From geo-resources to energy storage: how do underground lithologies respond to thermo-mechanical coupling?

On our quest to decarbonise our energy resources, underground heat energy storage is a key player. However, the impact of frequent cyclic thermo-mechanical (TM) stress changes over prolonged periods remains poorly understood and may threatened the longevity of the systems. This project will aim to fill the gap by performing laboratory and numerical experiments under relevant cyclic TM loading conditions to investigate the stability of targeted lithologies in such systems.
To address the energy transition challenges, new subsurface solutions focus either on new resources exploitation (geothermal) or storage (radioactive waste, heat and/or gas – underground gas storage, compressed-air energy storage, H, CO2). All these applications have in common to induce new, shallow, periodic, local thermo-mechanical stress changes. Recent works on TM effects (from room temperature to ca. 100oC) on porous rocks have demonstrated:
– a peak strength reduction with increasing thermal loading in intact samples, whilst samples with initial discontinuities first displayed an increase in peak shear strength at 50oC before showing similar reduction as intact samples at 100oC (Woodman, 2020);
– a substantial pore pressure accumulation with thermal loading, with fluid thermal expansion being substantially greater than mineralogical thermal expansion (Garitte et al., 2017);
– a non-valid use of uniform failure and friction criteria, which could lead to an erroneous estimation of the subsurface stress state (Arhens et al., 2021).
Moreover, series of cyclic mechanical loading tests performed at relevant underground gas storage conditions, have shown a complex impact of the material microstructure on the mechanical properties and material response at different scales of observation (Martin Clave et al., 2021). For instance, local microcracking in some minerals (inelastic deformation) appeared to be accommodating further elasticity at the macroscopic scale instead.
The scope of this PhD project is to use different scale observations to model and predict the stability of targeted lithologies in underground complex systems when those are subjected to cyclic TM stress changes over prolonged periods. This research work seeks to understand how grain scale deformation can contribute to the global response of the underground systems and how this response can be controlled to reduce any accompanied induced hazards. An innovative methodology, combining laboratory and numerical experiments, will be applied to extend the understanding of the thermo-sensitive brittle deformation processes in porous rocks. The data will provide information to support field scale operational conditions involving periodic TM stress changes as well as shed light on potential for cascading shallow geohazards.
O1: Examine the relationship between microstructural deformation and TM stresses.
O2: Collect, analyse and model TM data together.
O3: Transfer and improve existing DEM code from UDEC to open source and undertake grain size sensitivity analysis.
O4: Provide relevant data to inform on risks associated to TM stresses in underground geological storage conditions


Laboratory experiments will be performed at different scales (from grain to sample scales). Core samples will be x-ray scanned at HWU to understand their internal 3D microstructure and assess their transport properties (porosity and inferred permeability notably) pre and post TM experiments (O1). TM experiments will be performed at BGS using the MTS 815 Rock Testing System to simulate elevated environmental conditions. Several deformation scenarios will be investigated to cover different industrial field operations. This lab-scale global sensing data will be combined to petrographical analysis (O2) to correlate the spatiotemporal distribution of the lab-induced damage within the tested materials with the microstructural evolution. Moreover, similar grain-scale experiments with syn-deformation monitoring (x-rays) are possibly planned to unravel the micro-scale processes.
Numerical modelling and machine learning techniques are nowadays used more frequently to predict the subsurface system behaviour. TM coupling calibrated Grain Based Modelling (GBM) can capture micro-cracking as a mechanism of progressive damage, reproducing the stress-strain behaviour of laboratory tests. Several studies have shown the ability of calibrated Voronoi GBMs to produce realistic macroscopic mechanical only behaviour of samples of various lithologies (granite, diorite, tuff, sandstone) being deformed over a range of stresses within the brittle field (Christianson et al., 2006; Damjanac et al., 2007; Stavrou & Murphy, 2018) and TM behaviour (Lan et al., 2013). Yet, to our knowledge, only two studies have introduced TM coupling to a laboratory scale Voronoi GBMs (Park et al., 2015; Woodman et al., 2021). Developing such models though is key to understand how TM brittle damage develops across the scales, from grain size cracking to rock mass fracturing, and its time dependency. This PhD project will build on the DEM developed by Woodman et al. (2021) to undertake notably a grain size and distribution sensitivity analyses in thermo-mechanical simulations (O3) to further assess the up scaling of laboratory data to field scale (O4).

Project Timeline

Year 1

Literature review and training:
• Literature review on TM coupling and TM testing
• Training for the x-ray tomography (acquisition and image processing)
• DEM training (on the job) with UDEC and/or Yade
• Attending HW training sessions for 1st year PhD and ALERT Doctoral School
Samples and X-ray imaging:
• Collect material to sample (HWU)
• Perform X-ray tomography and run image analysis (HWU)
• 1 national/international conference (academia lead)

Year 2

• Training for high pressure-high temperature experimental testing (BGS)
• Training in project management and writing proposal (BGS)
• 6th Cargèse summer school on Flow and Transport in Porous and Fractured Media
• TM experiments (BGS) on porous samples representative of selected underground resources/storage conditions in the UK. The experimental conditions will be designed to simulate in-situ reservoir environments (saturation, pressure, temperature) and enable knowledge transfer from the laboratory- to the field-scale.
• DEM sensitivity analysis
• 1 international conference (academia lead)
• 1st paper on grain size sensitivity analysis

Year 3

• Attending ALERT Doctoral School
• Numerical modelling (BGS or HWU)
• TM experiments (BGS)
• 1 national/international conference/workshop (industry lead)
• 2nd paper on TM experimental results

Year 3.5

• Thesis
• 3rd paper on TM experimental data integration and upscaling

& Skills

Research Future Academy at HWU provides skills/career development workshops to facilitate doctorate and future research career of PhD students. The student will be able to attend workshops focusing on developing a. basic skills for successful research; b. research data management; c. communication and dissemination skills; d. strategy for publishing; e. citation and impact. At BGS the student will attend training sessions on scientific paper and proposal writing and project management. High skilled technical training will be provided by the PhD supervisors and technical staff at HWU and BGS. The student will be encouraged to attend 2 to 3 doctoral training schools and 2 to 3 conferences/workshops.

References & further reading

Arhens et al. (2021). https://library.seg.org/doi/pdfplus/10.1190/segam2021-3583290.1
Christianson et al. (2006). https://www.osti.gov/servlets/purl/837704
Damjanac et al. (2007). https://doi.org/10.1016/j.ijrmms.2006.07.010
Garitte et al. (2017). https://link.springer.com/content/pdf/10.1007/s12665-017-6662-1.pdf
Lan et al.(2013). https://link.springer.com/article/10.1007/s00603-012-0248-8
Park et al. (2015). https://onepetro.org/ISRMEUROCK/proceedings-abstract/EUROCK15/All-EUROCK15/ISRM-EUROCK-2015-116/41939
Stavrou & Murphy (2018). https://doi.org/10.1016/j.ijrmms.2018.01.019
Woodman (2020). https://etheses.whiterose.ac.uk/26306/
Woodman et al. (2021). https://link.springer.com/article/10.1007/s10706-021-01794-z

Apply Now