Topics

The Technical Committee invite practitioners, innovators and industry experts to contribute to this workshop and share their achievements and challenges, lay out big innovative ideas and seek new alliances to jointly develop a road for the future.

Contributors are welcome to submit abstracts of 2-4 pages in length. Submission for posters & oral presentations is welcome on all topics. Professionals, Bachelor, Master or PhD students are invited to share their work.

Abstracts should be submitted via the EAGE website using the downloadable template

Please submit abstracts on the following topics: 

Method development 1: Formulations

• ML as inversion engine: is end-to-end the goal?
• Physics-guided networks: neural operators and PINNs
• ML and multiparameter/multiphysics inversion
• Can we use ML to compensate for modelling deficiencies?
• Does ML make sense for modelling?
• Unsupervised/semi-supervised methods to leverage available labels

Method development 2: Uncertainty Quantification

• Do ML variational methods outperform MCMC
• ML for Bayesian inversion - computing priors
• ML for intelligent regularization
• Can ML bring UQ more naturally into FWI outputs?

Computation

• HPC for ML - parallelisation models for moving to scale
• Handling seismic data volumes in ML
• Cloud computing for ML-FWI - the good and the bad

Applications 1: Pre-processing and initialization

• Pre-processing: spectral extrapolation and denoising
• Alleviating scarcity of labelled data
• Initial model building
• Can FWI-ML be trained with synthetic data?
• Post-processing: interpretation

Applications 2: field data issues and case studies

• Applications and benchmarking
• Open data - availabilities and opportunities
• QC and validation
• VMB, characterization and monitoring
• Beyond O&G: applications for the energy transition.

Submit your paper here!