PhD Research Fellow in ML-assisted seismic inversion and geomechanical modelling of CO2 storage

About the position

Position as PhD Research Fellow in ML (machine learning)-assested seismic inverion and 3D field-scale geomechanical modelling of CO2 storage is available at the Department of Geosciences, the University of Oslo (UiO).

No one can be appointed for more than one PhD Research Fellowship period at the University of Oslo. The preferred starting date is before 01/04/2025.

The fellowship period is 3 years.

A fourth year may be considered with a workload of 25 % that may consist of teaching, supervision duties, and/or research assistance. This is dependent upon the qualification of the applicant and the current needs of the department.

Knowledge development in a changing world - Science and technology towards 2030.

The Faculty of Mathematics and Natural Sciences

Job description

The Section of Applied Basin Analysis at the Department of Geosciences, University of Oslo (UiO) seeks a highly motivated candidate for a PhD research fellowship aimed at de-risking CO2 storage sites in the offshore North Sea. The PhD research project targets quantitative interpretation and geomechanical modling by integrating seismic, well log, lab and literature data to de-risk the CO2 storage sites in the offshore Norway. The research outcomes would better understand geological heterogeneity of reservoir, seal and overburden rocks that challenges seal integrity, fluid injectivity, storage performance, plume evolution, and pressure-build ups of multi-site storage licenses. Moreover, the research will help to suggest the best practice to integrate machine learning to de-risk CO2 storage sites.

We seek a candidate with a strong background in rock physics, petrophysics, seismic attribute analysis, seismic inversion (both pre- and post-stack inversions), and machine learning with geoscience knowledge, preferably in seal/reservoir/overburden heterogeneities, static and dynamic reservoir modelling, and flow simulation. The candidate will work in a team of geologists, geophysicists, sedimentologists, geochemist and staff with strong machine learning and numerical modelling background to add knowledge on the impact of geological heterogeneity and subsurface environments (e.g., depth, exhumation, temperature, pressure) to de-risk CO2 storage sites, offshore Norway. There will be a close collaboration between UiO and other research institutes and industries participating in the gigaCCS centre, with co-supervision from partner’s institutions. The study areas will be selected based on the gigaCCS centre's focuses and the interests f industry partners. 

Project description:

The PhD will be part of the new FME gigaCCS centre. The centre will advance Norway’s expertise in CCS, as well as support the global implementation of CCS at a gigatonne scale. One part of the project is to characterize CO2 storage sites in the Norwegian North Sea. Due to heterogeneity and anisotropic behaviors, these reservoir rocks pose challenges related to injectivity, fluid migration, plume evolution and pressure build-up. The goal is to gain quantitative understanding of reservoir-seal, under- and overburden units by integrating petrophysics, rock physics, geophysics, geomechanics and machine learning. A detailed project plan will be developed in collaboration with the successful candidate at the start of PhD.

Qualification requirements

The Faculty of Mathematics and Natural Sciences has a strategic ambition to be among Europe’s leading communities for research, education and innovation. Candidates for these fellowships will be selected in accordance with this, and expected to be in the upper segment of their class with respect to academic credentials.

• Master’s degree or equivalent
• Foreign completed degree (M.Sc.-level) corresponding to a minimum of four years in the Norwegian educational system
• Fluent oral and written communication skills in English

Required qualifications:

• Experience with petrophysics, rock physics, seismic attribute analysis, seismic inversion and machine learning with relevance to the geoscience problem described above.
• Master’s degree or equivalent in geophysics, petrophysics, formation eval-uation, reservoir engineering, or similar.
• Foreign completed degree (M.Sc.-level) corresponding to a minimum of four years in the Norwegian educational system.
• Candidates without a Master’s degree must submit their thesis within the application deadline Dec 30th and present a date for the final exam.
   

Desired qualifications:

• Insight into rock physics, petrophysics, reservoir geology, reservoir geophysics, geomechanics and quantitative seismic interpretation.
• Insight into geological CO2 sequestration.
• Skills in industry-standard geoscientific software of Petrel, HampsonRussell, RokDoc, Interactive Petrophysics, PowerLog, Jason, and Visage.
• Programming skills (e.g., Python, MatLab, R).
• Publications related to the field of the PhD research topic.

Candidates without a master’s degree must obtain their Master degree before the date of employment in the PhD position.

Grade requirements:
The norm is as follows:

• The average grade point for courses included in the Bachelor’s degree must be C or better in the Norwegian educational system
• The average grade point for courses included in the Master’s degree must be B or better in the Norwegian educational system
• The Master’s thesis must have the grade B or better in the Norwegian educational system
• Fluent oral and written communication skills in English.
• English requirements for applicants from outside of EU/ EEA countries and exemptions from the requirements:

https://www.mn.uio.no/english/research/phd/regulations/regulations.html#toc8 

The purpose of the fellowship is research training leading to the successful completion of a PhD degree. 

The fellowship requires admission to the PhD programme at the Faculty of Mathematics and Natural Sciences. The application to the PhD programme must be submitted to the department no later than two months after taking up the position.

For more information see: 

http://www.uio.no/english/research/phd/
 
http://www.mn.uio.no/english/research/phd/

Personal skills

• Being motivated and enthusiastic to perform the research tasks
• To be able to work independently and in a team and have good communication and interpersonal skills
• Being focused and at the same time be able to deliver tasks within deadlines

We offer

• Salary NOK 532 200 – 575 400 per annum depending on qualifications and seniority as PhD Research Fellow (position code 1017)
• Attractive welfare benefits and a generous pension agreement 
• Vibrant international academic environment
• Career development programmes
• Oslo’s family-friendly surroundings with their rich opportunities for culture and outdoor activities

How to apply

The application must include:

• Cover letter - statement of motivation and research interests
• CV (summarizing education, positions and academic work - scientific publications)
• Copies of the original Bachelor and Master’s degree diploma and transcripts of records
• Documentation of English proficiency if applicable
• List of publications and academic work that the applicant wishes to be considered by the evaluation committee
• Names and contact details of 2-3 references (name, relation to candidate, e-mail and telephone number)

The application with attachments must be delivered in our electronic recruiting system (please follow the link “Apply for this job”). Foreign applicants are advised to attach an explanation of their University's grading system. Please note that all documents should be in English or a Scandinavian language.

Interviews with the best qualified candidates will be arranged.

Formal regulations

Please see the guidelines and regulations for appointments to Research Fellowships at the University of Oslo.

According to the Norwegian Freedom and Information Act (Offentleglova) information about the applicant may be included in the public applicant list, also in cases where the applicant has requested non-disclosure.

UiO has an agreement for all employees, aiming to secure rights to research results a.o.

Inclusion and diversity are a strength. The University of Oslo has a personnel policy objective of achieving a balanced gender composition. Furthermore, we want employees with diverse professional expertise, life experience and perspectives.

If there are qualified applicants with disabilities, employment gaps or immigrant background, we will invite at least one applicant from each of these categories to an interview.

Contact information

For further information about the position please contact:  Prof. Nazmul Haque Mondol,  e-mail: nazmulh@geo.uio.no

For questions regarding Jobbnorge, please contact HR Adviser Ørjan Pretorius, e-mail: orjan.pretorius@mn.uio.no