Evidence map›Paper›PMID 42125175›Full record

ArticleEnergy & fuels : an American Chemical Society journal2026

Coupled Hysteresis and Variogram-Controlled Heterogeneity Effects on Underground Hydrogen Storage in Saline Aquifers.

Abdolali Mosallanezhad, Amir Jahanbakhsh, Azim Kalantariasl, M Mercedes Maroto-Valer

Abstract read
In one paragraph

Article in Energy & fuels : an American Chemical Society journal, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

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0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Abdolali MosallanezhadResearch Centre for Carbon Solutions (RCCS), School of Engineering and Physical Sciences, Heriot-Watt University, Edinburgh EH14 4AS, U.K.ORCID https://orcid.org/0000-0002-2317-9969
Amir JahanbakhshResearch Centre for Carbon Solutions (RCCS), School of Engineering and Physical Sciences, Heriot-Watt University, Edinburgh EH14 4AS, U.K.
Azim KalantariaslDepartment of Petroleum Engineering, School of Chemical and Petroleum Engineering, Shiraz University, Shiraz 7134851154, Iran.
M Mercedes Maroto-ValerResearch Centre for Carbon Solutions (RCCS), School of Engineering and Physical Sciences, Heriot-Watt University, Edinburgh EH14 4AS, U.K.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Hydrogen is projected to be a critical component in worldwide efforts to transition toward low-carbon energy systems. As hydrogen generation capacities rise to meet climate goals, parallel advancements in scalable, high-efficiency storage infrastructure are urgently required. Accurately assessing the storage capacity of saline aquifers is critical for deploying underground hydrogen storage (UHS) on the scale necessary for the energy transition. Conventional assessments, however, often rely on static reservoir properties, such as porosity and permeability, which fail to capture the complex realities of subsurface fluid behavior. This study demonstrates that neglecting crucial dynamic parameters, such as hysteresis, leads to a significant overestimation of recoverable gas. Our numerical simulations reveal that relative permeability hysteresis is one of the dominant factors, causing substantial residual gas trapping that reduces the hydrogen recovery factor by nearly 30% in the initial cycles. The heterogeneous nature of the reservoir adversely affects hydrogen storage operations by promoting preferential flow paths, reducing sweep efficiency, and leading to uneven hydrogen distribution and storage within porous media. Optimal selection of the production rate is crucial for balancing the hydrogen recovery and water management. In heterogeneous models, by optimizing flow rates, recovery improved by ∼10% and water production decreased by ∼20%, underscoring the need for reservoir-specific flow-control strategies. This research underscores the imperative of a dynamic, physics-based approach to designing efficient and cost-effective UHS projects. Moving beyond static assumptions is not just an improvement; it is essential for unlocking the true potential of saline aquifers for large-scale hydrogen storage.

Identifiers

PMID42125175
PMCPMC13158903

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.