Viridien (www.viridiengroup.com) is an advanced technology, digital and Earth data company that pushes the boundaries of science for a more prosperous and sustainable future. With our ingenuity, drive and deep curiosity we discover new insights, innovations, and solutions that efficiently and responsibly resolve complex natural resource, digital, energy transition and infrastructure challenges.
Job Details
This role is for physicists, mathematicians, computer scientists and machine-learning scientists in their last year of Master-level degree, who are looking for a six-month internship where they can put their theoretical knowledge and problem-solving skills to develop/test/improve the methods oriented to real Earth imaging problem.
What will you learn?
The world beneath our feet is incredibly complex. It is also the source of natural resources fundamental to the functioning of our society. In Viridien, we use knowledge of signal processing, wave propagation, numerical optimization and AI to develop and test high-end algorithms, sequences, or workflows with predefined geophysical or engineering content for our clients.
During your internship, you will be working in the subsurface imaging R&D team, in close collaboration with our software and production departments, to meet their demands and industry trends.
You will have the opportunity to engage in cutting-edge research on reservoir-oriented full-waveform inversion (FWI). In Viridien, FWI has been widely used for velocity model building and seismic imaging in complex geological contexts around the world to accurately construct highly detailed, data-driven physical medium parameters of subsurface. Until recently, most FWI industrial applications have relied on acoustic-approximation-based modeling to reduce computational costs. A step forward from acoustic modeling to elastic modeling allows FWI to interpret elastic phenomena in the seismic data.
This approach not only enhances P-wave–based velocity model building and seismic imaging beneath complex overburdens, but also provides an additional S-wave velocity model, which is highly valuable for distinguishing fluid types (water, oil, and gas) and monitoring fluid movements during hydrocarbon reservoir characterization.
During this internship, you will investigate the potential of using neural networks to incorporate petrophysical information for guiding full-waveform inversion (FWI) from both methodology and development perspectives. The main objectives are as follows:
Qualifications
Key Skills And Experiences
Additional Information
We see things differently. Diversity fuels our innovation, we value the unique ways in which we differ, and we are committed to equal employment opportunities for all professionals.
Our Hiring Process
At Viridien, we are committed to delivering a respectful, inclusive, and transparent recruitment experience.
Due to the high volume of applications we receive, we may not be able to provide individual feedback to every applicant. Only candidates whose qualifications closely match the role criteria will be contacted for an interview. We do, however, aim to share personalized feedback with those who progress to the first round of interviews and beyond.
We are also dedicated to ensuring that our hiring process accessible to all. If you require any reasonable adjustments to fully participate in the application or interview stages, please don’t hesitate to contact your recruiter directly.
We see things differently. Diversity fuels our innovation, we value the unique ways in which we differ, and we are committed to equal employment opportunities for all professionals.