Advances in World Oil Shale Production Technologies
Bibliographic record
Abstract
Abstract The development of domestic oil shale resources has regained significant attention in the past few years. Several factors have contributed to this, including high oil prices, emerging recovery technologies, increasing world demand for liquid hydrocarbons, and the continued decline in U.S. conventional oil production. In recent years, several initiatives have been taken by government and the private sector to encourage the development of a domestic oil shale industry. The United States has the largest and most concentrated deposits of oil shale in the world, including nearly 2.0 trillion barrels across the eastern and western states. However, until recently, U.S. oil shale development efforts have largely been in hiatus. Several other nations also have significant oil shale resources, including China, Estonia, Israel, and Turkey. Since 2006, more than 25 U.S. companies have made public information about new oil shale technologies. Other non-U.S. companies have also achieved significant advances. An analysis has been conducted to identify and profile advanced oil shale technologies that improve performance and help mitigate barriers to commercialization. Advances include reduced water use, improved energy efficiency and net energy balance, better carbon and emissions management, reduced surface impact, spent shale use and disposal, and effective groundwater protection. The analysis addresses both surface and in-situ processes and includes technologies intended to produce liquid fuels or to fire electric power generation. Notable examples include the Kiviter and Galoter retorts in use in Estonia, the Alberta Taciuk Processor considered for use by OSEC in Utah, Shell's In-Situ Conversion process under consideration in Colorado and in Jordan, Petrobras’ Petrosix Gas Combustion Retort (and variations) in use in Brazil, the Raytheon/CF radio-frequency with critical fluids technology just licensed by Schlumberger, and the EcoShale process under development in Utah. The results of the analysis suggest significant promise that production of oil from oil shale can be technically and economically feasible while meeting rigorous industry and public standards for technical performance, resource conservation, and environmental protection. It also identifies areas where further research, development, and demonstration are needed.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.004 |
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".