A multicomponent 3D seismic data study from an oil sands field, Alberta, Canada
Bibliographic record
Abstract
Oil sands in the Athabasca region of Alberta are a major hydrocarbon resource. Kelly and Lawton (2012) utilized time-lapse seismic data to study the McMurray formation in the Athabasca region with a detailed geological interpretation of their pre-steam baseline survey. Isaac (1996) processed and interpreted multicomponent 3D seismic data in a heavy oil field in Northeast Alberta, obtaining excellent converted wave volumes. In this project, a multicomponent 3D seismic dataset is used to image and characterize an Athabasca oil sands field. The data provided consists of fully processed PP seismic data, and three-component raw seismic data. The PP data is used for an initial, full volume interpretation including: picking several key reflection horizons, well log ties and post-stack impedance inversion. Joint processing of the PP and PS components is currently underway with promising PS reflectivity being observed. Presentation Date: Wednesday, October 19, 2016 Start Time: 1:55:00 PM Location: 170/172 Presentation Type: ORAL
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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 | 0.000 | 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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 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".