Electro-Thermal Dynamic Stripping Process<i>Integrating Environmentalism with Bitumen Production</i>
Why this work is in the frame
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Bibliographic record
Abstract
Abstract The Electro-Thermal Dynamic Stripping Process(ET-DSP™) was commercialized as an environmental remediation technology to remove volatile soil contaminants. After nearly ten years of use, it has been adapted for the thermal stimulation and recovery of bitumen from oil sand reservoirs. A proof of concept field pilot [McGee, 2008] in the McMurray formation was conducted in 2007 and was deemed to be successful. Using a tight well spacing, the pilot demonstrated the effective recovery of approximately 75% of the original bitumen in place. Sand production was minimal and the produced bitumen was emulsion free. An expanded field test is currently underway to establish commercial viability of the ET-DSP™ process as an in-situ recovery process. Validation and calibration of the computer simulation model from the initial pilot test is presented along with details of the expanded field test. The Athabasca Oil Sands are well known to the public as open-pit mining or SAGD in-situ projects. Approximately two-thirds of the Athabasca Oil Sands resource base occurs at depths that are defined as either too deep to surface mine or too shallow for currently available in-situ techniques and concerns regarding environmental issues that arise from these methods have the potential to slow their development. The ET-DSP™ process represents an alternative in-situ recovery technology that delivers significant environmental advantages in addition to its ability to access bitumen reserves that otherwise would be not recoverable. With growing public expectations for reduced greenhouse gas emissions, reduced fresh water usage and improved management of waste water, as well as the accelerated reclamation of disturbed land and boreal forest, there are many drivers to support the commercial development of the ET-DSP™ technology.
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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 | 0.001 | 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) | 0.000 | 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 it