Imperial College London Featured PhD Programmes
Gdansk University of Technology Featured PhD Programmes
University of Reading Featured PhD Programmes

Numerical modelling and design of geothermal heat recovery from subsurface systems


   Department of Chemical Engineering & Analytical Science

   Applications accepted all year round  Self-Funded PhD Students Only

About the Project

Sedimentary basins are ubiquitous, naturally porous and permeable, and the geothermal heat in these basins can be extracted with geologic water or CO2 and used to generate electricity. The UK must decarbonise heating for it to meet its commitments on emissions reduction. UK heat demand can be met from ultra-low-carbon, low enthalpy geothermal energy. In the geothermal energy technology, this is a common practice to drill a doublet (i.e. an injection and production well pair) system. The well spacing distance is usually chosen through engineering judgement. There is, however, a need for improved well placement strategies as in view of optimizing the net energy gained through either use of water or CO2

Model based optimization strategies for well location, trajectory and thereby spacing are commonly practiced in the oil and gas industry. Using this background, optimization of well spacing can be extended and implemented for doublet design. Additionally, due to the usually large uncertainty present in the subsurface it is essential to also account for geological uncertainties during optimization. In this framework, geological uncertainties are accounted for through an ensemble of equiprobable geological models. Therefore, a single robust solution of well locations is to be found, which is optimal in terms of an expected objective function value over the ensemble of models. The practice for CO2 geothermal systems will produce guidelines for industry. 

The project benefits from direct collaboration with Schlumberger using ECLIPSE geothermal simulator, and with Durham Energy Institute (Prof Jon Gluyas). 

Application information: Information about the application process and a link to the online application form can be found at https://www.manchester.ac.uk/study/postgraduate-research/admissions/how-to-apply/. Take note of the application checklist and provide the requested documents. To apply for this programme, select PhD Chemical Engineering and PhD Multi-scale Modelling. When completing the application include the name of the lead supervisor as the potential supervisor.

Applicants should have or expect to achieve at least a 2.1 honours degree in degree in Mechanical Engineering, Chemical Engineering, Civil Engineering, or Petroleum Engineering.

Enquiries about this project can be sent to Dr Masoud Babaei () as the lead project supervisor. The Admissions team in CEAS can be contacted at  with any queries you may have regarding the application process.

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).

All appointments are made on merit.

The University of Manchester and our external partners are fully committed to equality, diversity and inclusion. 


Email Now


Search Suggestions
Search suggestions

Based on your current searches we recommend the following search filters.

PhD saved successfully
View saved PhDs