Reservoir Analytical Model Pattern Recognition - AB-025
Preferred Disciplines: Computer Science/Statistical Science; Masters, PhD, Post-Doc
Project length: 4-6 months
Desired start date: February 15th, 2018 or as soon as possible
Location: Calgary, AB
No. of Positions: 1
Preferences: University of Calgary/Alberta, no real preference. Language: English
Oil & gas reservoir engineering software start-up with focus on EOR properties. Combining analytical models with field data for reservoir surveillance and optimization.
Aiming to create a machine learning pattern recognition system to interpret field data and fit to analytical reservoir models.
Introduce large database of Enhanced Oil Recovery (EOR) history/forecasts to create probabilistic forecasts using analogous (database) progressions & analytical backing.
Background and required skills
- Determine an efficient system to handle large amounts of data
- Explore multiple mathematical approaches to determine most effective route
- Create well simulator using machine learning
- Experimenting with stochastic and non-stochastic learning, Markov models
- Applying machine learning, AI systems
Expertise and Skills Needed:
- At least one programming language, (C# or VS preferred)
- Basic knowledge of neural networks
- Knowledge of evolutionary algorithms
For more info or to apply to this applied research position, please
- Check your eligibility and find more information about open projects.
- Complete this webform. You will be asked to upload your CV. Remember to indicate the title of the project(s) you are interested in and obtain your professor’s approval to proceed!
Interested students need to get the approval from their supervisor and send their CV along with a link to their supervisor’s university webpage by applying through the webform or directly to Oba Harding at, oharding(a)mitacs.ca.