Bibliographic record
Abstract
Statement of the Problem: Microwave energy is successfully being used in the petroleum industry (inspecting coiled tubing/ line pipe, measuring multiphase flow, and the mobilization of asphaltic crude oil). Depletion of conventional crude reserves is accompanied by growing economic demand for various fuel types. In Canada, efforts have intensified to develop microwave irradiation technology for in situ enhanced oil recovery of large deposits of heavy oil/bitumen. Of the estimated 30 billion barrels of heavy oil in place, about 26 billion barrels are considered unrecoverable using current technology. Objectives included studying microwave process conditions that affect the upgrading of heavy oil/bitumen to synthetic crude, achieve up to 50% desulphurization and obtain preliminary data on process design and economics. Methodology & Theoretical Orientation: Typical experiments including mixing of oil with one or more additives, and exposing to various dosages of low pressure microwave radiation. The microwave reactor was constructed from a domestic microwave oven and modified to allow for the accommodation of a mixer, temperature monitor and pressure in the reactor and interfaced with a desktop computer for data acquisition. Power level and irradiation intensity were at level high. Findings: Results obtained with GC-MS showed evidence of fragmentation process in heavy oil/bitumen samples but, no significant change in molecular structure for majority of the light crude oil samples after being subjected to microwave irradiation. Average reduction in sulfur content of 16% and 39.4% were obtained for heavy oil and light oil, respectively. Conclusion & Significance: This work has shown strong indications for the employment of microwave technology not only for hydrocarbon extractions but for in situ upgrading and field upgrading of heavy oil/bitumen desulphurization of crude oil, and future upgrading of coal and oil shale. Overall, microwave technology presents the best alternative, economically and environmentally, to existing technologies for enhanced oil recovery operations and processing.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 0.005 |
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 source (direct Gemma or distilled Codex), 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".