Research on Sesmic Attribute Reservoir Prediction Method: Taking the Shang Block 2 of Sanzhao Sag as an Example
Bibliographic record
Abstract
Block 2 is located at the northeastern end of the Sanzhao sag in the Liao Basin.The main oil layer is Fuyang oil layer.There is a problem that the sand body develops rapidly and the reservoir distribution is not clear. In order to solve the problem of modification, this paper uses the seismic attribute technique to analyze the lateral distribution characteristics of the reservoir in the Shang 2 block of the Sanzhao Sag in the study area. On the basis of establishing the forward modeling by ray tracing method, the influence analysis of mudstone interlayer thickness and sand-ground ratio forward analysis are carried out. The analysis results show that the sedimentary environment of the Fuyang oil layer is mainly the sub-facies of the delta diversion plain, which develops the diversion channel, the diversion bay and the mat-like sand microfacies, and the channel is mainly distributed in the eastward direction.
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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 | 0.001 |
| 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 | 0.001 |
| 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".