Establishment of Geological Knowledge Database for Meandering River Reservoirs in Offshore Oilfields With Large Well Spacing
Bibliographic record
Abstract
Based on quantitative logging microfacies identification, seismic constraint facies map compilation and horizontal wells architecture analysis, the reservoir geologic knowledge database of different grades configuration unit was established for meandering river reservoirs of Lower Minghuazhen Formation in Q oilfield. The results show that the average point bar sand body width is 360-783 m, the average sand body thickness is 4.0-8.5 m, the ratio of width to thickness mainly distributed in 40-100. Average lateral accretion layers dip is 5.7°, lateral accretion layers horizontal interval mainly distributed in 70-200 m. On the basis of reservoir geological knowledge database, a fine geological model was established together with sequential indicator method and equivalent characterization method. Base on the reservoir geologic knowledge database and geological modeling results, 130 adjustment wells were successfully deployed and implemented at the comprehensive adjustment process of Q oilfield, these wells made an obvious oil production increase effect.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.008 | 0.006 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".