Monitoring of Subsurface Fluid Flow Based on Computational Models

Dear Colleagues,

Fluid flow directs a wide range of critical processes in the subsurface including, the build-up of earthquakes and volcanoes, groundwater resources, the extraction of hydrocarbons for energy, and, of late, CO₂ sequestration and subsurface energy storage. To reduce the uncertainty and risk associated with these processes, the monitoring of subsurface fluid flows is crucial and requires integrating typically incomplete and inaccurate information from available observations with models representing the established physics through optimized workflows. Significantly, recent advancements in computational methodologies and the continuous evolution of observational techniques hold great potential for optimizing current monitoring strategies and workflows. Furthermore, by enhancing the methodologies used for exploiting the relationship between observations and models, we can obtain more accurate predictions of the fluid flow processes and, therefore, reduced risks.

This Special Issue will outline the latest research trends and important methodological advancements related to the monitoring of subsurface fluid flow. We invite original research articles and case studies within areas including, but not limited to, the following:

• Data assimilation methods;
• Geophysical inversion;
• Multi-physics inversion;
• Hybrid methods combining data assimilation and generative AI;
• Multifidelity methods;
• Uncertainty quantification and risk assessment;
• Fluid flow modelling;
• Value of information analysis.

This Special Issue will provide new and valuable insights that contribute to the advancement and understanding of subsurface fluid flow within a variety of applications.

Dr. Martha Lien
Dr. Trond Mannseth
Guest Editors

Manuscript Submission Information

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• machine learning
• multi-physics inversion
• uncertainty quantification
• data assimilation
• numerical modelling
• subsurface flow simulations
• geophysical data
• bayesian methods
• artificial intelligence
• seismics
• gravimetry
• electromagnetics