Unconventional Oil Potential Tends to Change the World Oil Market
Bibliographic record
Abstract
Falling unconventional oil production costs and a significant increase in its production (especially in the North America) can potentially impact the structure of the global oil trade. As a result, it will create additional risks for the producers of conventional oil, which production costs went up sharply in recent years. The aim of this study is the analysis and forecast of the development of unconventional oil production, its potential impact on the international oil market and the traditional exporting countries. The forecast for the future state of the oil industry was carried out with the help of a modeling complex SCANER, developed at the Energy Research Institute of the Russian Academy of Sciences (ERI RAS). The estimates of the future situation in the oil market were based on the forecasts of the economic development of the world’s main countries and regions, which then were compiled by the Russian Energy Agency in 2012. The modeling results showed that unconventional oil had a great development potential. According to the ERI RAS forecast, its production by 2035 could increase by almost fivefold as compared to 2010 (i. e., from 2.3 mb/ d to 11.4 mb/d), around 90% of oil from unconventional sources will be produced in the North America. Such an increase in production may also lead to the situation, when the North America will reduce its dependence on imported oil. In the future, this will lead to a redistribution of oil trade flows in the world and will impose a negative impact on the producers in Europe, the Commonwealth of Independent States (CIS), the Asian-Pacific region (APR) and, to a lesser extent, in the Middle East.
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".