GD10.1 | Advances in Numerical Modelling of Geological Processes: Methods, Applications and Tooling
Advances in Numerical Modelling of Geological Processes: Methods, Applications and Tooling
Convener: Ludovic RässECSECS | Co-conveners: Boris Kaus, Ivan UtkinECSECS, Thibault Duretz, Dave May
Orals
| Wed, 17 Apr, 16:15–18:00 (CEST)
 
Room -2.21
Posters on site
| Attendance Wed, 17 Apr, 10:45–12:30 (CEST) | Display Wed, 17 Apr, 08:30–12:30
 
Hall X1
Orals |
Wed, 16:15
Wed, 10:45
Geological and geophysical data sets convey observations of physical processes governing the Earth’s evolution. Such data sets are widely varied and range from the internal structure of the Earth, plate kinematics, composition of geomaterials, estimation of physical conditions, dating of key geological events, thermal state of the Earth to more shallow processes such as natural and “engineered” reservoir dynamics in the subsurface.

The complexity in the physics of geological processes arises from their multi-physics nature, as they combine hydrological, thermal, chemical and mechanical processes. Multi-physics couplings are prone to nonlinear interactions ultimately leading to spontaneous localisation of flow and deformation. Understanding the couplings among those processes therefore requires the development of appropriate numerical tools.

Integrating high-quality data into physics-based predictive numerical simulations may lead to a constructive workflow and allow to further constrain unknown key parameters within the models. Innovative inversion strategies, linking forward dynamic models with observables, and combining PDE solvers with machine-learning via differentiable programming is therefore an important research topic that will improve our knowledge of the governing physical parameters.

We invite contributions from the following two complementary themes:

#1 Computational advances associated with
- alternative spatial and/or temporal discretisation for existing forward/inverse models
- scalable HPC implementations of new and existing methodologies (GPUs / multi-core)
- solver and preconditioner developments
- Combining PDEs with AI / Machine learning-based approaches (physics-informed ML)
- Automatic differentiation (AD) and differentiable programming
- code and methodology comparisons (“benchmarks”)

#2 Physics advances associated with
- development of partial differential equations to describe geological processes
- inversion strategies and adjoint-based modelling
- numerical model validation through comparison with observables (data)
- scientific discovery enabled by 2D and 3D modelling
- utilisation of coupled models to explore nonlinear interactions

We plan on a special topical issue for the research output presented in this session in the EGU journal of Geoscientific Model Development (GMD) https://www.geoscientific-model-development.net.

Orals: Wed, 17 Apr | Room -2.21

Chairpersons: Ludovic Räss, Thibault Duretz
16:15–16:16
Multi-physics modelling
EGU24-18807
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ECS
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solicited
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On-site presentation
Arne Spang et al.
EGU24-16931
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On-site presentation
Yuan Li et al.
Methodological advances
EGU24-10708
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On-site presentation
Beatriz Martinez Montesinos et al.
EGU24-16244
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ECS
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On-site presentation
Albert de Montserrat Navarro et al.
17:56–18:00

Posters on site: Wed, 17 Apr, 10:45–12:30 | Hall X1

Display time: Wed, 17 Apr 08:30–Wed, 17 Apr 12:30
Chairpersons: Boris Kaus, Ivan Utkin, Dave May
EGU24-19607
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ECS
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On-site presentation
Samuel Omlin et al.
EGU24-19212
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ECS
|
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On-site presentation
Mathis Bergogne et al.
EGU24-6508
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ECS
|
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On-site presentation
Eugenio D'Ascoli et al.
EGU24-8080
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On-site presentation
Thibault Duretz and Laetitia Le Pourhiet
EGU24-11777
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ECS
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On-site presentation
Jon Bryan May et al.
EGU24-14445
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On-site presentation
Eric Hutton et al.
EGU24-15096
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On-site presentation
Zenan Huo et al.
EGU24-15998
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On-site presentation
Marcel Thielmann et al.
EGU24-16725
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Highlight
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On-site presentation
Boris Kaus et al.
EGU24-18423
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ECS
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On-site presentation
Timothy Gray et al.
EGU24-12283
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On-site presentation
Anton A. Popov et al.