The doctoral research Raymond is doing is part of the research work done at the Centre for Sustainable Subsurface Resources (CSSR-WP2) in collaboration with University of Bergen. The team on work package two (WP2) focusses on short-cycle (hours/days/months) energy storage in porous media, where subsurface hydrogen storage is the key topic. Raymond will experimentally quantify hydrogen flow and distribution in porous media at the core by combining traditional core flooding test with modern in-situ visualisation methods (MRI and PET). Hydrogen saturation functions will be measured at a range of conditions (varying pressure, temperature, injection and withdrawal rates). Focus on microbial activity on hydrogen storage will follow the two steps above at a core scale. At this stage imaging methods MRI and PET will be vital. Correlation and upscaling between core and pore scale observations will then follow. And finally data from experimental results will be provided to the simulation team as a validation datset or quality simulator input data . 

Fluent in English, good in bokmål

Academic lecture

• Mushabe, Raymond; Minougou, Wendpanga Jean Donald; Landa-Marbán, David et al. (2024). Predicting ultimate hydrogen production and residual volume during cyclic underground hydrogen storage in porous media using machine learning. (external link)
• Mushabe, Raymond; Liu, Na; Dopffel, Nicole et al. (2024). Quantitative analysis of anaerobic microbial hydrogen consumption in porous media. (external link)
• Mushabe, Raymond; Ersland, Geir; Liu, Na et al. (2024). Combining traditional methods and state of the art MRI-PET imaging to extract the kinetics of microbial hydrogen consumption in porous media at a core scale. (external link)
• Mushabe, Raymond; Liu, Na; Dopffel, Nicole et al. (2024). Measurements of anaerobic microbial hydrogen consumption in porous media: Rates and effects. (external link)
• Mushabe, Raymond; Brattekås, Bergit; Liu, Na et al. (2023). In-situ visualization of microbial hydrogen consumption in a porous medium using high-resolution PET-MRI. (external link)
• Mushabe, Raymond; Brattekås, Bergit; Liu, Na et al. (2023). How to optimize the potential of MRI-PET in conducting experimental reservoir physics research relevant for underground hydrogen storage: Methods and analysis. (external link)
• Mushabe, Raymond; Brattekås, Bergit; Liu, Na et al. (2023). Visualisation of biomass in porous media. (external link)

Lecture

• Sandve, Tor Harald; Kane, Birane; Landa-Marbán, David et al. (2023). Machine Learning for near well Models in CCS/CCUS/H2 Storage Simulations​. (external link)

Poster

• Mushabe, Raymond; Minougou, Wendpanga Jean Donald; Landa-Marbán, David et al. (2023). Predicting ultimate hydrogen production and residual volume during cyclic underground hydrogen storage in porous media using machine learning. (external link)
• Mushabe, Raymond; Brattekås, Bergit; Liu, Na et al. (2023). In-situ visualization of microbial hydrogen consumption and growth in a porous medium using high-resolution PET-MRI. (external link)

Academic article

• Mushabe, Raymond; Azizov, Ilgar; Adejumo, Gbadebo Nafiu et al. (2022). Ion Composition Effect on Spontaneous Imbibition in Limestone Cores. (external link)

See a complete overview of publications in Cristin.

https://pubs.acs.org/doi/10.1021/acs.energyfuels.2c02101

https://hdl.handle.net/11250/2788857