HPC Software Engineer Intern (3 months)

Job Title:

HPC Software Engineer Intern (3 months) - Starting Summer 2026

Project Title: Upscaling of embedded meshes to boost simulator accurary and performance.

About SLB:

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Location:

Abingdon, Oxfordshire

Description & Scope:

​​​Reservoir simulators are key tools for understanding fluid flow in complex geological formations, but balancing accuracy and performance remains a challenge. One promising approach is the use of embedded meshes, which allow us to represent fracture grids within the rock matrix. These fractures play a critical role in controlling how fluids move underground, and capturing their effects accurately is essential for reliable predictions. However, modeling fractures at fine resolution everywhere is computationally expensive. To make large-scale simulations feasible, these detailed embedded meshes need to be upscaled—translating the fracture-level detail into coarser representations that preserve their impact on flow while reducing computational cost.

In this project, the intern will explore and prototype methods for upscaling embedded fracture meshes within our next-generation simulator. The work will involve a mix of numerical experimentation, algorithm development, and performance analysis, giving the intern the opportunity to learn about advanced concepts in reservoir simulation, fracture modeling, and high-performance computing. Beyond technical growth, the intern will contribute to a project with direct impact on improving the efficiency and predictive power of industry-scale simulations.​

Responsibilities

Implementing an upscaling algorithm for embedded fracture meshes and integrating it into a prototype workflow. Coding, testing, and validating the algorithm on representative geological models. Deliverables will include a functional implementation, validation results compared against fine-scale simulations, Completing a report documenting the approach and findings. 

Through this project, the intern will gain practical experience in scientific programming, mesh-based modeling, and numerical validation techniques, as well as exposure to high-performance computing practices. By the end of the internship, the student will have hands-on experience in developing a method that directly improves the efficiency and accuracy of industry-scale reservoir simulations.​

Qualifications:

Studying a ​​Masters​ in ​High Performance Computing, Mathematics, Computer Science, Physics, Reservoir Simulation or a related discipline Proficiency in programming (C++ or Python) Strong foundation in mathematics, especially linear algebra and geometry Ability to apply mathematical concepts to algorithm development​