GD8.1 | PICO
Advances in Numerical Modelling of Geological Processes
Co-organized as EMRP1.81/SM7.6/TS11.6
Convener: Thibault Duretz | Co-conveners: Boris Kaus, Dave May, Ludovic Räss
| Wed, 10 Apr, 14:00–15:45
PICO spot 3

Geological and geophysical data provide quantitative information which permit the advancement of our understanding of the present, and past, interior of the Earth. Examples of such processes span from the internal structure of the Earth, plate kinematics, composition of geomaterials, estimation of physical conditions and dating of key geological events, thermal state of the Earth to more shallow processes such as reservoir geomechanics, or nuclear waste storage.

A quantitative understanding of the dynamics and the feedbacks between geological processes requires the integration of geological data with process oriented numerical models. Innovative inverse methods, linking forward dynamic models with observables, are topics of growing interest within the community. Improving our knowledge of the governing physical parameters can thus be addressed while reconciling models and observables.

Resolving the interactions between various processes occurring at scales differing from each other over several orders of magnitude in space and time represents a computational challenge. Hence, simulating such coupled, nonlinear physics-based forward models requires both the development of new approaches and the enhancement of established numerical schemes.

The majority of geological processes combine several physical mechanisms such as hydrological, thermal, chemical and mechanical processes (e.g. thermo-mechanical convection). Understanding the tight couplings among those processes represents a challenging and essential research direction. The development of novel numerical modelling approaches, which resolve multi-physics feedbacks, is vital in order to provide accurate predictions and gain deeper understanding of geological processes.

We invite contributions from the following two complementary themes:

#1 Computational advances associated with
- alternative spatial and/or temporal discretisations for existing forward/inverse models
- scalable HPC implementations of new and existing methodologies (GPUs / multi-core)
- solver and preconditioner developments
- code and methodology comparisons (“benchmarks”)
- open source implementations for the community

#2 Physics advances associated with
- development of partial differential equations to describe geological processes
- inverse and adjoint-based methods
- numerical model validation through comparison with natural observations and geophysical data
- scientific insights enabled by 2D and 3D modelling
- utilisation of coupled models to address nonlinear interactions