Reduction of global natural gas hydrate (NGH) resource estimation and implications for the NGH development in the South China Sea
Bibliographic record
Abstract
There have been at least 29 groups of estimates on the global natural gas hydrate (NGH) resource since 1973, varying greatly with up to 10,000 times and showing a decreasing trend with time. For the South China Sea (SCS), 35 groups of estimations were conducted on NGH resource potential since 2000, while these estimates kept almost the same with time, varying between 60 and 90 billion tons of oil equivalent (toe). What are the key factors controlling the variation trend? What are the implications of these variations for the NGH development in the world and the SCS? By analyzing the investigation characteristics of NGH resources in the world, this study divided the evaluation process into six stages and confirmed four essential factors for controlling the variations of estimates. Results indicated that the reduction trend reflects an improved understanding of the NGH formation mechanism and advancement in the resource evaluation methods, and promoted more objective evaluation results. Furthermore, the analysis process and improved evaluation method was applied to evaluate the NGH resources in the SCS, showing the similar decreasing trend of NGH resources with time. By utilizing the decreasing trend model, the predicted recoverable resources in the world and the SCS are (205–500) × 1012m3 and (0.8–6.5) × 1012m3, respectively, accounting for 20% of the total conventional oil and gas resources. Recoverable NGH resource in the SCS is only about 4%–6% of the previous estimates of 60–90 billion toe. If extracted completely, it only can support the sustainable development of China for 7 years at the current annual consumption level of oil and gas. NGH cannot be the main energy resource in future due to its low resource potential and lack of advantages in recovery.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".