the ab initio finite element method, followed by regression analysis to yield closed-form expressions. Two-phase flow simulations reveal that the WFBL increases residual saturations, reduces relative permeabilities, and decreases waterflooding displacement efficiency, with effects being more pronounced during secondary imbibition. This integrated approach provides a robust framework for constructing representative digital rock models of tight reservoirs and offers essential theoretical support for accurately modeling nanoscale flow behaviors in complex subsurface systems. Full article
(This article belongs to the Special Issue New Insights into the Physics of Digital Porous Media)
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19 pages, 24809 KB  
Article
Pore-Scale Resolution Effects on Image-Based Permeability Estimation in Tight Sandstone Using Physical Multiscale SEM Imaging
by Zipeng Chen, Hongyang Ni, Hai Pu and Yiping Sun
Appl. Sci. 2026, 16(16), 8273; https://doi.org/10.3390/app16168273 - 19 Aug 2026
Viewed by 325
Abstract
Reliable image-based permeability estimation in tight porous media depends strongly on how pore and throat geometries are resolved across scales. This study investigates the influence of image resolution on pore characterization and permeability estimation in tight sandstone using true multiscale scanning electron microscopy [...] Read more.
Reliable image-based permeability estimation in tight porous media depends strongly on how pore and throat geometries are resolved across scales. This study investigates the influence of image resolution on pore characterization and permeability estimation in tight sandstone using true multiscale scanning electron microscopy (SEM). A fixed sandstone region was imaged at three resolutions—S1 (0.1 μm/pixel), S4 (0.05 μm/pixel), and S16 (0.025 μm/pixel)—and spatially registered to ensure the same field of view across scales. Porosity, pore roundness, fractal dimension, pore size distribution, and permeability were extracted and compared. With increasing resolution, more fine pores are identified, porosity rises from 4.6% (S1) to 5.55% (S4) and 6.31% (S16), pore roundness and fractal dimension increase, indicating greater complexity and fine-scale heterogeneity. Meanwhile, the pore size distribution narrows and shifts towards smaller pores as large merged pores at low resolution are decomposed into multiple micropores. Permeability derived from individual images becomes more spatially variable at higher resolutions, but the overall permeability decreases, with only a small additional change from S4 to S16. The values at the S4 and S16 scales (1.77 × 10−17 m2 and 1.72 × 10−17 m2) agree well with the measured gas permeability of 1.85 × 10−17 m2. These results indicate that image resolution exerts systematic control on transport-relevant pore descriptors and image-based permeability. Within the investigated resolution range, further refinement from S4 to S16 reveals additional fine-scale heterogeneity but produces only a limited change in the overall permeability estimate. The findings, therefore, highlight the importance of balancing image resolution and field-of-view representativeness in digital-rock workflows aimed at pore-scale transport analysis and permeability upscaling. Full article
(This article belongs to the Special Issue New Insights into the Physics of Digital Porous Media)
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