Research theme: Multiscale Modelling and Flow Simulation

Multiscale Modelling and Flow Simulation

Theme lead: Dr. Steven McDougall

Research project

• Novel Mathematical Approaches for Multiscale Modelling of Three-Phase Porous Media Flow

Current activities

1. Multiscale modelling of migration regimes associated with CO₂ storage
2. Pore-to-core simulation of water injection into heavy oils
3. Analysis and modelling of steady- and unsteady-state water relative permeability
4. Scale deposition at the pore-scale
5. Guidance cues and blood perfusion in the developing retinal vasculature
6. Diabetic wounds and the impact of obesity
7. The role of connexins in tissue growth and bone implants
8. Multiscale simulation of chemotherapy protocols

Summary

Our group uses a wide range of innovative modelling techniques to understand the fundamental recovery mechanisms governing multiphase displacements in subsurface reservoirs. Techniques range from advanced pore-scale modelling approaches – including pore reconstruction protocols and the integration of multi-scale pore systems – through core-scale simulation of a variety of SCAL measurements, to the application of novel multi-grid methodologies at the reservoir scale. The modelling work is regularly informed by related experimental activity from several IPE Themes, including HRM micromodel experiments and HRM/PC coreflood data.

The current three-phase network models we have developed are considered the most advanced of their type, particularly in relation to the physics of wetting films and layers (which assist in the drainage of oil). Depressurisation pore-scale physics has been extensively studied and 3D network models have been developed for analysing pressure depletion in light and heavy oil systems, the first to explicitly couple non-equilibrium PVT behaviour, gravitational migration of discontinuous gas structures and viscous forces.  Network modelling has also been used to examine flow in biological systems (flow in vascular beds, tumours, and retinae) and has highlighted a number of important new targets for therapeutic intervention. 

A framework for the classification of digital rocks by machine learning is currently being constructed to produce reliable and robust predictions of micro-to-macro relationships – it is underpinned by recent advances in support vector machine learning. Additionally, a number of new, highly efficient lattice Boltzmann simulation techniques have been developed at IPE for examining flow through low-porosity rocks and multi-scale interconnected pore systems.

Many of these modelling approaches have been informed by a powerful, rapid reconstruction methodology (PAM: Pore Architecture Modelling), that facilitates the  creation of multi-scale 3-D in silico porous media from a range of 2-D cross-sectional data.