Time-lapse seismic and AVO modelling, White Rose Field, Newfoundland
Bibliographic record
Abstract
We have applied FluidSeis, well logs and AVO modelling to investigate the change in seismic response due to fluid substitution in the White Rose Field. The White Rose Field has a gas cap, an oil leg and a water drive. Three scenarios are presented. A water drive has water replacing the oil in the oil leg up to residual oil saturation. A gas drive has gas replacing the oil in the oil leg up to residual oil saturation. A final scenario has gas invading the upper half of the oil leg and water invading the lower half of the oil leg. Using PVT data and inferred post-production saturation, new sonic logs and density logs are generated. Synthetic seismic and AVO models are compared before and after production. Reflection coefficients at the gas-oil contact (GOC) and the oil-water contact (OWC) change in magnitude approximately 15%. The synthetics indicate that P-P and PS AVO responses can be used to observe the changes in fluid distributions. The change in density due to fluid substitution appears to be the major factor in changing the seismic response. This study indicates that the White Rose Field is a good candidate for timelapse seismic monitoring of fluid movements.
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".