InterPore Journal
type: channel
description: InterPore Journal is a new international, peer-reviewed, open-access journal, fully owned and published by the International Society for Porous Media (InterPore). Like the Society, our mission is to advance knowledge and research on porous media systems and their technical and industrial applications. We provide a trusted medium for sharing insights into the processes and phenomena involved, bringing together contributions from across disciplines to strengthen the global porous media community. The journal publishes original research articles, technical notes, review papers, open datasets and source codes, as well as short communications, commentaries, and opinion pieces. Topics span the full breadth of porous media science and technology, including imaging and characterization, physical and numerical modeling, data-driven methods, material design, and applications in geology, industry, environment, and biology. Our overarching goal is to serve as the focal point for the worldwide porous media community by publishing and freely sharing high-quality, multidisciplinary, and multiscale research. Articles are published under a Creative Commons license and appear four times per year with the online release of each issue, following final publication approval by the authors. Information on all published articles is shared through our bi-weekly e-newsletters (reaching 3000+ recipients) and across our social media channels. Stay Connected Keep up with the latest publications, news, and updates from InterPore Journal by subscribing to our newsletter and following us on social media. Join our vibrant online community and engage with fellow researchers worldwide: LinkedIn X YouTube Submit your manuscript today and join us in advancing the field of porous media science and technology. We look forward to receiving your contributions and continuing to support the growth of knowledge in 2025 and beyond.
publisher: InterPore: International Society for Porous Media
language: en
publication name: InterPore Journal
issn: 3105-6369
copyright: Unless otherwise stated above, this is an open access article published by InterPore under either the terms of the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0) (https://creativecommons.org/licenses/by-nc-nd/4.0/). Article metadata are available under the CCo license.
items: Highlights from the new issue of InterPore Journal
items: MAGNET: Medial Axis Guided Network Extraction Tool
items: Suitability Mapping for Subsurface Floodwater Storage Schemes
items: Static Elastic Properties of Rocks Obtained by X-ray Microtomography, Inverse Modeling and Surrogate Model
items: A Hydro-Geomechanical Porous-Media Model to Study Effects of Engineered Carbonate Precipitation in Faults
items: On the Interpretation of Unsteady State Experiments in Heterogeneous Rock by Stochastic Methods
items: Experimental Investigation of Solubility Trapping in 3D Printed Micromodels
items: 3D Printing Reactive Porous Media: Calcite Precipitation Kinetics on Surface Functionalized Polymer Films and 3D-printed Cores
items: Experimental Study of Microbial Hydrogen Consumption Rates by Oleidesulfovibrio Alaskensis in Porous Media
items: Regional-Scale Subsurface Modeling
items: Highlights From the New Issue of InterPore Journal
items: Understanding Fracture Aperture and Permeability Evolution due to Carbonate Mineralization Utilizing 3D Printing
items: A novel robust optimization framework based on surrogate modeling for underground hydrogen storage in depleted natural gas reservoirs
items: Rubble Characteristics Associated with Room Collapse at the Waste Isolation Pilot Plant: Impact of Salt Clast Shapes and Size Distributions on the Depositional Pore System
items: Anchored Physics-Informed Neural Network for Two-Phase Flow Simulation in Heterogeneous Porous Media
items: Highlights From the Fourth issue of InterPore Journal
items: The Importance and Challenges Associated with Multi-scale Heterogeneity for Geological Storage
items: Enhancing Effective Thermal Conductivity Predictions in Digital Porous Media Using Transfer Learning
items: Modeling of Hydraulic Fracture Propagation in Real Heterogeneous Conglomerates from the Mahu Oilfield using the Global Cohesive Zone Method
items: A framework for simulating the partially miscible multi-component hydrocarbon fluids in porous media via the pseudo-potential lattice Boltzmann model
items: Modeling Nanoparticle-Stabilized Foam Flow in Porous Media Accounting for Particle Retention and Permeability Reduction
items: Biosurfactant-induced PFAS Leaching from Aqueous Film-Forming Foam (AFFF) Impacted Soil
items: The Influence of Density Driven Mixing Mechanisms on Ureolysis Induced Carbonate Precipitation
items: Integration of geochemistry into a geomechanical subsurface flow simulator
items: Inverse method to determine hydraulic conductivity from a velocity field using graph theory
items: High-fidelity experimental model verification for flow in fractured porous media
items: A line search algorithm for multiphysics problems with fracture deformation
items: Exploring chances and limitations of high resolution 3D-printing for guided water percolation in gas diffusion layers of polymer electrolyte fuel cells
items: The soil plastisphere: The nexus of microplastics, bacteria, and biofilms

Highlights from the new issue of InterPore Journal
type: item
description: As we open this new issue of the InterPore Journal, I am encouraged by how rapidly our field is developing and by the role the journal plays in this progress. Each contribution in this edition reflects not only technical advancement but also the expanding relevance of porous media research to a wide range of challenges. The work presented here demonstrates a shared commitment to curiosity, rigor, and collaboration, which are necessary to sustain our community and push the boundaries of what we can achieve together.
subject: Editorial
  topic: section
subject: Editorial
  topic: keywords
creator: Nima Shokri
rights: Copyright (c) 2025 Nima Shokri https://creativecommons.org/licenses/by-nc-nd/4.0
date: 2025-12-01
publication date: 2025-12-01
starting page: IPJ011225
ending page: 1
doi: 10.69631/6nwzqr77

Highlights from the new issue of InterPore Journal
type: item
subject: Editorial
  topic: section
subject: Editorial
  topic: keywords
creator: Nima Shokri
rights: Copyright (c) 2025 Nima Shokri https://creativecommons.org/licenses/by-nc-nd/4.0
date: 2025-08-25
publication date: 2025-08-25
starting page: IPJ250825
ending page: 1
doi: 10.69631/ipj.v2i3nr99

MAGNET: Medial Axis Guided Network Extraction Tool
type: item
description: Pore network models are useful for studying transport in porous materials in a computationally efficient way. Extraction of networks from volumetric images has evolved over the years, starting with medial axis-based approaches to more recent watershed segmentation. This paper reconsiders the classic medial axis method, which offers several advantages such as speed and topological correctness, and develops a modernized, updated, and improved version. The new method is named Medial Axis Guided Network Extraction Tool (MAGNET). It works by analyzing the skeleton of a porous material to identify pore centers at junctions and endpoints. Additional pore bodies are found on long throats using two different approaches. This work includes an efficient tool for calculating the cross-sectional area of throats with irregular shape by using walkers with an infinite mean-free path to probe the geometry orthogonal to the medial axis at the point of the throat constriction. This extra step was critical for obtaining an equivalent diameter needed to calculate the permeability. Lastly, MAGNET was written with computational efficiency in mind. The skeletonization approach was itself 4.2X faster than the SNOW watershed segmentation for a 10003 image. Additionally, a parallelized skeletonization was applied by processing the image in blocks with sufficient overlap which resulted in a 5.5X speed-up compared to the serial approach. To validate the output, MAGNET was tested on a 4003 voxel image of a Berea sandstone, and the flow and capillary properties of the extracted network were compared to the results from SNOW and the lattice-Boltzmann method. Structural information such as pore and throat size distribution and mercury intrusion curves was compared, and noticeable similarity was achieved. Crucially, the permeability predicted by MAGNET was within 5% of the lattice-Boltzmann prediction on the same image.
subject: Original Research Papers
  topic: section
subject: Network extraction
  topic: keywords
subject: Pore network modelling
  topic: keywords
subject: Image processing
  topic: keywords
subject: Permeability
  topic: keywords
subject: Porous media
  topic: keywords
creator: Michael McKague
creator: Hamed Fathiannasab
creator: Mohammad Amin Sadeghi
creator: Jeff Gostick
rights: Copyright (c) 2025 Michael McKague, Hamed Fathiannasab, Mohammad Amin Sadeghi, Jeff Gostick https://creativecommons.org/licenses/by-nc-nd/4.0
date: 2025-12-01
publication date: 2025-12-01
starting page: IPJ011225
ending page: 7
doi: 10.69631/g47x8w91

Suitability Mapping for Subsurface Floodwater Storage Schemes
type: item
description: The hydrological conditions a changing climate imposes require updated measures to address extreme water events sustainably. These must evolve from isolated solutions, such as water retention basins, to holistic management strategies that consider at least two situations simultaneously, such as floods and droughts. One strategy for sustainable groundwater management is managed aquifer recharge (MAR), which copes with decreasing groundwater levels by a targeted recharge of aquifers. Using high water as a recharge water source (Flood-MAR) can additionally cover the aspect of flood protection, resulting in a multi-beneficial solution for the region. This study evaluated the site suitability for subsurface floodwater storage schemes, which must focus more on assessing the existing aquifer characteristics and the specific flood dynamics in nearby rivers compared to known MAR schemes. Potential sites for underground flood storage are characterized by decreasing groundwater levels and, thus, frequent water scarcity, combined with eminent risks of flooding by a nearby river. Suitability, on the other hand, must take the aquifer, surface, and water source characteristics into account. In this study, we present a workflow for generating suitability maps for implementing subsurface floodwater storage systems with a geographic information system-based multi-criteria decision analysis (MCDA). The workflow was intentionally and exclusively based on publicly available data, was implemented in Python, and provided as open-source software. The resulting suitability maps spatially depict the feasibility of underground flood storage, and thus form the basis for the implementation planning of such projects. The approach was demonstrated for the administrative district of Swabia, Germany, where approximately 35% of the area was identified as suitable at varying levels. A sensitivity analysis of the assigned weights was applied to show the high robustness of the underlying data. The resu…
subject: Original Research Papers
  topic: section
subject: Flood and drought management
  topic: keywords
subject: Managed aquifer recharge (MAR)
  topic: keywords
subject: Geographic information systems (GIS)
  topic: keywords
subject: GIS-based multi-criteria decision analysis (GIS-MCDA)
  topic: keywords
subject: Floodwater storage
  topic: keywords
subject: Landscape water balance
  topic: keywords
creator: Lea Augustin
creator: Thomas Baumann
rights: Copyright (c) 2024 Lea Augustin, Thomas Baumann https://creativecommons.org/licenses/by-nc-nd/4.0
date: 2024-08-24
publication date: 2024-08-24
starting page: ipj240824
ending page: 7
doi: 10.69631/ipj.v1i2nr20

Static Elastic Properties of Rocks Obtained by X-ray Microtomography, Inverse Modeling and Surrogate Model
type: item
description: Digital rock analysis uses imaging techniques to obtain information concerning the internal structure of the rock. In the context of obtaining mechanical properties from digital images, much attention is given to determining the elastic parameters of rocks based on their mineralogical composition. While many applications for this type of simulation are available in the literature, the quantification of mineral property variations resulting from external influences has largely been overlooked. This work adopts an inverse modeling approach to estimate such elastic property variations in rocks. This methodology requires a predictive tool and an optimization algorithm to iteratively update the model’s parameters while reducing the discrepancies between modeled and measured data. In this study, a representative sandstone sample from the Botucatu Formation in Brazil was used to evaluate the methodology. Two case studies were considered: a synthetic example was designed for validation of the methodology while the second case applies real-world laboratory test data to estimate the properties that are most supported by the experimental evidence. A MATLAB code was built to integrate a finite element program and a genetic algorithm in a single framework. Additionally, an artificial neural network was used as a surrogate model to reduce the computational time of the numerical forward run. Overall, the results support the robustness of the approach and present a new alternative to obtain the mechanical properties of rock constituents at the pore scale.
subject: Original Research Papers
  topic: section
subject: Elastic properties
  topic: keywords
subject: X-ray microtomography
  topic: keywords
subject: Inverse modeling
  topic: keywords
subject: Surrogate model
  topic: keywords
subject: Pore-scale
  topic: keywords
creator: Ruan Gomes
creator: Sergio Fontoura
creator: Guilherme Righetto
creator: Luiza Fernandes
creator: Rafael Lopez
creator: Rafaella Sampaio
creator: Claudio Lima
creator: Marcel Naumann
creator: William Silva
rights: Copyright (c) 2025 Ruan Gomes, Sergio Fontoura, Guilherme Righetto, Luiza Fernandes, Rafael Lopez, Rafaella Sampaio, Claudio Lima, Marcel Naumann, William Silva https://creativecommons.org/licenses/by-nc-nd/4.0
date: 2025-12-01
publication date: 2025-12-01
starting page: IPJ011225
ending page: 5
doi: 10.69631/v65nzv74

A Hydro-Geomechanical Porous-Media Model to Study Effects of Engineered Carbonate Precipitation in Faults
type: item
description: Hydro-geomechanical models are required to predict or understand the impact of subsurface engineering applications such as gas storage in geological formations. This study focuses on engineered carbonate precipitation through biomineralization in a fault zone of a cap-rock, aiming to reduce gas leakage from a reservoir. In addition to altering hydraulic properties such as porosity and permeability, precipitated carbonates also change the mechanical properties of the rock. We present a conceptual modeling approach implemented in the open-source simulator DuMux. After model verification, we applied the model to a CO2-storage scenario to investigate how biomineralization affects stress distribution within the rock, as well as how it may alter the risks of fault reactivation and induced seismic events. The generic study shows a tendency towards increased stiffness due to precipitated carbonate, which may cause shear failure events to occur earlier than in an untreated setup, while the magnitude of the seismicity is smaller.
subject: Original Research Papers
  topic: section
subject: Hydro-geomechanical coupling
  topic: keywords
subject: Biomineralization
  topic: keywords
subject: Fault reactivation
  topic: keywords
subject: Model verification
  topic: keywords
creator: Yue Wang
creator: Holger Class
rights: Copyright (c) 2025 Yue Wang, Holger Class https://creativecommons.org/licenses/by-nc-nd/4.0
date: 2025-06-04
publication date: 2025-06-04
starting page: IPJ040625
ending page: 6
doi: 10.69631/ipj.v2i2nr41

On the Interpretation of Unsteady State Experiments in Heterogeneous Rock by Stochastic Methods
type: item
description: Rock heterogeneity has a significant effect on immiscible displacement. This is especially true when the mobility ratio of the two fluids is unfavorable, favoring unstable displacement. However, this is not taken into account in the numerical analysis of classical core flooding experiments to quantify two-phase flow properties using Special Core Analysis (SCAL). Our approach combines the modern interpretation of SCAL data with experimental data measured on rock samples for which the homogeneity assumption - a prerequisite for SCAL experiments - can no longer apply due to their size and heterogeneity. In contrast to other studies that take heterogeneities into account, we focus on simple-to-perform unsteady-state experiments. We analyze these experiments by numerical interpretation using homogeneous and heterogeneous simulation domains and by introducing porosity-based heterogeneity and permeability as well as capillary scaling. In the current study, we first question the applicability of standard relative permeability measurements to heterogeneous rocks and fluids with an excessively high mobility ratio, such as for CO2-brine displacement in heterogeneous rocks. However, we show that they describe two-phase flow very well when porosity-based heterogeneity is taken into account, which is equivalent to downscaling. The study thus shows a way to fall back on established standard measurements if it should be possible to account for subgrid heterogeneities in SCAL workflows. To this end, we propose an approach based on steady-state experiments and appropriate sample selection.
subject: Original Research Papers
  topic: section
subject: Special Core Analysis
  topic: keywords
subject: CO2 sequestration
  topic: keywords
subject: unsteady-state experiments
  topic: keywords
subject: relative pereability
  topic: keywords
subject: capillary heterogeneity
  topic: keywords
subject: upscaling
  topic: keywords
creator: Omidreza Amrollahinasab
creator: Boris Jammernegg
creator: Siroos Azizmohammadi
creator: Holger Ott
rights: Copyright (c) 2025 Omidreza Amrollahinasab, Boris Jammernegg, Siroos Azizmohammadi, Holger Ott https://creativecommons.org/licenses/by-nc-nd/4.0
date: 2025-06-04
publication date: 2025-06-04
starting page: IPJ040625
ending page: 5
doi: 10.69631/ipj.v2i2nr44

Experimental Investigation of Solubility Trapping in 3D Printed Micromodels
type: item
description: Understanding interfacial mass transfer during dissolution of gas in a liquid is vital for optimizing large-scale carbon capture and storage operations. While the dissolution of CO2 bubbles in reservoir brine is a crucial mechanism towards safe CO2 storage, it is a process that occurs at the pore-scale and is not yet fully understood. Direct numerical simulation (DNS) models describing this type of dissolution exist and have been validated with semi-analytical models on simple cases like a rising bubble in a liquid column. However, DNS models have not been experimentally validated for more complicated scenarios such as dissolution of trapped CO2 bubbles in pore geometries where there are few experimental datasets. In this work, we present an experimental and numerical study of trapping and dissolution of CO2 bubbles in 3D printed micromodel geometries. We used 3D printing technology to generate three different geometries, a single cavity geometry, a triple cavity geometry, and a multiple channel geometry. To investigate the repeatability of the trapping and dissolution experimental results, each geometry was printed three times, and three identical experiments were performed for each geometry. The experiments were performed at a low capillary number (Ca = 3.33 x 10-6), representative of flow during CO2 storage applications. The DNS simulations were then performed and compared with the experimental results. Our results show experimental reproducibility and consistency in terms of CO2 trapping and the CO2 dissolution process. At such a low capillary number, our numerical simulator cannot model the process accurately due to parasitic currents and the strong time-step constraints associated with capillary waves. However, we show that, for the single and triple cavity geometry, the interfacial transfer and resulting bubble dissolution can be reproduced by a numerical strategy where the interfacial tension is divided by 100 to relax the capillary time-step constraints. Th…
subject: Original Research Papers
  topic: section
subject: Mass Transfer
  topic: keywords
subject: CO2 Dissolution
  topic: keywords
subject: CO2 Trapping
  topic: keywords
subject: 3D printing
  topic: keywords
subject: Direct Numerical Simulation
  topic: keywords
creator: Alexandros Patsoukis Dimou
creator: Mahdi Mansouri Boroujeni
creator: Sophie Roman
creator: Hannah P. Menke
creator: Julien Maes
rights: Copyright (c) 2025 Alexandros Patsoukis Dimou, Mahdi Mansouri Boroujeni, Sophie Roman, Hannah Menke, Julien Maes https://creativecommons.org/licenses/by-nc-nd/4.0
date: 2025-06-04
publication date: 2025-06-04
starting page: IPJ040625
ending page: 4
doi: 10.69631/ipj.v2i2nr49

3D Printing Reactive Porous Media: Calcite Precipitation Kinetics on Surface Functionalized Polymer Films and 3D-printed Cores
type: item
description: Mineral precipitation reactions in porous media can change the porosity and permeability of the rock formations. Predicting the rate of reaction and impacts on formation properties is challenging due to a lack of understanding of mineral precipitation reaction kinetics and mechanisms in porous media. This is furthermore challenging due to the highly heterogeneous nature of natural porous media. Here, we aim to develop a novel experimental platform leveraging 3D printing to facilitate replicable mineral precipitation experiments in controlled, heterogenous porous media systems. This requires fundamental understanding of the kinetics of mineral precipitation on the polymer materials used to fabricate the 3D printed porous media. In this work, we manipulate (via sulfonation) material surfaces (high impact polystyrene, HIPS) to promote calcite precipitation from supersaturated solutions to inform the design of synthetic subsurface systems. Calcite precipitation on HIPS films of varied surface sulfonation is confirmed using X-ray diffraction (XRD) analysis and weight-based precipitation experiments where increased precipitation with increased surface functionalization and solution saturation index are observed. This approach is then applied to 3D-printed porous media to enhance understanding of geochemical reactions, specifically calcite precipitation. Three dimensional images of Bentheimer Sandstone are used as the basis for 3D-printed porous media samples. Two 3D-printed samples were functionalized with acid to activate the surface and promote mineral precipitation. Functionalized and unfunctionalized samples underwent calcite precipitation core flooding experiments with oversaturated calcite solutions for 96 hours. Three dimensional X-ray micro-CT imaging revealed calcite growth in functionalized samples, with a calcite volume fraction of approximately 2.6% and a substantial reduction in porosity. Unfunctionalized samples exhibited diminished calcite precipitation and…
subject: Original Research Papers
  topic: section
subject: Mineral precipitation
  topic: keywords
subject: Surface functionalization
  topic: keywords
subject: 3D printing
  topic: keywords
subject: Porosity-permeability evolution
  topic: keywords
subject: X-ray CT imaging
  topic: keywords
creator: Harrish Kumar Senthil Kumar
creator: Abdullah Al Nahian
creator: Nailah Braziel
creator: Zhoufan Shi
creator: Madelyn Torrance
creator: Vinita V. Shinde
creator: Lauren E. Beckingham
creator: Bryan S. Beckingham
rights: Copyright (c) 2025 Harrish Kumar Senthil Kumar, Abdullah Al Nahian, Nailah Braziel, Zhoufan Shi, Madelyn Torrance, Vinita V. Shinde, Lauren E. Beckingham, Bryan Beckingham https://creativecommons.org/licenses/by-nc-nd/4.0
date: 2025-06-04
publication date: 2025-06-04
starting page: IPJ040625
ending page: 7
doi: 10.69631/ipj.v2i2nr71

Experimental Study of Microbial Hydrogen Consumption Rates by Oleidesulfovibrio Alaskensis in Porous Media
type: item
description: The recovery efficiency of short- and long-term cyclic operations of porous media underground hydrogen storage (UHS) is a key parameter for successful implementation, but anaerobic microbes autochthonous in the storage formation can consume hydrogen and adversely influence hydrogen recoverability and storage efficiency. Here we have experimentally measured hydrogen consumption rates by a model sulphate-reducing bacterium (Oleidesulfovibrio alaskensis G20) in drainage-storage cycles that mimic porous media UHS. Laboratory tests were performed in cylindrical sand pack columns as storage site analogues (inner diameter: 14.7 mm, length: 51.4 mm) with an average porosity of 28% at conditions of 37°C and 1.15 bara. The storage capacity (initial hydrogen saturation in place) of each sand pack was also analyzed and compared against sterilized benchmarks. We observed an exponential decay in microbial hydrogen consumption between storage cycles: 28 ± 12% hydrogen was lost during the first cycle (with a peak average rate of 1.26 ± 0.12µmol/hr/cm3), compared with 10 ± 5% in the second cycle and 7 ± 3% in the third cycle. The cumulative loss across the three cycles amounted to 15 ± 6%, even though nutrient and carbon source concentrations were adequate for full hydrogen consumption in each cycle. The reduced microbial activity after the first storage cycle was explained by the observed increase in brine pH from an initial 7.5 to 8.4 ± 0.2 at the end of the last storage cycle. We observed improvement in the average hydrogen in place saturations after the first non-sterile storage cycles. Our experimental data enhances the understanding of microbial hydrogen loss during UHS and its impact on recovery and storage efficiency.
subject: Original Research Papers
  topic: section
subject: Underground hydrogen storage
  topic: keywords
subject: pH
  topic: keywords
subject: Microbial hydrogen consumption
  topic: keywords
subject: Anaerobic sulphate reduction
  topic: keywords
subject: Storage capacity
  topic: keywords
subject: Cyclic drainage and storage
  topic: keywords
creator: Raymond Mushabe
creator: Na Liu
creator: Nicole Dopffel
creator: Geir Ersland
creator: Martin A. Fernø
rights: Copyright (c) 2025 Raymond Mushabe, Na Liu, Nicole Dopffel, Geir Ersland, Martin Fernø https://creativecommons.org/licenses/by-nc-nd/4.0
date: 2025-06-04
publication date: 2025-06-04
starting page: IPJ040625
ending page: 3
doi: 10.69631/ipj.v2i2nr72

Regional-Scale Subsurface Modeling
type: item
description: The subsurface is a critical foundation for society, providing essential resources such as water, minerals, and energy, while also offering storage capacity for resources and waste. Current subsurface use is expanding rapidly, leading to aggregated effects at regional scales ranging from tens to hundreds of kilometers. Despite their growing importance, current subsurface models remain limited to field-scale analysis and are insufficient for understanding regional scale impacts. This commentary advocates for a shift in subsurface modeling research, highlighting the importance of developing regional scale models that can assess the cumulative and interconnected effects of multiple subsurface operations. We outline a roadmap for developing the mathematical and numerical foundations necessary for regional scale subsurface analysis, highlighting the need for multiscale modeling, hybrid physics- and data-driven modeling approaches, and efficient computational tools.
subject: Invited Commentaries
  topic: section
subject: Geological
  topic: keywords
subject: Subsurface
  topic: keywords
subject: Resources
  topic: keywords
creator: Inga Berre
creator: Paola F. Antonietti
creator: Rainer Helmig
creator: Marc Hesse
creator: Jan Martin Nordbotten
rights: Copyright (c) 2025 Inga Berre, Paola Antonietti, Rainer Helmig, Marc Hesse, Jan Martin Nordbotten https://creativecommons.org/licenses/by-nc-nd/4.0
date: 2025-06-04
publication date: 2025-06-04
starting page: IPJ040625
ending page: 2
doi: 10.69631/ipj.v2i2nr79

Highlights From the New Issue of InterPore Journal
type: item
subject: Editorial
  topic: section
subject: Editorial
  topic: keywords
creator: Nima Shokri
rights: Copyright (c) 2025 Nima Shokri https://creativecommons.org/licenses/by-nc-nd/4.0
date: 2025-06-04
publication date: 2025-06-04
starting page: IPJ040625
ending page: 1
doi: 10.69631/ipj.v2i2nr88

Understanding Fracture Aperture and Permeability Evolution due to Carbonate Mineralization Utilizing 3D Printing
type: item
description: Caprock formations are a crucial part of subsurface-engineered systems. Composed largely of shale, caprocks act as natural barriers that prevent the upward migration of fluids, thereby ensuring the containment of stored substances in subsurface formations. Fractures in these formations are potential leakage pathways for stored fluids. Mineral precipitation reactions in these fractures, particularly calcite, can significantly restrict the fluid permeability, reducing leakage potential. However, predictive capabilities of mineral precipitation in fractures and associated permeability evolution are limited due to a lack of fundamental understanding of such reactions in natural samples, complicated by mineral heterogeneity and the complexity of the fracture structure. In this study, 3D-printed fracture samples are used to understand the impact of carbonate mineralization on fracture aperture and permeability evolution. Samples were printed using a digital light processing (DLP) 3D printer and commercial liquid resin. Calcite precipitation was first tested on printed 2D films before conducting plug flow column experiments aimed to understand fracture permeability changes due to mineral precipitation. Contact angle measurement and Fourier transform infrared (FTIR) spectroscopy on printed 2D films show evidence of a substantial amount of surface energy for calcite nucleation and precipitation. Surface topography analysis of printed fractured surfaces reveals comparable values, highlighting the high replicability of the printed samples. During the column experiments, the permeability reduces exponentially due to a decrease in fracture aperture. Reductions in fracture aperture estimated from effluent concentration and 3D X-ray computed tomography (CT) show comparable results. Moreover, 3D X-ray CT images suggest the impact of local flow velocities on precipitation. The insights gained from this research contribute to a deeper understanding of the permeability evolution due t…
subject: Original Research Papers
  topic: section
subject: 3D printing
  topic: keywords
subject: Rock fracture
  topic: keywords
subject: X-ray computed tomography
  topic: keywords
subject: Carbonate mineralization
  topic: keywords
subject: Permeability evolution
  topic: keywords
creator: Md. Fahim Salek
creator: Harrish Kumar Senthil Kumar
creator: Abdullah Al Nahian
creator: Samsul Mahmood
creator: Bryan S. Beckingham
creator: Kyle Schulze
creator: Lauren E. Beckingham
rights: Copyright (c) 2025 Md. Fahim Salek, Harrish Kumar Senthil Kumar, Abdullah Al Nahian, Samsul Mahmood, Bryan S. Beckingham, Kyle Schulze, Lauren E. Beckingham https://creativecommons.org/licenses/by-nc-nd/4.0
date: 2025-12-01
publication date: 2025-12-01
starting page: IPJ011225
ending page: 6
doi: 10.69631/dpd8ha46

A novel robust optimization framework based on surrogate modeling for underground hydrogen storage in depleted natural gas reservoirs
type: item
description: Underground hydrogen storage (UHS) plays a vital role in global net-zero energy systems, enabling the storage of excess renewable energy for future use. However, physical reservoir model-based optimization for UHS system design and operation is computationally expensive due to complex geological properties and well-operational controls. This study developed a novel, efficient framework for UHS stochastic optimization to address this challenge, integrating advanced compositional reservoir simulation, accurate surrogate modeling, and stochastic optimization techniques. First, a base reservoir simulation model was developed to capture compositional fluid flow, hydrogen methanation reactions, gravity segregation, hysteresis, and capillary effects. To rapidly evaluate various well controls and reservoir configurations, convolutional neural network (CNN)-bi-directional long short-term memory (BiLSTM)-Attention models were trained as surrogate models using a comprehensive dataset generated from reservoir simulations. The CNN transforms three-dimensional (3D) geological fields into one-dimensional (1D) vectors, effectively capturing spatial features. The BiLSTM network learns the temporal evolution of the input features over time by processing them in both forward and backward directions. Subsequently, the attention mechanism enhances prediction accuracy by identifying and emphasizing the most significant features at critical time steps. The well-trained surrogate models were seamlessly integrated into the stochastic optimization framework based on the genetic algorithm, aiming to maximize the net present value (NPV) from UHS projects. The results demonstrate that the surrogate model exhibits satisfactory performance in the context of prediction accuracy, computational efficiency, and scalability. Notably, the newly developed framework based on surrogate models achieves an approximate 4878-fold speedup compared to an approach relying solely on reservoir simulation, while ma…
subject: Invited Student Papers
  topic: section
subject: Underground hydrogen storage
  topic: keywords
subject: Robust optimization
  topic: keywords
subject: Surrogate modeling
  topic: keywords
subject: Deep learning
  topic: keywords
creator: Zhilei Han
creator: Zeeshan Tariq
creator: Bicheng Yan
rights: Copyright (c) 2025 Zhilei Han, Zeeshan Tariq, Bicheng Yan https://creativecommons.org/licenses/by-nc-nd/4.0
date: 2025-08-25
publication date: 2025-08-25
starting page: IPJ250825
ending page: 6
doi: 10.69631/ipj.v2i3nr69

Rubble Characteristics Associated with Room Collapse at the Waste Isolation Pilot Plant: Impact of Salt Clast Shapes and Size Distributions on the Depositional Pore System
type: item
description: The fluid transport properties of rubble associated with disposal room collapse within layered salt deposits at the Waste Isolation Pilot plant (WIPP) in southeastern New Mexico, USA are of concern when evaluating repository performance. Although properties of crushed salt have been studied extensively, salt rubble characteristics are less well known, while also being more difficult to characterize and model given the broader associated range in clast sizes. We describe a methodology for assessing rubble porosity and three-dimensional internal structure through deposition simulations that use high-fidelity renditions of clast shapes and that consider a broad range in clast sizes. We demonstrate the application of this approach using clast size and shape data that we collected on run of mine (ROM) material from WIPP, which represents the best available proxy for rubble material. Clast sizes from sieve analysis span ~1–100 mm with a mass weighted mean value of 13 mm. Simulated rubble deposits have interclast porosity values ranging from 34.1–38.6 vol% (n = 6). The largest clasts in these simulations tend to be underlain by the largest pores. Thus, although these clasts act as barriers for flow, they also are associated with highly permeable but localized flow paths. Scenarios involving alternative input configurations reveal that porosity values are highly sensitive to clast size variability (~10 vol% greater for nearly uniform compared to highly variable clast size distributions), clast shape (~10–13 vol% greater when using ROM shapes compared to spheres), and the extent of induced rearrangement (~3 vol% lower with limited rearrangement and ~10 vol% lower for extensive rearrangement). Porosity also is strongly affected by frictional coefficient values (~10 vol% lower for μ = 0.05 compared to μ = 1.0), but less so for values within the range of uncertainty for salt clasts (~2 vol% lower for μ = 0.62 compared to μ = 1.0).
subject: Original Research Papers
  topic: section
subject: Nuclear waste storage
  topic: keywords
subject: Nuclear waste disposal
  topic: keywords
subject: Waste isolation pilot plant
  topic: keywords
subject: Granular media
  topic: keywords
subject: Porosity
  topic: keywords
subject: Grain shape
  topic: keywords
subject: Polydispersity
  topic: keywords
creator: Robert Lander
creator: Edward Matteo
creator: Linda Bonnell
creator: Thomas Dewers
creator: Melisa Mills
creator: James Guilkey
creator: Chven Mitchell
creator: John Stormont
rights: Copyright (c) 2025 Robert Lander, Edward Matteo, Linda Bonnell, Thomas Dewers, Melisa Mills, James Guilkey, Chven Mitchell, John Stormont https://creativecommons.org/licenses/by-nc-nd/4.0
date: 2025-08-25
publication date: 2025-08-25
starting page: IPJ250825
ending page: 3
doi: 10.69631/ipj.v2i3nr45

Anchored Physics-Informed Neural Network for Two-Phase Flow Simulation in Heterogeneous Porous Media
type: item
description: In this study, we propose a tensorization-anchoring strategy based on adaptive architectures to accelerate the computation of Enriched Physics-Informed Neural Networks (EPINN) for two-phase flow simulations. Specifically, we design an adaptive tensorization mechanism for the adjacency matrix embedding, the activation function, and the skip-gated connection in EPINN, which collectively expand the neural network's (NN) parameter space for learning more generalized patterns. Moreover, we developed an anchoring strategy by establishing Anchors-EPINN (An-EPINN). By detaching tensorization parameters from the computational graph and anchoring weighted nodes to fixed positions, the NN can benefit from tensorized fusion effects while reducing high-dimensional matrix calculations during forward and backward propagation, thereby enhancing simulation efficiency. This approach reduces execution time by 31.47% in homogeneous cases and 27.91% in heterogeneous cases, while maintaining higher computational accuracy.
subject: Invited Student Papers
  topic: section
subject: Artificial intelligence for partial differential equations
  topic: keywords
subject: AI4PDE
  topic: keywords
subject: Simulation
  topic: keywords
subject: Two-phase flow
  topic: keywords
subject: Heterogeneous
  topic: keywords
subject: Tensorizing
  topic: keywords
subject: Adaptive architecture
  topic: keywords
subject: Neural networks
  topic: keywords
creator: Jingqi Lin
creator: Xia Yan
creator: Kai Zhang
creator: Zhao Zhang
creator: Jun Yao
rights: Copyright (c) 2025 Jingqi Lin, Xia Yan, Kai Zhang, Zhao Zhang, Jun Yao https://creativecommons.org/licenses/by-nc-nd/4.0
date: 2025-08-25
publication date: 2025-08-25
starting page: IPJ250825
ending page: 5
doi: 10.69631/ipj.v2i3nr67

Highlights From the Fourth issue of InterPore Journal
type: item
subject: Editorial
  topic: section
subject: Editorial
  topic: keywords
creator: Nima Shokri
rights: Copyright (c) 2025 Nima Shokri https://creativecommons.org/licenses/by-nc-nd/4.0
date: 2025-02-26
publication date: 2025-02-26
starting page: IPJ260225
ending page: 1
doi: 10.69631/ipj.v2i1nr77

The Importance and Challenges Associated with Multi-scale Heterogeneity for Geological Storage
type: item
description: Understanding multi-scale heterogeneity in porous media has become increasingly critical as the world transitions from fossil fuel production to geological storage of CO2 and H2 for climate change mitigation. This commentary examines why small-scale heterogeneities have taken on a heightened importance in modeling subsurface fluid migration. We identify three key factors: increased public scrutiny and stricter permitting requirements for storage projects, different risk tolerances requiring long-term monitoring, and distinct flow physics compared to traditional oil and gas extraction. Drawing from current research, we demonstrate how current models consistently underestimate CO2 plume spread, likely due to inadequate representation of small-scale heterogeneities, which will also heavily impact H2 storage in porous rocks. We review the current state of research on incorporating small-scale heterogeneities into field scale models, discuss relevant spatial scales for both CO2 and H2 storage applications, and highlight promising directions for future research in this critical area.
subject: Invited Commentaries
  topic: section
subject: Multicomponent multiphase fluid
  topic: keywords
subject: CO2 sequestration
  topic: keywords
subject: Hydrogen storage
  topic: keywords
subject: Underground hydrogen storage
  topic: keywords
subject: CCUS
  topic: keywords
subject: Carbon capture utilization and storage
  topic: keywords
creator: Catherine Spurin
creator: Catherine Callas
creator: Nihal Darraj
creator: Maja Rücker
creator: Sally Benson
rights: Copyright (c) 2025 Catherine Spurin, Maja Rücker, Sally Benson, Catherine Callas, Nihal Darraj https://creativecommons.org/licenses/by-nc-nd/4.0
date: 2025-02-26
publication date: 2025-02-26
starting page: IPJ260225
ending page: 2
doi: 10.69631/ipj.v2i1nr76

Enhancing Effective Thermal Conductivity Predictions in Digital Porous Media Using Transfer Learning
type: item
description: Porous media beneath the Earth’s surface, including aquifers, oil and gas reservoirs, and geothermal systems, play a crucial role in various natural resource management and environmental engineering applications. The study of their physical properties, particularly thermo-physical properties like effective thermal conductivity (ETC), is essential for enhancing the efficiency of subsurface engineering technologies including nuclear waste disposal, geothermal energy utilization, and underground thermal energy storage. Traditionally, determining ETC has relied on either simplified empirical models, which often lack accuracy, or sophisticated laboratory experiments, which are time-consuming and resource intensive. The advent of three-dimensional (3D) imaging technologies has enabled digital characterization of subsurface media, but direct numerical simulations of ETC remain computationally prohibitive. In response to these challenges, we introduce a novel machine learning framework that leverages transfer learning to enhance the prediction of ETC in digital rock samples. Our approach utilizes state-of-the-art convolutional neural networks (CNNs), pre-trained on extensive datasets, and applies them to various porous media samples, including Berea sandstone, Bentheimer sandstone, and Ketton limestone. By employing transfer learning, we demonstrate that our models can achieve high prediction accuracy with significantly reduced training time, computational power, and data requirements. This study highlights the potential of transfer learning to advance the efficiency and accuracy of digital rock analysis, offering a promising tool for the rapid and reliable characterization of subsurface properties.
subject: Original Research Papers
  topic: section
subject: Digital Rock Physics
  topic: keywords
subject: Machine learning
  topic: keywords
subject: Geothermal energy
  topic: keywords
subject: Effective thermal conductivity
  topic: keywords
creator: Mohamed Elmorsy
creator: Wael El-Dakhakhni
creator: Benzhong Zhao
rights: Copyright (c) 2025 Mohamed Elmorsy, Wael El-Dakhakhni, Benzhong Zhao https://creativecommons.org/licenses/by-nc-nd/4.0
date: 2025-08-25
publication date: 2025-08-25
starting page: IPJ250825
ending page: 7
doi: 10.69631/ipj.v2i3nr75

Modeling of Hydraulic Fracture Propagation in Real Heterogeneous Conglomerates from the Mahu Oilfield using the Global Cohesive Zone Method
type: item
description: Hydraulic fracturing enhances production in unconventional reservoirs but is challenged by reservoir heterogeneity, which complicates fracture propagation and reduces the efficiency of conglomerate reservoir development. The Mahu area in Xinjiang, a major petroleum reservoir in western China, is rich in oil and gas but features highly heterogeneous geological structures that complicate hydraulic fracturing and hydrocarbon extraction. In this study, we analyzed both homogeneous and heterogeneous core samples from the Mahu area. Real pore structures and gravel compositions were obtained using Computed Tomography (CT) and Quantitative Evaluation of Minerals by Scanning Electron Microscopy (QEMSCAN). The Global Pore-Pressure Cohesive Zone (GPPCZ) model was applied to study the impact of heterogeneity on fracture propagation, considering differences in the mechanical properties of the matrix, gravel, and interfaces. Results showed that fractures tend to propagate in regions with lower critical fracture energy. In heterogeneous cores, fractures were more likely to deflect around gravel and bifurcate, forming complex networks. Peak propagation velocity occurred at interface contacts, but homogeneous cores exhibited faster propagation under the same stress conditions. This work provides theoretical support for optimizing hydraulic fracturing strategies in heterogeneous conglomerate reservoirs such as the complex Mahu area.
subject: Invited Student Papers
  topic: section
subject: Hydraulic fracturing
  topic: keywords
subject: Heterogeneous conglomerate
  topic: keywords
subject: Mahu area
  topic: keywords
subject: cohesive zone method
  topic: keywords
creator: Mingyang Zhang
creator: Yanying Chen
creator: Ming Yue
creator: Ninghong Jia
creator: Weifeng Lyu
creator: Amer Alizadeh
creator: Haoran Cheng
creator: Chiyu Xie
rights: Copyright (c) 2025 Mingyang Zhang, Yanying Chen, Ming Yue, Ninghong Jia, Weifeng Lyu, Amer Alizadeh, Haoran Cheng, Chiyu Xie https://creativecommons.org/licenses/by-nc-nd/4.0
date: 2025-12-01
publication date: 2025-12-01
starting page: IPJ011225
ending page: 3
doi: 10.69631/taka2w77

A framework for simulating the partially miscible multi-component hydrocarbon fluids in porous media via the pseudo-potential lattice Boltzmann model
type: item
description: Retrograde condensation is a unique pressure-volume-temperature (PVT) behavior of partially multi-component hydrocarbon mixtures in porous media. However, some important physical properties, such as the component composition in each phase, the surface tension of the mixture, and the fluid wettability on specific rock surfaces at given temperatures, pressures, and molar compositions are difficult to evaluate dynamically in a laboratory. Previously, a multicomponent multiphase (MCMP) model was proposed to simulate the behavior of fluids composed of multiple components, such as gas condensate fluids or volatile oil fluids, where the components are partially miscible with each other. In this study, we extend the previously developed MCMP lattice Boltzmann (LB) model for partially miscible fluids by proposing a new framework to investigate the fluids’ phase behavior and flow dynamics under different phase conditions in porous media. The proposed framework integrates multiple lattice Boltzmann models to enable the convenient generation of desired wettability conditions on structural surfaces. A porous medium generated by the Voronoi tessellation (VT) was used in the case study to represent the pore-scale environment. The consistent scaling system in LB simulations was also briefly discussed. The proposed framework can enhance the understanding of the behavior of these fluids under varying conditions and can provide valuable insights into the qualitative evaluation of the pore-scale multiphase flow mechanism. Overall, this work contributes to the development of a computational framework for studying partially miscible hydrocarbon mixtures, which has important implications for the oil and gas industry.
subject: Original Research Papers
  topic: section
subject: Retrograde condensation
  topic: keywords
subject: Multicomponent multiphase fluid
  topic: keywords
subject: Psuedo-potential lattice Boltzmann models
  topic: keywords
subject: Partially miscible
  topic: keywords
creator: Zhicheng Wang
creator: Cheng Peng
creator: Luis Ayala
creator: Seyyed Hosseini
rights: Copyright (c) 2024 Zhicheng W. Wang, Cheng Peng, Luis F. Ayala, Seyyed A. Hosseini https://creativecommons.org/licenses/by-nc-nd/4.0
date: 2024-04-26
publication date: 2024-04-26
starting page: ipj260424
ending page: 5
doi: 10.69631/ipj.v1i1nr7

Modeling Nanoparticle-Stabilized Foam Flow in Porous Media Accounting for Particle Retention and Permeability Reduction
type: item
description: This work presents a model for nanoparticle-stabilized foam flow in porous media, accounting for particle retention and the resulting permeability reduction. We present a semi-analytical solution under steady-state conditions, which allows for obtaining water saturation, foam apparent viscosity, and pressure drop profiles. We study different nanoparticle concentrations (in the presence and absence of salt) using retention parameters based on experimental data. When particle retention is neglected, the sweep efficiency of the porous medium improves compared to the case without nanoparticles, even at a low nanoparticle concentration (0.1 wt%). In contrast, when retention is accounted for, this enhancement is observed only at higher concentrations (0.5 wt% and 1.0 wt%). Neglecting nanoparticle retention generally underestimates pressure drop, especially in scenarios with significant retention. However, while retained nanoparticles increase pressure by reducing permeability, the loss of suspended nanoparticles decreases pressure by reducing the foam’s apparent viscosity. Consequently, when considering both nanoparticle loss and reduced permeability, the pressure drop is higher than in models that ignore retention. In contrast, omitting retention effects on permeability, the pressure drop is lower.
subject: Invited Student Papers
  topic: section
subject: Foam
  topic: keywords
subject: Nanoparticles
  topic: keywords
subject: Porous media
  topic: keywords
subject: Particle retention
  topic: keywords
creator: Tatiana Danelon
creator: Rouhi Farajzadeh
creator: Pavel Bedrikovetsky
creator: Grigori Chapiro
rights: Copyright (c) 2025 Tatiana Danelon, Rouhi Farajzadeh, Pavel Bedrikovetsky, Grigori Chapiro https://creativecommons.org/licenses/by-nc-nd/4.0
date: 2025-05-05
publication date: 2025-05-05
starting page: IPJ260225
ending page: 3
doi: 10.69631/ipj.v2i1nr57

Biosurfactant-induced PFAS Leaching from Aqueous Film-Forming Foam (AFFF) Impacted Soil
type: item
description: The development of sustainable per- and polyfluoroalkyl (PFAS) remediation techniques is critical for the removal of contaminants from soil and water at sites impacted by aqueous film-forming foam (AFFF). This study is the first to explore the feasibility of flushing PFAS with a rhamnolipid biosurfactant solution using column testing and soil from an AFFF-contaminated site. Soil was flushed by either tap water alone or a 0.005% rhamnolipid solution. The PFAS concentrations in eluate and mass balances were compared for each test. In the first 12 pore volumes, 91% of the total perfluorooctane sulfonic acid (PFOS) flushed by the rhamnolipid solution was removed, while only 64% of PFOS was flushed in that time by tap water alone. Phosphate leached from soil and PFOS measured in the same eluate had similar concentration patterns, suggesting competitive sorption occurs with negatively charged phosphate, PFOS, and the anionic biosurfactant rhamnolipid. The flushing tests also show that there is no significant difference in flushing with a biosurfactant for PFAS compounds other than PFOS. Transport modeling confirmed that PFOS retardation (R-value) was lower with the rhamnolipid solution (R = 9.76) than with tap water (R = 22.3), which indicates that it is more efficient at removing PFOS from soil than water alone. This concept study provides insight into the release of PFAS compounds from a real contaminated saturated soil containing organic carbon, clay, and a complex mixture of PFAS. It shows promising first results for the use of biosurfactants as a sustainable flushing strategy.
subject: Original Research Papers
  topic: section
subject: PFOS
  topic: keywords
subject: Perfluorooctane sulfonic acid
  topic: keywords
subject: Rhamnolipid
  topic: keywords
subject: Soil flushing
  topic: keywords
subject: Column testing
  topic: keywords
creator: Sophie R. Hibben
creator: Alraune Zech
creator: Bas van der Grift
creator: Jacco Koekoek
creator: Sicco Brandsma
creator: Johan van Leeuwen
rights: Copyright (c) 2025 Sophie R. Hibben, Alraune Zech, Bas van der Grift, Jacco Koekoek, Sicco Brandsma, Johan van Leeuwen https://creativecommons.org/licenses/by-nc-nd/4.0
date: 2025-12-01
publication date: 2025-12-01
starting page: IPJ011225
ending page: 4
doi: 10.69631/7v8xmn98

The Influence of Density Driven Mixing Mechanisms on Ureolysis Induced Carbonate Precipitation
type: item
description: Engineered subsurface barriers with reduced porosity and permeability are critical for safe storage of CO2 and H2, for the prevention of pollutant transport, and for several other subsurface flow challenges. This study investigates enzyme-induced carbonate precipitation (EICP), a promising technique with the potential to achieve uniform precipitation in otherwise inaccessible regions, provided the mechanisms of pore-scale mixing are well understood. High-speed lab x-ray computed tomography and flow modelling were used to study the mechanisms of reagent mixing and precipitation. Our experiments show that initially, crystallization occurs homogeneously across grain surfaces, then localizes in­ pores with high enzyme concentrations. In these regions, we see crystal growth throughout the 65-minute experiment. Simulation of reagent injection produces a mixing front that matches the distribution of crystals seen in the experiments if we model mixing as a density driven flow. Overall, we see substantial reductions in simulated permeability (11-37%) depending on the efficiency of mixing. Our validated model allows us to predict and propose tailored injection strategies for optimizing mixing, bringing us closer to real-world deployment of EICP for subsurface barriers.
subject: Invited Student Papers
  topic: section
subject: MICP
  topic: keywords
subject: Microbially induced carbonate precipitation
  topic: keywords
subject: EICP
  topic: keywords
subject: Enzyme-induced carbonate precipitation
  topic: keywords
subject: Permeability
  topic: keywords
subject: High-speed XCT
  topic: keywords
subject: Tomography
  topic: keywords
creator: Philip J. Salter
creator: James M. Minto
creator: Jay Warnett
creator: Katherine J. Dobson
rights: Copyright (c) 2025 Philip J. Salter, James M. Minto, Jay Warnett, Katherine J. Dobson https://creativecommons.org/licenses/by-nc-nd/4.0
date: 2025-02-26
publication date: 2025-02-26
starting page: IPJ260225
ending page: 4
doi: 10.69631/ipj.v2i1nr59

Integration of geochemistry into a geomechanical subsurface flow simulator
type: item
description: Accurately modeling geochemical reactions in subsurface flow is essential for understanding processes such as CO2 sequestration and contaminant transport. This paper presents a new numerical subsurface simulator (MF3D-GC) that combines flow, geomechanics, and geochemistry in an integrated and fully coupled manner. The simulator's capabilities were benchmarked by comparing it with other reactive-transport simulators. An adaptive tolerance method was implemented in the geochemistry module which reduced computing time while maintaining accuracy. User-defined kinetic models were used and coupled with changes in specific surface area, fluid saturation, temperature, and pH. The unique abilities of the model to couple geomechanics with geochemistry are highlighted. Our results show the importance of carefully selecting minerals and models to balance accuracy and computational efficiency. The model is used to simulate six different classes of geochemical flow problems which include flow, dissolution, precipitation, redox reactions, and diffusion with increasing levels of complexity. The potential applications of the model to CO2 sequestration, solution mining, geothermal energy production, and contaminant transport are briefly discussed.
subject: Original Research Papers
  topic: section
subject: Geomechanics
  topic: keywords
subject: Reactive Transport Modeling
  topic: keywords
subject: Fractured Reservoir
  topic: keywords
subject: CCUS
  topic: keywords
subject: CO2 capture, utilization, and storage
  topic: keywords
creator: Miki Mura
creator: Shuang Zheng
creator: Mukul Sharma
rights: Copyright (c) 2024 Miki Mura, Shuang Zheng, Mukul Sharma https://creativecommons.org/licenses/by-nc-nd/4.0
date: 2024-11-27
publication date: 2024-11-27
starting page: IPJ271124
ending page: 4
doi: 10.69631/ipj.v1i3nr6

Inverse method to determine hydraulic conductivity from a velocity field using graph theory
type: item
description: A numerical inverse method called FlowPaths is presented to solve for the hydraulic conductivity field of an isotropic heterogeneous porous medium from a known specific discharge field (and constant-head boundary conditions). This method makes possible a new approach to reactive transport experiments, aimed at understanding the dynamic spatial and temporal evolution of hydraulic conductivity, which simultaneously record the evolving reaction and the evolving flow geometry. This inverse method assumes steady, two-dimensional flow through a square matrix of grid blocks. A graph-theoretical approach is used to find a set of flow paths through the porous medium using the known components of the specific discharge, where every vertex is traversed by at least one path from the upstream high-head boundary to the downstream low-head boundary. Darcy’s law is used to create an equation for the unknown head drop across each edge. Summation of these edge equations along each path through the network generates a set of linearly independent head-drop equations that is solved directly for the hydraulic conductivity field. FlowPaths is verified by generating 12,740 hydraulic conductivity fields of varying size and heterogeneity, calculating the corresponding specific discharge field for each, and then using that specific discharge field to estimate the underlying hydraulic conductivity field. When estimates from FlowPaths are compared to the simulated hydraulic conductivity fields, the inverse method is demonstrated to be accurate and numerically stable. Accordingly, within certain limitations, FlowPaths can be used in field or laboratory applications to find hydraulic conductivity from a known velocity field.
subject: Original Research Papers
  topic: section
subject: Inverse problem
  topic: keywords
subject: Groundwater
  topic: keywords
subject: Velocity field
  topic: keywords
subject: Graph theory
  topic: keywords
creator: Michael E. Mont-Eton
creator: Steffen Borgwardt
creator: David Mays
rights: Copyright (c) 2024 Dr. Mont-Eton, Dr. Borgwardt, Dr. Mays https://creativecommons.org/licenses/by-nc-nd/4.0
date: 2024-11-27
publication date: 2024-11-27
starting page: IPJ271124
ending page: 5
doi: 10.69631/ipj.v1i3nr30

High-fidelity experimental model verification for flow in fractured porous media
type: item
description: Mixed-dimensional mathematical models for flow in fractured media have been prevalent in the modeling community for almost two decades, utilizing the explicit representation of fractures by lower-dimensional manifolds embedded in the surrounding porous media. In this work, for the first time, direct qualitative and quantitative comparisons of mixed-dimensional models are drawn against laboratory experiments. Dedicated displacement experiments of steady-state laminar flow in fractured media are investigated using both high-resolution PET images as well as state-of-the-art numerical simulations.
subject: Original Research Papers
  topic: section
subject: Flow in fractured media
  topic: keywords
subject: Mixed-dimensional modeling
  topic: keywords
subject: PET imaging
  topic: keywords
subject: Wasserstein distance
  topic: keywords
subject: model verification
  topic: keywords
creator: Jakub Wiktor Both
creator: Bergit Brattekås
creator: Eirik Keilegavlen
creator: Martin Fernø
creator: Jan Martin Nordbotten
rights: Copyright (c) 2024 Jakub Wiktor Both, Bergit Brattekås, Eirik Keilegavlen, Martin Fernø, Jan Martin Nordbotten https://creativecommons.org/licenses/by-nc-nd/4.0
date: 2024-11-27
publication date: 2024-11-27
starting page: IPJ271124
ending page: 6
doi: 10.69631/ipj.v1i3nr31

A line search algorithm for multiphysics problems with fracture deformation
type: item
description: Models for multiphysics problems often involve significant nonlinearities. When fracture contact mechanics are incorporated, discontinuous derivatives arise at the interfaces between open and closed fractures, or between sliding and sticking fractures. The resulting system of equations is highly challenging to solve. The naïve choice of Newton’s method frequently fails to converge, calling for more refined solution techniques such as line search methods. When dealing with strong nonlinearities and discontinuous derivatives, a global line search based on the magnitude of the residual of all equations is at best costly to evaluate and at worst fails to converge. We therefore suggest a cheap and reliable approach tailored to the discontinuities. Utilizing adaptive variable scaling, the algorithm uses a line search to identify the transition between contact states for each nonlinear iteration. Then, a solution update weight is chosen to ensure that fracture cells which change state do not move far beyond the transition point. We demonstrate the algorithm on a series of test cases for poromechanics and thermoporomechanics in fractured porous media. We consider both single- and multifracture cases, and study the importance of proper scaling of variables and equations.
subject: Original Research Papers
  topic: section
subject: Porous media
  topic: keywords
subject: Line search
  topic: keywords
subject: Fracture deformation
  topic: keywords
subject: Contact mechanics
  topic: keywords
subject: Multiphysics
  topic: keywords
creator: Ivar Stefansson
rights: Copyright (c) 2024 Ivar Stefansson https://creativecommons.org/licenses/by-nc-nd/4.0
date: 2024-11-27
publication date: 2024-11-27
starting page: IPJ271124
ending page: 7
doi: 10.69631/ipj.v1i3nr33

Exploring chances and limitations of high resolution 3D-printing for guided water percolation in gas diffusion layers of polymer electrolyte fuel cells
type: item
description: In polymer electrolyte fuel cells (PEFC), the design of the porous materials is of significant interest due to their crucial role in determining the cell performance. Additive manufacturing (AM) has emerged as a feasible method for producing complex structures, offering precision and customization which cannot be achieved by conventional manufacturing techniques. This study explores the potential of high-resolution 3D-printing to produce gas diffusion layers (GDL) specifically tailored for polymer electrolyte fuel cells. We demonstrate the advantages of the method, such as its ability to create complex features in a 3-dimensional framework, as well as the challenges it faces, including the accuracy, reliability, and handling of the sample. The findings highlight both the promising capabilities and the current limitations of additive manufacturing of GDL, providing insights into future research directions and technological enhancements required to fully leverage AM to produce next generation porous materials.
subject: Original Research Papers
  topic: section
subject: 3D printing
  topic: keywords
subject: Fuel cells
  topic: keywords
subject: Polymer electrolyte fuel cells
  topic: keywords
subject: PEFC
  topic: keywords
subject: Water transport
  topic: keywords
creator: Tim Dörenkamp
creator: Felix N. Büchi
creator: Thomas J. Schmidt
creator: Jens Eller
rights: Copyright (c) 2024 Tim Dörenkamp, Felix N. Büchi, Thomas J. Schmidt, Jens Eller https://creativecommons.org/licenses/by-nc/4.0/
date: 2024-11-27
publication date: 2024-11-27
starting page: IPJ271124
ending page: 3
doi: 10.69631/ipj.v1i3nr43

The soil plastisphere: The nexus of microplastics, bacteria, and biofilms
type: item
description: Bacteria are one of the oldest life forms on Earth, dating back to more than 3.5 billion years ago. They control the global cycling of carbon, nitrogen, and oxygen. They provide plants, fungi and other organisms with the necessary nutrients and elements. They help us digest our food, protect us against pathogens, and even affect our behavior. Microplastics, however, have disrupted the bacterial ecosystems across the globe, from the soil to the oceans. Microplastics are tiny plastic particles formed as a result of the breakdown of the consumer products and plastic waste. Due to their stability and persistence, they can travel long distances in the soil and subsurface environments, ultimately making their way to the water resources, rivers, and oceans. In this journey, they interact with bacteria and other micro/macro-organisms, become ingested or colonized, and act as carriers for contaminants and pathogens. How and whether bacteria adapt to these new microplastic-rich ecosystems are open questions with far-reaching implications for the health of our planet and us. Therefore, there is an urgent need for improving our fundamental understanding of bacterial interactions with the microplastics in complex environments. In this commentary, we focus on the nexus of bacteria, biofilms, and microplastics, also known as the “plastisphere”, and discuss the challenges and opportunities.
subject: Invited Commentaries
  topic: section
subject: Microplastics
  topic: keywords
subject: Biofilms
  topic: keywords
subject: Bacterial ecosystems
  topic: keywords
subject: Plastisphere
  topic: keywords
creator: Amir A. Pahlavan
rights: Copyright (c) 2024 Amir Pahlavan https://creativecommons.org/licenses/by-nc-nd/4.0
date: 2024-11-27
publication date: 2024-11-27
starting page: IPJ271124
ending page: 2
doi: 10.69631/ipj.v1i3nr50