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Reference Number EP/J02080X/1
Title Porous Media Processes and Mathematics (PM)^2
Status Completed
Energy Categories FOSSIL FUELS: OIL, GAS and COAL(CO2 Capture and Storage, CO2 storage) 10%;
RENEWABLE ENERGY SOURCES(Geothermal Energy) 5%;
FOSSIL FUELS: OIL, GAS and COAL(Oil and Gas, Enhanced oil and gas production) 10%;
HYDROGEN and FUEL CELLS(Fuel Cells) 5%;
NOT ENERGY RELATED 70%;
Research Types Basic and strategic applied research 100%
Science and Technology Fields PHYSICAL SCIENCES AND MATHEMATICS (Applied Mathematics) 75%;
ENVIRONMENTAL SCIENCES (Earth Systems and Environmental Sciences) 25%;
UKERC Cross Cutting Characterisation Not Cross-cutting 100%
Principal Investigator Professor G Lord
No email address given
Sch of Mathematical and Computer Science
Heriot-Watt University
Award Type Standard
Funding Source EPSRC
Start Date 28 January 2013
End Date 27 January 2016
Duration 36 months
Total Grant Value £145,471
Industrial Sectors Energy
Region Scotland
Programme NC : Engineering, NC : Maths
 
Investigators Principal Investigator Professor G Lord , Sch of Mathematical and Computer Science, Heriot-Watt University (99.999%)
  Other Investigator Dr S Geiger-Boschung , Institute Of Petroleum Engineering, Heriot-Watt University (0.001%)
  Industrial Collaborator Project Contact , Schlumberger Cambridge Research Ltd (0.000%)
Project Contact , Computer Modeling Group CMG Ltd, Canada (0.000%)
Web Site
Objectives
Abstract Natural and industrial porous media is key to a wide variety of traditional and emerging engineering applications, including but not limited to oil and gas extraction from geological reservoirs, carbon capture and storage, geothermal reservoir engineering, soil sciences, groundwater remediation and protection, biological engineering, food processing, fuel cells, nano-technology, construction engineering, wood processing and printing.We are proposing the formation of a UK wide research network focussed on porous media flow which will sit at the interface between engineering, applied mathematics, applied probability and scientific computing. The overall aim of the network is to transfer techniques, models and scientific insights between engineering and mathematics, as well as promote mobility between academia and industry. Initially, the key areas of scientific research will include: large scale computational modelling, fundamental pore-scale physics, inverse problems and history matching, reservoir simulations, soil science and shallow ecosystems, theoretical biology and physiology, groundwater remediation, subsurface storage of greenhouse gases and nuclear waste, uncertainty quantification, homogenisation and multi-scale methods, visualization, numerical analysis and random field modelling
Publications (none)
Final Report (none)
Added to Database 19/03/13