Scientific Geomechanics Intern (6 months) | Schlumberger

Job Details

Scientific Geomechanics Intern (6 months)

Abingdon - United Kingdom

Job title:

Scientific Geomechanics Intern



Abingdon, United Kingdom


About SLB:

We are a global technology company, driving energy innovation for a balanced planet.


At SLB we create amazing technology that unlocks access to energy for the benefit of all. That is our purpose. As innovators, that’s been our mission for 100 years. We are facing the world’s greatest balancing act- how to simultaneously reduce emissions and meet the world’s growing energy demands. We’re working on that answer. Every day, a step closer.


Our collective future depends on decarbonizing the fossil fuel industry, while innovating a new energy landscape. It’s what drives us. Ensuring progress for people and the planet, on the journey to net zero and beyond. For a balanced planet.


Job Description:


Schlumberger-Doll Research in Cambridge, MA, USA and Schlumberger Abingdon Technology Center in Abingdon, UK are seeking a highly motivated intern to assist with cutting edge research into automatic construction of borehole geomechanics models, also known as 1D Mechanical Earth Models (MEMs). 


A 1D MEM is comprised of attributes required to predict the mechanical failure of rocks i.e. the pore pressure, rock properties, and the in situ stress field.  Traditional methods for constructing MEMs are tedious, time-consuming, and often impractical on a multi-well scale. 


The objective of this project is to further the development of a new theoretical framework for stochastic inversion of 1D MEMs.  The framework builds on recently published work [Nicolaidou et al 2022; Birchwood et al 2021].  The intern will collaborate with research scientists in the USA and the UK to apply this theory to field data.  Such data would include core data, well logs, and stress measurements. 


Essential Responsibilities and Duties:


The main responsibilities and duties involved within this position are:

  • The intern will have the opportunity to acquire theoretical and practical knowledge of geomechanics, computer programming, and probability theory. 
  • He or she would be expected to improve existing software using the Python language, by incorporating novel techniques to enhance the performance of the inversion methodology on serial and parallel architectures. 
  • The intern would compare inversion results with those obtained by traditional methods (human versus machine comparisons); tune input parameters to improve the efficiency and accuracy of stochastic inversion; identify deficiencies in the theory and assist with necessary alterations; and prepare internal and external publications. The main output of this work would be efficient python code that would help drive cloud-based automation.


Qualifications and competencies:


The successful candidate should possess the following:

  • Students in Engineering, Mathematics, Physics, or Earth Sciences with strong mathematical and programming skills are encouraged to apply.
  • Preference will be given to students with knowledge of Bayesian statistical inference techniques



We are open to flexible, hybrid working with a combination of on-site & home working days.


SLB is an equal employment opportunity employer. Qualified applicants are considered without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, or other characteristics protected by law.