9 May 2022:
The programme for the day will offer a series of presentations across various aspects of machine learning applications to reservoir uncertainty modelling workflows: seismic interpretation, geological pattern recognition from outcrops, fluvial facies modelling with GANs, dynamic data integration into fracture reservoir modelling and multi-objective optimisation of reservoir production to tackle CO2 emission targets.
In the afternoon we will present a new HWU JIP initiative on Uncertainty quantification of geomechanically sensitive reservoirs and welcome interested companies to join.
- Introduction. Vasily Demyanov
- Seismic auto-segmentation with point cloud clustering evaluation & optimisation, Quentin Corlay
- Learning geological patterns from outcrops by using computer vision methods, Athos Nathanail
- A GAN-based Workflow for 3D Fluvial Facies Modelling, Chao Sun
- Integrating geological uncertainty and dynamic data into modelling procedures for fractured reservoirs, Bastian Steffens, PhD overview
- Well Grouping and Control Optimisation for CO2 Emission Offset in Field Production,
Amirsaman Rezaeyan - Uncertainty quantification of geomechanically sensitive reservoirs – a new JIP overview, Dan Arnold