The Development of Non-Conventional Oil and Gas in Indonesia
Bibliographic record
Abstract
Oil and gas fuel from unconventional types of reservoirs was the development of alternative sources in addition to oil and gas fuels from conventional type reservoirs that can be obtained to meet domestic needs. The development of unconventional oil and gas reservoirs has developed rapidly outside Indonesia, such as in North America and Canada. One type of unconventional oil and gas reservoir was obtained from shale rock reservoirs. Hydrocarbon shale produced from shale formations, both source from rock and reservoir. This unconventional hydrocarbon has a big potential to be utilized. In this study, an analysis of the development of unconventional oil and gas from Shale Hydrocarbons carried out in Indonesia. This research included the distribution of shale reservoir basins, the number of unconventional shale reservoir resources, factors affecting the development of unconventional oil and gas in shale reservoirs in Indonesia, efforts made by the government to promote exploration activities, exploitation of shale reservoirs in Indonesia, and existing regulations for non-conventional oil and gas. The development of unconventional oil and gas reservoir shale needed to be developed immediately and will attract investors to meet domestic needs for renewable energy needs. From the geological data obtained, there were 6 basins and 11 formations that analyzed for commercialization. Tanjung and Batu Kelau Formation was a prospect formation from 4 desired data categories. In terms of regulation, it still needed improvement to increase the interest of upstream oil and gas entrepreneurs in the unconventional oil and gas shale reservoir. Research in the field of unconventional oil and gas exploitation technology for hydrocarbon shale needed to be improved.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".