Seismic acquisition with digital point receivers and prestack reservoir characterization at China's Sulige gas field
Bibliographic record
Abstract
Sulige (Shanxi province, 750 km southwest of Beijing) is the largest onshore gas field in China (proven gas reserves of 1.1 trillion m3 in the last evaluation). Sandstone and mudstone in the main reservoir formation (He-8) were deposited in a deltaic plain of lower Permian age. Braided stream channels moved laterally and overlapped frequently, resulting in a very heterogeneous vertical stack of sand bodies. He-8 Formation has a thickness of 25–30 m but the sand layers with sufficient porosity and permeability are often less than 10 m. There is no correlation between the height of the reservoir and the total thickness of the formation, making conventional characterization based upon poststack data unreliable. This was the motivation for looking at prestack data to improve reservoir prediction.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".