Reservoir Engineer (Data Science)
Tasks
- Apply machine learning for reservoir characterization
- Automate subsurface analyses and improve data quality
- Build reservoir simulation models
- Develop Python workflows for subsurface analysis
- Forecast production and detect anomalies
- Integrate geological petrophysical stimulation and operational data
- Perform history matching sensitivity analysis and scenario evaluation
- Update and maintain analytical models
- Visualize and communicate technical results
Perks/Benefits
- 401k match
- Dental insurance
- Flexible paid time off
- Life insurance
- Long-term disability
- Medical insurance
- Paid Incentives
- Paid parental leave
- Short-term disability
- Stock options
- Vision insurance
Skills/Tech-stack
Anomaly Detection | Cloud Computing | Data Visualization | Data integration | Fluid Flow in Porous Media | Fluid flow | Geological data integration | Geoscience data | Git | High Performance | High-Performance Computing | History matching | Machine Learning | Material balance | NumPy | Numerical modeling | Pandas | Performance Computing | Petrophysical Data | Petrophysical Data Integration | Porous media | Pressure transient analysis | Production forecasting | Python | Reproducible Research | Reservoir simulation | Scenario Analysis | SciPy | Sensitivity Analysis | Statistical Analysis | Transient analysis
Education
Roles
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