Methane is a major greenhouse gas and so contributes to climate change. Cranfield and SLB are offering an iCASE PhD studentship, developing practical methods to monitor methane emissions from point source emissions such as oil and gas facilities. The proposed research will link observations of methane and other data streams from client facilities with appropriate atmospheric modelling techniques, to identify and estimate the size and location of leaks within site boundaries. This studentship will help SLB and its present & future clients meet their net-zero greenhouse gas emission objectives. This studentship will provide a bursary of up to £18,000 (tax free) plus fees for four years.

The 2021 IPCC assessment report on climate change and the US-EU led Global Methane Pledge highlight the contribution of methane to the current global atmospheric warming trend. The IPCC report estimates that 0.5ºC of the current 1.1ºC temperature rise is attributable to this potent greenhouse gas. Sources of methane include agriculture, landfill, water treatment and oil & gas facilities. To assist SLB and its clients meet their net-zero greenhouse gas emission objectives, there is a need for continuous monitoring at well construction and production facilities, and mitigation of vented and fugitive methane emissions. In collaboration with the newly-launched Emissions Management business line, this project will contribute to SLB’s net zero by 2050 roadmap, covering scope 1, 2 & 3 emissions, based on the GHG Protocol Corporate Accounting and Reporting Standard.
The proposed research will link observations of methane and other data streams from client facilities with appropriate atmospheric modelling techniques, to identify, then estimate size and location of leaks within site boundaries.

The key research objectives include:

1. Assess the challenges involved in identifying methane leaks at oil and gas installations and enabling timely remedial action. This will include understanding the minimum level of instrumentation required to achieve meaningful, quantitative estimates of methane emission within an acceptable level of uncertainty.

2. Develop modelling approaches suited to use the pseudo-continuous time-series methane concentration data to arrive at meaningful emission estimates.

3. Investigate if the ground-based emissions estimates from oil and gas facilities can be improved by combination with other sensing approaches, such as from airborne, satellite platforms and other on-site data sources.

4. Develop edge-based machine-learning techniques to provide near-instantaneous emission estimates.

5. Determine the suitability of the technology to scaling from individual facilities up to basin-wide levels and for its applicability in non-oilfield applications such as biogas, water treatment, agriculture & LNG shipping.
SLB is a global technology company, driving energy innovation for a balanced planet. Currently, it is the leading provider of technology and services to the energy industry. Throughout much of the oil and gas lifecycle in over 120 countries, they design, develop, and deliver technology and services that transforms how work is done. SLB are looking for innovators to work with their diverse community of colleagues and develop new solutions and push the limits of what’s possible.

Successful development of a technique for rapid identification of emissions leading to timely mitigation actions will be of great value in the efforts to reduce CH4 emissions including those of SLB’s clients, both present and future.

The student will visit UK and overseas oil and gas facilities to learn about the practical problems faced in the field. This may also include visits to dedicated emission research facilities such as the METEC Energy Institute in Colorado. In addition, there will be opportunities to work with other centres within SLB as well as their partners and clients in the Oil and Gas industry.

Quantitative skills including use of artificial intelligence; communicating and networking with academic and commercial sectors; insight into and understanding of the rapidly evolving energy industry as society responds to the climate crisis; problem solving skills; team working; technological literacy; adaptability.


At a glance

  • Application deadlineOngoing
  • Award type(s)PhD
  • Start date02 Oct 2023
  • Duration of award4 years
  • EligibilityUK
  • Reference numberSWEE0206


Supervisors- 1st Supervisor: Prof Neil Harris    
2nd supervisor: Dr Michelle Cain

Entry requirements

Applicants should have a first or second class UK honours degree or equivalent in a related discipline. This project would suit a candidate with a physical science or engineering science background. Prior study of this specific research area is not a pre-requisite, but candidates must be highly numerate and be willing to study any previously unknown underpinning areas of science that are required. We encourage applications from under-represented groups and are committed to equality, diversity and inclusion.


Sponsored by EPSRC and SLB, this studentship will provide a bursary of up to £18,000 (tax free) plus fees for four years.

This studentship is open to UK only


Cranfield Doctoral Network

Research students at Cranfield benefit from being part of a dynamic, focused and professional study environment and all become valued members of the Cranfield Doctoral Network. This network brings together both research students and staff, providing a platform for our researchers to share ideas and collaborate in a multi-disciplinary environment. It aims to encourage an effective and vibrant research culture, founded upon the diversity of activities and knowledge. A tailored programme of seminars and events, alongside our Doctoral Researchers Core Development programme (transferable skills training), provide those studying a research degree with a wealth of social and networking opportunities.

How to apply

For further information please contact:
Name: Dr Michelle Cain

For information about applications please contact: E:

If you are eligible to apply for the PhD, please complete the online PhD application form stating the reference No. SWEE0206