Advances in Fluid Transport for Sustainable Energy and Environment in Subsurface Systems

Dear Colleagues,

Subsurface systems are a key element in energy transition and play an important role in the sustainability of energy and environment. They provide multiple functions, including the extraction of geo-energy such as geothermal and hydrocarbons, the mining of rare earth elements, and the large-scale geological storage of carbon dioxide (CO₂) and hydrogen. The use of a subsurface system for the affordable, clean extraction of resources and the efficient mitigation of climate change requires deep understanding of fluid transport coupled with multi-physics in complex permeable rocks.

This Special Issue aims to present and disseminate the most recent advancements related to fluid flows and transport in different subsurface porous media that will benefit a variety of applications, from the sustainable extraction of underground resources to environment mitigation.

Topics of interest for publication include, but are not limited to:

• Understanding fluid transport for cleaner geo-energy production, including geothermal recovery, hydrocarbon recovery, and lithium extraction from reservoir water;
• Understanding fluid transport for large-scale hydrogen geological storage in depleted oil and gas reservoirs, salt domes, aquifers, and excavated rock caverns;
• Understanding fluid transport for the mitigation of the environment, including CO₂ sequestration in saline aquifer and depleted oil and gas reservoirs, methane leakage from orphaned wells, and contaminate transport in soil and aquifer systems;
• Fluid transport in homogenous, heterogeneous, and fractured rocks;
• Fluid flows involving multi-physics such as single (miscible) and multiphase (immiscible) displacements;
• Fluid flows coupled with heat transfer;
• Reactive flows;
• Fluid flows coupled with solid deposition and migration;
• Recent experimental studies;
• Classical physics-based modelling for fluid flows;

New approaches using artificial intelligence and machine learning methods.

Dr. Qingwang Yuan
Dr. Bowen Ling
Guest Editors

Manuscript Submission Information

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Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 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.