[Geodynamics] GeoBerlin 2023 - Session 4.7 Data-driven digital twins of the subsurface and their applications

[Judith Bott]

Dear colleagues,

You are very welcome to contribute to our session "*Data-driven digital 
twins of the subsurface*" at the upcoming *GeoBerlin 2023* (3-8 Sept).

We would appreciate if you can help us spread this information within 
your networks.

Thank you very much in advance!

Judith

[On behalf of the conveners team]



	

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**4.7 Data-driven digital twins of the subsurface and their applications *
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	Dear colleague,

We would liketo cordially invite you to submit an abstract to the 
*session 4.7* in the frame of the *GeoBerlin 2023* conference.

Here, you will have the opportunity of presenting a *talk* or a *poster*.

Each abstract will have a DOI and will be published in the *DGGV media 
library*.

Additionally, students can take part on the *students' best poster award!*

*Abstract submission deadline**: Wednesday, 3 May 2023*

*More information* <https://protect-au.mimecast.com/s/PddDCmO5glupj37qYiGbl4g?domain=geoberlin2023.de>

Looking forward to your contributions,

Ángela María Gómez-García,Judith Bott, Ajay Kumar,
Magdalena Scheck-Wenderoth and Mikhail Tsypin.

*Session description*

Subsurface utilization and the assessment of associated potential 
seismic hazard require robust knowledge of the rock physical properties, 
as well as the processes controlling state variables, pressure and 
temperature, from reservoir to lithospheric scale. The interpretation of 
subsurface observations is often non-unique due to the scarce data or 
inherent non-linearity. Integration of different types of data (e.g., 
geological, well-log, active and passive seismic, potential field, GNSS, 
InSAR data) and their joint inversion allows to narrow down the solution 
space, and help to build robust and reliable models of the solid Earth, 
useful for process simulations and predictions beyond the spatiotemporal 
restrictions of direct observations.

The data integration process, however, is challenging. Direct 
relationships between different physical properties are mostly 
empirical, realistic models are complex, and inversions (including 
sensitivity tests) are computationally expensive. Such data-driven 
integrative digital twins of the subsurface are the basis for various 
studies targeted at, for instance, geothermal energy, groundwater 
utilization, energy and waste storage, mining, and even fundamental 
geodynamic questions. With this session, we would like to bring together 
people from various disciplines to exchange their experience in 
across-scales data integration methods and resulting applications. In 
particular, we invite contributions that present multidisciplinary data 
management and visualization software, as well as innovative methods for 
joint inversion and interpretation.

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