High precision 3D seismic exploration techniques of the large mining city zone in eastern China
Bibliographic record
Abstract
Old oil fields in eastern China have high level of exploration and development, the main structural oil & gas reservoirs have been basically imaged. In order to realize the idea of continuous oilfield development and to find oil around and in the deep layers under old oilfields, researching the prospecting techniques, which are aimed at the complicated near-surface areas in oil-rich areas (the forbidden exploration area, for example, the urban zone), has to be increased In recent years, in the eastern China, a set of high precision 3D exploration techniques has been developed by carrying out the seismic work for the wide range of obstacles of old oil field - mining city zone (more than 20km2 mining area), including: special geometry design techniques based on the complex surfaces and deep objectives, geometry optimizing and implementing techniques based on the high — resolution satellite image, near-surface obstacles investigation techniques, city zone seismic shooting techniques, noise eliminating techniques for fixed source noise interference, migration imaging techniques based on energy balance, which could be provided reference for similar project.
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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 | 0.000 | 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".