Model verification: synthetic single pattern simulations using seismic reflection data
Bibliographic record
Abstract
During Phase 1 of the Weyburn Project (2000-2004), 4D reflection seismic data were used to map CO2 migration within the Midale reservoir, while an extensive fluid sampling program documented the geochemical evolution triggered by CO2-brine-oilmineral interactions. The aim of this task (3b.11) is to exploit these existing seismic and geochemical data sets, augmented by CO2/H2O injection and HC/H2O production data toward optimizing the reservoir model and thereby improving site characterization and dependent predictions of long-term CO2 storage in the Weyburn-Midale reservoir. Our current project activities have concentrated on completing and testing a stochastic inversion method that will identify reservoir models that optimize agreement between the observed and predicted seismic response. This report describes the results of a validation test that uses synthetic seismic data to identify optimal porosity/permeability distributions within the reservoir. The report partially fulfills deliverable D3: “Model verification: synthetic single pattern simulations” in the project’s statement of work. A future deliverable will describe verification activities related to the geochemical inversion algorithm.
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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 | 0.001 | 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 | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".