Innovative forward and inverse modeling techniques, advances in numerical solvers and the ever-increasing power of high-performance compute clusters have driven recent developments in inverting seismic and other geophysical data to reveal properties of the Earth at all scales.

The interpretation of single disciplinary geophysical field data often allows for various, equally probable models that may not always sufficiently discern plausible hypotheses that are challenged. Therefore, co-validation of data from different disciplines is critical.

This session provides a forum to present, discuss and learn the state-of-the-art in computational seismology, non-linear and joint inversion, uncertainty quantification and collaborative interpretation.

Invited Speakers:
Christel Tiberi, "Joint inversion and collaborative interpretations in complex geodynamical context";
Andrew Curtis, "Variational Probabilistic Tomography";
Yann Capdeville, "Intrinsic non-uniqueness of the acoustic full waveform inverse problem"

Numerical modeling of earthquakes provides new approaches to apprehend the physics of earthquake rupture and the seismic cycle, seismic wave propagation, fault zone evolution and seismic hazard assessment.
Recent advances in numerical algorithms and increasing computational power enable unforeseen precision and multi-physics components in physics-based earthquake simulation but also pose challenges in terms of fully exploiting modern supercomputing infrastructure, realistic parameterization of simulation ingredients and the analysis of large synthetic datasets while advances in laboratory experiments link earthquake source processes to rock mechanics.
This session aims to bring together modelers and data analysts interested in the physics and computational aspects of earthquake phenomena and earthquake engineering. We welcome studies focusing on all aspects of seismic hazard assessment and the physics of earthquakes - from slow slip events, fault mechanics and rupture dynamics, to wave propagation and ground motion analysis, to the seismic cycle and inter seismic deformation - and studies which further the state-of-the art in the related computational and numerical aspects.

Public information:
Welcome to session SM7.3 "Physics-based earthquake modeling and engineering”.
Our session aims to bring together modelers and data analysts interested in the physics and computational aspects of earthquake phenomena and earthquake engineering.
We are looking forward to discussing uploaded displays in display number order as appearing to your right. Presenters please prepare a short introduction, then we will discuss questions. We will end with an open discussion at the end of the session.

We stick with the simple EGU text chat during all the session increasing accessibility. Please take advantage by asking lots of questions, and, importantly, post comments beneath displays!

Geological and geophysical data sets are in essence the output of physical processes governing the Earth’s evolution. Such data sets are widely varied and range from the internal structure of the Earth (e.g. seismic tomography), plate kinematics (e.g. GPS), composition of geomaterials (e.g. petrography), estimation of physical conditions and dating of key geological events (e.g. thermobarometry), thermal state of the Earth (e.g heat-flow measurements) to more shallow processes such as natural and “engineered” reservoir dynamics and waste sequestration in the subsurface (e.g. seismic imaging).

Combining the abundant data to process-based numerical models fosters our understanding of the dynamical Earth. Process-based models are powerful tools to predict the evolution of complex natural systems resolving the feedbacks among various physical processes. Integrating high-quality data into direct numerical simulations leads to a constructive workflow to further constrain the key parameters within the models. Innovative inversion strategies, linking forward dynamic models with observables, are topics triggering a growing interest within the community.

The complexity of geological systems arises from their multi-physics nature, as they combine hydrological, thermal, chemical and mechanical. Multi-physics couplings are prone to nonlinear interactions ultimately leading to spontaneous localisation of flow and deformation. Understanding the couplings among those processes requires the development of appropriate tools to capture spontaneous localisation and represents a challenging though essential research direction.

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
- AI / Machine learning-based approaches
- 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
- 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