Megareservoirs of hydrocarbons are accumulation of giant by oil and gas deposits
Bibliographic record
Abstract
The priority direction for the development of the oil and gas complex of Russia is the search for and development of giant oil and gas fields in terms of reserves, confined to natural megareservoirs of sedimentary strata. The article considers: conventional megareservoirs of oil and gas bearing basins (OGB), in which giant and unique oil and gas deposits are accumulated (on the example of the Pokur suite of Western Siberia); megareservoirs associated with commercial vanadium-bearing heavy oils and natural bitumen in unconventional reservoirs: bituminous sands in the province of Alberta (Western Canadian OGB), Permian natural bitumen in the Volga-Ural (Republic of Tatarstan) OGB, Cambrian bitumen in Eastern Siberia; megareservoirs of unconventional low-pore shale reservoirs. These accumulations of hydrocarbons (HC) can be considered megareservoirs: due to their vast areas and high saturation with kerogen. It is shown that accumulations of hydrocarbons in megareservoirs of shale formations, high-viscosity oils and natural bitumens accumulate ore concentrations of industrially valuable metals; an integrated approach to field development is economically in demand in the present conditions. Keywords: megareservoirs; collector; gigantic accumulations; oil and gas bearing basins; trace elements; natural bitumen; shale formations.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.003 | 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".