Joint PP‐PS inversion at Pikes Peak oilfield, Saskatchewan
Bibliographic record
Abstract
The method of simultaneous PP-PS inversion has recently been developed and tested on the 3-D Blackfoot seismic data set. This paper shows the application of this method on 3C-2D seismic data from Pikes Peak oilfield. The inversion was accomplished with a newly installed inversion module in ProMAX. After careful prestack processing, five limited-offset stacked sections for each of the vertical and radial components were created, migrated and correlated. The inversion module assumes that the data have been trace-equalized and, to restore the average AVO behaviour, it requires the input of scalar RMS amplitude estimates for each offset. These were obtained by creating elastic synthetic seismograms for P-P and P-S from well control and calculating the RMS amplitudes for each offset. Then the ten datasets, together with the RMS amplitude values and a background velocity model, were input into the joint PP-PS AVO inversion module in ProMAX. The weighted stacking requires estimation of the P-P and P-S incidence angles at each depth level and
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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 | 0.001 |
| 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".