Poststack inversion of broadband seismic data from Alberta, Canada
Bibliographic record
Abstract
The Hussar experiment was carried out in September 2011 with the purpose of acquiring broadband seismic data, including low frequencies, to be used in inversion methods. Three wells located close to the seismic line and a dynamite-source dataset, acquired with three-component 10 Hz geophones, were used for a post-stack inversion test using commercial software. Several low-frequency cut-off filters applied to the data were tested with the 3-5 Hz model being selected as the optimum. The resultant impedance reflects lateral changes that were not present in the initial model and therefore are derived from the seismic reflections. Impedance changes in the target zone shows the general trend and relative variations, which would allow changes in the reservoir as variations in the rock properties occur. A final inversion was performed to simulate traditional approaches when the low-frequency component is absent in the seismic data. Filtered seismic-data (10-15- 60-85 Hz) and an initial model with a 10-15 Hz cut-off were used for this test. The results at the well locations show a good match but the lateral variation and character of the events resemble more the initial model character.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".