Electromagnetic Induction Heating Technology for Enhanced Heavy Oil and Bitumen Recovery
Bibliographic record
Abstract
Abstract This paper demonstrates how a novel electromagnetic induction heating technology can be used to recover oil from the Athabasca oil sands of Alberta with minimal environmental impact. The paper compares the new technology to other electromagmetic heating technologies for oil sands, exhibits how electromagnetic induction heating is coupled to the reservoir, and addresses requirements of the new technology for economic production. The patent pending inductor design generates thermal energy in a reservoir model representing a 33 meter pay zone with properties for the lower McMurray formation in an area north of Fort McMurray within the Athabasca oil sands deposit. Electromagnetic energy is coupled to the reservoir in an iterative process that enables operators to monitor and control reservoir temperature, pressure, fluid production, and energy to oil ratio, to enhance recovery of heavy oil and bitumen. This is performed by interfacing commercial electromagnetic and reservoir simulators using an in-house coupling script. The results demonstrate an ultimate oil recovery factor of +70% with an energy to oil ratio lower than 200 kilowatt hour per barrel. This is less energy per barrel than the average energy required by steam assisted gravity drainage. Though not compulsory for the process, it is observed that oil recovery is improved with water injection. This is mainly because the amount of electromagnetic energy coupled to the reservoir correlates with water saturation in the near wellbore region. Water injection helps maintain water saturation levels and improves heat convection further into the reservoir. Nonetheless, there is no need for external water supply, because the volume of injected water required to improve oil recovery is comparable to the overall volume of water produced from the reservoir. Unlike other recovery methods, this technology is expected to have low energy intensity, zero emissions, and minimized land footprint leading to responsible bitumen recovery. This paper sheds light on the capability of an innovative clean energy technology to enhance bitumen recovery from the Athabasca oil sands in Alberta. The novel technology takes advantage of clean energy to recover oil at a lower energy to oil ratio than the average ratio achieved with steam injection methods.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".