Development characteristics of organic-rich shale and strategic selection of shale gas exploration area in China
Bibliographic record
Abstract
Shale gas,as a new type of unconventional natural gas resources,its exploration and development have got great success in the U.S.A.,and fast progress in Canada,Australia and other countries.Shale gas exploration in China has just started and its study is still focused on shale gas reservoir conditions and favorable area evaluation.China's preferred shale gas favorable area is mainly related with organic-rich clay and shale,and the major optimization is a prospective area for shale gas.Complicated geological background and multi-stage evolution lead to many types of China's petroleum basins whose structures are complex.Different evolution history of each basin directly controls the development and distribution of organic-rich shale.By the different formation environment,organic-rich shale can be divided into marine thick layer organic-rich shale,continent-sea intercrossing organic-rich shale,coal-bearing strata organic-rich shale,and lacustrine organic-rich shale.Among them,the thick layer marine organic-rich shale is of first priority in China's near future shale gas exploration;continent-sea intercrossing organic-rich shale and coal-bearing strata organic-rich shale are thin in single-layer,but they have symbiotic conditions with tight sandstone gas and coal-bed gas,so the multi-layer co-mining technology of shale gas,tight sandstone gas and many other types of natural gas resources has great practical significance;the lacustrine organic-rich shale's diagenesis degree is generally low,and needs further optimization of a horizon with high-strength rock and the conditions of open hole completion for exploration and development.
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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 | 0.002 | 0.002 |
| 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) | 0.001 | 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".