Objective: The main objective of this PhD project is to better understand and upscale the fundamental controls on fluid migration in the Mercia Mudstone Group based on 3D multi-scale imaging, modelling of large 3D data sets, and the application of machine learning approaches.
Context: The UK has a policy of providing safe long-term disposal of legacy and future higher-level (intermediate and high level and spent fuel) nuclear waste through deep burial in a geological disposal facility (GDF). One potential host rock for a GDF is fine–grained sedimentary rock, or mudstone. Mudstones are considered potentially suitable host rocks due to their very low permeability and ductile nature which can lead to seal healing of faults and fractures under burial conditions. One host rock under consideration is the highly-complex and heterogeneous Triassic aged Mercia Mudstone Group (MMG).
To satisfy the requirements for a GDF safety case, many near-field and far-field factors need to be taken into account, including, for instance, the likelihood that fluid and solutes could flow or diffuse from the waste into surrounding host-rock and impact the far-field (particularly receptors within the biosphere). The assumption is that mudstones, by virtue of their very low permeability, will mean such transport is limited. However, at present, multi-scale (nano-scale to metre-scale) assessment and modelling of potential pathways have not been carried out for the MMG. Such analysis is challenging due to the small-scale of 3D pore networks and micro fractures in LSSR rocks. This PhD research will utilise state-of-the-art multi-scale imaging techniques at the University of Manchester to better quantify and understand these 3D characteristics at multiple scales.
Key questions: Hosted at Manchester, and jointly supervised by staff from Manchester, the National Nuclear Laboratory and the University of Liverpool, the following key questions will be addressed, focussing on Mercia Mudstone Group sediments:
1) How does 2D and 3D nano- and micro-structure vary within key units within the Mercia Mudstone Group?
2) How can cm- to metre-scale variability in heterogeneity be upscaled in order that potential pathways for fluids and gases be better understood?
3) Can 3D image-based data be used to construct fluid reactive transport models applicable to the short, medium and long-term behaviour of the MMG as a host rock for a GDF?
Method, samples, and data: The PhD project will be split into four main tasks:
· Task 1 - Characterisation. 2D SEM and 3D Micro- and nano-CT, together with Focused Ion Beam Scanning Electron Microscopy (FIB-SEM) and Atomic Force Microscope (AFM) of selected samples. From this 3D microstructure and pore-fracture system across four scales (from nm-scale to mm-scale).
· Task 2 – Heterogeneity. The quantification of level of heterogeneity, and Representative Elementary Volume analysis on lithological, microstructural and pore systems at all scales, and geo-statistical analysis.
· Task 3 – Upscaling. Based on outputs from task 1 and 2, to upscale to core-scale observations of key portions in the MMG.
· Task 4 - Modelling and NNL placement. Image-based data on the 3D pore- and microfracture- structure will be used to form the basis of fluid/gas/reactive transport models, to better inform a future site descriptive model (SDM), concept development, underpinning for engineering, underpinning for safety assessments, borehole design/locations, and initial site evaluations (ISE). As part of this task it is envisaged that the student will complete a short placement to obtain specialist training and gain valuable industry insights.
Impact: outputs from this project will help inform, by analogue, site descriptive model (SDM), concept development, underpinning for engineering, underpinning for safety assessments, borehole design/locations, and initial site evaluations (ISE).
Training: Full training in X-ray and electron-beam techniques will be provided as well as in the development of numerical models for fluid flow and solute diffusion in low porosity rocks. Training will also be given in features of repository development including safety case creation, performance assessment and the development of 3D/4D spatial databases suitable to handle raw, modelled and conceptual models for such safety cases.
Careers: In addition to learning in-demand key skills which are essential for the nuclear sector, the approaches developed in this research will also be more widely applicable to other energy systems, such as cap-rock performance to CO2 storage reservoirs.
Admissions qualifications / requirements: Applicants should have or expect to achieve at least a 2.1 honours degree (or equivalent), in earth sciences, geology, chemical or mechanical engineering, geophysics, environmental sciences, or a related discipline.
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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