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40 Fin Coopers Jobs
Reservoir Modeling Digital Solutions Earth Scientist
2-5 years
Bangalore / Bengaluru
1 vacancy
Reservoir Modeling Digital Solutions Earth Scientist
Fin Coopers
posted 22d ago
Job Role Insights
Flexible timing
Key skills for the job
Job Description
- Responsible for the development and/or deployment of existing and new technology and workflows to solve key business challenges across Chevron
- The job involves integration of geological, petrophysical, geophysical and engineering data to create reservoir models used for resource evaluation and production forecasting
- Provides support to the Digital Platform, and is responsible for running, maintaining, supporting users and improving the Geology suite of Petrel-plugins
- Contributes to the development of new Geological plug-ins in Petrel (e.g. coding in Ocean, development of user interfaces and algorithms)
- Targeted user-experience and data management development (e.g., GUI, Power-BI, data engineering, Machine Learning engineering, and mature digital minimum viable products)
- Teaming with US-based R&D groups focusing on developing and deploying reservoir modeling and geology products and workflows
- Application testing, pipeline, build and release in cloud platform
- Development of technical digital solutions and training documentation
- MSc/PHD degree in Earth Science or Engineering from deemed/recognized (AICTE) university
- At least five years of experience in Earth Science or Engineering or related industry
- Proficiency with Petrel or equivalent Earth Modeling suite
- Demonstrated fluency in digital solutions development, including python, C#, C++, Azure ecosystems developments (pipelines, dashboards, visualization, data management systems)
- Understanding of physical processes associated with earth science, reservoir modeling and subsurface.
- Experience with customer support and understanding of subsurface business needs and utilizing Scaled Agile Framework (SAFe) processes to implement highly prioritized features
- Good communication skills and ability to work effectively in a team environment
- Fundamental knowledge of geological workflows applied to subsurface
- Familiarity with SLB Ocean development framework is preferred but not a must
- Skills of using Machine Learning/AI to accelerate performance, and accuracy of reservoir characterization and modeling is preferred but not a must
- Direct experience with discretization of reservoir models is preferred but not a must
Employment Type: Full Time, Permanent
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