Bibliographic record
Abstract
Heavy oil technology Two projects in Canada are out to show that oil sands production need not remain in the steam age. Both are powered by electricity, though they use it quite differently. The motivations are the billions of barrels of crude in formations where current methods are not practical or economic, and a desire to find a way to produce heavy crude with less energy and water. No one is talking about replacing steam for heavy oil production—it is an extremely efficient method for delivering the heat needed to reduce the viscosity of the heavy crude called bitumen. But the potential payoffs for finding a workable alternative is huge. Of the total bitumen resource in the ground in Alberta, 7% is shallow enough to be mineable, said Todd Zahacy, senior engineering consultant for exploration and production at C-FER Technologies. While production using in-situ extraction techniques from deeper reserves has recently exceeded the output from mining, only about 9% of that vast resource is counted as reserves in Alberta’s 2012 survey of its oil, gas, and coal resources. “There is a massive prize out there if you can go after those areas that are not currently technically producible,” said Zahacy, with the research and testing company that has been evaluating electric methods for a client. The goals of these two programs are electric-powered heating methods capable of eliminating the costly equipment needed to produce steam and process large volumes of water on site. Lower-temperature methods may also reduce energy use and open up access to underground formations not suited for high-pressure steaming. The search for electric-powered heating in heavy oil fields goes back decades, but no one has made it work on a commercial scale. Les Little, executive director of energy technology for Alberta Innovates, has long followed the experiments with electric heating technology, and he knows many question if it can be more successful this time. The government technology promotion agency is backing another round of testing, though, because he said this technology “is not your dad’s electrical heating system.” The province is putting up more than USD 23 million from the Climate Change and Emissions Management Corporation—the government arm is funding half the budgeted cost—because the two electric-powered heating projects could reduce the environmental impact of heavy oil production as measured by water use and carbon dioxide emissions. That is a potent motivation in Alberta. Projects critical to tapping the oil sands, such as the Keystone pipeline running from western Canada to US Gulf Coast refineries, have been threatened by environmentalists who point out the energy and water required for heavy oil extraction mean it has a larger environmental impact than conventional production.
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 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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.059 | 0.016 |
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".