Inverse problems for deep geothermal energy forecasting: adaptive Markov chain Monte Carlo strategies (FPI 2023) per al CIMNE

Functions to be developed:

A doctoral thesis in the framework of the research project entitled DeepGeo - Computational Engineering Supporting Future Clean Energy via Deep Geothermal Prospection, with reference PID2023-153082OB-I00. Principal investigators: Prof. Sergio Zlontik and Prof. Pedro Díez Mejia.

During the last 20 years the Solid Earth community pursues massive data-driven simulations and joint inversions for the physical state of the Earth's interior. In this thesis we want to explore model reduction techniques that seek low-dimensional representations of parameters. The goal is producing an adaptive parameterisation effectively reducing the number of parameters to be identified.

Tasks to be performed:

  • Get familiar with the methods for deep geothermal forecasting, lithospheric structure and probabilistic inversions.
  • Get familiar with lithospheric dynamics including thermal, mechanical, rheological behaviors; Bayesian methods, in particular Markov chain Metropolis-Hastings.
  • Understand model order reduction techniques and to integrate them within a Bayesian solver.
  • Understand Reduced Basis; uncertainty quantification and error assessment; adaptive strategies (e.g. active subspaces);
  • Propose a methodology to accelerate the probabilistic inversion algorithm and facilitate efficient sampling in the reduced parameter space. The result will be a tractable procedure for the solution of statistical inverse problems involving partial differential equations with high-dimensional parametric input spaces.

Additional information about the project is available at: CIMNE RTD Project: DeepGeo

The candidate will join the research group of Credible data-driven Models: Credible High Fidelity and Data Driven Models

This contract is financed by the announcement of Proyectos de Generación de Conocimiento 2023 of the Ministerio de Ciencia, Innovación y universidades: Proyectos de Generación de conocimiento 2023| Agencia Estatal de Investigación (aei.gob.es)

The deadline for registration to the offer ends on November 22nd, 2024 at 12 noon.

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