We are a global technology company, driving energy innovation for a balanced planet. Together, we create amazing technology that unlocks access to energy for the benefit of all.
At SLB, we recognize that our innovation, creativity, and success stem from our differences. We actively recruit people with a diverse range of backgrounds and cultivate a culture of inclusion that unlocks the benefits of our diversity.
We want to ensure that everyone feels a sense of belonging here and we encourage, enable, and empower our people to foster inclusivity, build trust, and demonstrate respect for all across the organization.
Global in outlook, local in practice – and with a united, shared passion for discovering solutions, we hire talented, driven people and support them to succeed, personally and professionally.
Description & Scope
The Visage finite-element geomechanics simulator enables you to plan for and mitigate risks by modeling problems before they occur. This includes the following:
- Compaction and subsidence,
- Well and completion integrity,
- Cap-rock and fault-seal integrity,
- Fracture behavior,
- Thermal recovery,
- CO2 disposal.
The industry-leading Visage simulator has over 20 years’ pedigree and benefits from continuous software development and innovation by SLB.
The scope of the internship is to set-up a surrogate model based on deep-learning for the assimilation of data related to poro-elasticity problems. The surrogate model will be design making use of Physics informed Neural Network (PINN) and then used for parameter estimation using Baysesian inversion.
Deliverables
- Responsible for evaluating different deep learning approaches to be applied to poro-elasticity problems.
- You will implement a prototype based on the evaluations to be used for forecasting or parameter estimation.
- You will gain exposure to deep learning techniques applied to energy and sustainability solutions.
- A successful completion of project would open the possibility for a publication in a scientific journal.
Required skills & qualifications
- Studying for Masters Degree / PhD in Data science or a related discipline
- Oral and written communication skills in English
- Good motivation, autonomy, teamwork, and ingenuity
- Background in data science
- Good knowledge and expertise in deep learning methods
- Good programming skills in Python
- Problem solving and analytical skills
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.