PetE 471
Enhanced Oil Recovery
Description
Classification of EOR methods, areal, vertical and volumetric sweep efficiencies, predictive models for immiscible displacement. Frontal advance theory and Buckley-Leverett-Weldge approach. Chemical (alkaline, polymer, surfactant, micellar injection) flooding. Miscible-immiscible gas (hydrocarbon and CO2) injection.Prerequisite: PET E 295 or PET E 373.
Learning Outcomes
- Identify rock wettability and governing mechanisms for oil trapping.- Examine and integrate reservoir rock-fluid properties and propose/screen enhanced oil recovery (EOR) method for oil recovery.
- Interpret the governing mechanisms during various EOR methods and screening parameters of EOR methods.
- Explain the concepts of capillary pressure and relative permeability and how they change for a particular EOR process.
- Carry out water flood calculations for 1D, 2D and 3D reservoirs and estimate oil recovery.
- Examine the influence of gravity segregation and predict oil recovery.
- Explain the essentials of surfactant and polymer characteristics, ASP flood, micro emulsions.
- Appreciate polymer and surfactant selection requirements/property assessment for optimal field performance.
- Estimate minimum miscibility for gas injections, immiscible gas injection, CO2 injection.
- Analyze historical EOR pilot/field performance, interpret performance results, derive analogy and lessons learned to integrate into future development strategies.
- Develop design concepts of EOR (selection of proper method, estimation of recovery performance, cost analysis) as part of an open-ended design project.
- Apply design procedures for developing EOR field pilot using real field operational parameters, suitable well patterns, various uncertainty criteria and optimization implementation strategies in an open-ended design project considering techno-economical assessment.
| Lecture | Seminar | Lab | Credits | Total AU |
|---|---|---|---|---|
| 3 | 0/1 | 0/1 | 3 | 37.8 |
| M % | NS % | CS % | ES % | ED % |
|---|---|---|---|---|
| 0 | 0 | 0 | 70 | 30 |
None defined
- A knowledge base for engineering
- Problem analysis
Undergraduate Program(s)
| 2026/2027 - Winter - Pete-coop - Year 5 |
| 2026/2027 - Winter - Pete - Year 4 |
| 2025/2026 - Winter - Pete-coop - Year 5 |
| 2025/2026 - Winter - Pete - Year 4 |
| 2024/2025 - Winter - Pete-coop - Year 5 |
| 2024/2025 - Winter - Pete - Year 4 |
| 2023/2024 - Winter - Pete-coop - Year 5 |
| 2023/2024 - Winter - Pete - Year 4 |
| 2022/2023 - Winter - Pete-coop - Year 5 |
| 2022/2023 - Winter - Pete - Year 4 |
| 2021/2022 - Winter - Pete-coop - Year 5 |
| 2021/2022 - Winter - Pete - Year 4 |
| 2020/2021 - Winter - Pete-coop - Year 5 |
| 2020/2021 - Winter - Pete - Year 4 |
| 2019/2020 - Winter - Pete-coop - Year 5 |
| 2019/2020 - Winter - Pete - Year 4 |
Sections & Respective Instructors
| B1 - 2026/2027 - Winter - Tayfun Babadagli |
| B1 - 2025/2026 - Winter - Tayfun Babadagli |
| B1 - 2024/2025 - Winter - Tayfun Babadagli |
| B1 - 2023/2024 - Winter - Tayfun Babadagli |
| B1 - 2022/2023 - Winter - Tayfun Babadagli |
| B1 - 2021/2022 - Winter - Japan Trivedi |
| B1 - 2020/2021 - Winter - Japan Trivedi |
| B1 - 2019/2020 - Winter - Tayfun Babadagli |