The subsurface system can act as a large-scale, low-cost and safe system for huge storage for either energy or waste, which provides provide important solutions to carbon management in order to tackle the global climate crisis and meet the Net-Zero target. However, the high degree of heterogeneity and the complexity of the rocks and the dynamic environment make the characterisation and prediction highly challenging. This project aims to use state-of-the-art digital rock techniques including multi-scale and 4D (3D+time) X-ray tomography, Focused Ion Beam Scanning Electron Microscopy, Transmission Electron Microscopy, combined with reactive transport modeling and machine learning to provide a comprehensive understanding of the subsurface system and its behaviours under the complex conditions (temperature, pressure, chemistry and multi-phase flow). The focuses of this project are the nm-scale to km-scale heterogeneity of rocks, the reactive transport of the fluids in porous media and the complex thermo-hydro-mechanical-chemical-microbiological (THMCM) processes in the subsurface over time. The real-world applications can be selected from one of the followings: 1) geological carbon sequestration, 2) underground hydrogen storage, 3) geothermal and aquifer heat storage, 4) nuclear waste disposal, 5) other relevant subsurface applications. The methods used in this project can be one or more of the following options: 1) experiments, 2) numerical modelling, 3) machine learning.
The student will be provided full training on the 3D/4D image acquisition and processing and have access to National X-ray Computed Tomography Facility (https://nxct.ac.uk/), National institute for Advanced materials research and innovation (https://www.royce.ac.uk/), and Diamond light source (www.diamond.ac.uk).
More details can be found here (https://www.research.manchester.ac.uk/portal/en/researchers/lin-ma(87434d6c-9ea2-4291-92a2-481374db4fe5)/projects.html?period=running) and can be further discussed via email or video calls.
Strong applicants will be recommended to university scholarship competition.
Entry Requirements
Applicants should have or expect to achieve at least a 2.1 honours degree (or equivalent) in earth sciences, environmental sciences, petroleum engineering, chemical engineering, civil engineering, mechanical engineering, or machine learning.
Successful candidates will join the ‘Digital Rock Manchester’ group and will be enrolled in the 3.5-year Ph.D. program of the School of Chemical Engineering at University of Manchester.
Funding
At Manchester we offer a range of scholarships, studentships and awards at university, faculty and department level, to support both UK and overseas postgraduate researchers.
For more information, visit our funding page or search our funding database for specific scholarships, studentships and awards you may be eligible for.
Before you apply
You MUST contact the lead supervisor for this project - Dr Ma - [Email Address Removed] - before you apply.
How to apply
To be considered for this project you’ll need to complete a formal application through our online application portal.
When applying, you’ll need to specify the full name of this project, the name of your supervisor, how you’re planning on funding your research, details of your previous study, and names and contact details of two referees.
Your application will not be processed without all of the required documents submitted at the time of application, and we cannot accept responsibility for late or missed deadlines. Incomplete applications will not be considered.
If you have any questions about making an application, please contact our admissions team by emailing [Email Address Removed].
Equality, diversity and inclusion
Equality, diversity and inclusion is fundamental to the success of The University of Manchester and is at the heart of all of our activities. We know that diversity strengthens our research community, leading to enhanced research creativity, productivity and quality, and societal and economic impact.
We actively encourage applicants from diverse career paths and backgrounds and from all sections of the community, regardless of age, disability, ethnicity, gender, gender expression, sexual orientation and transgender status.
We also support applications from those returning from a career break or other roles. We consider offering flexible study arrangements (including part-time: 50%, 60% or 80%, depending on the project/funder).
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