Am I Really Predicting Natural Fractures in the Tight Nordegg Gas Sandstone of West Central Alberta? Part II: Observations and Conclusions
Bibliographic record
Abstract
This two part effort is concerned with understanding and predicting fracture density in the Nordegg of West Central Alberta. In particular we are concerned with fractures that might be encountered by horizontal drilling of this tight gas reservoir. The ultimate goal of these efforts is to build the fundamental knowledge of fracture density that will help in the planning of the most prolific horizontal wells from this formation. The key fundamental stepand our goal in this workis a quantitative analysis of fracture prediction techniques for the Nordegg using objective and scientific validation data. To aid us in this effort, we have validating data from FMI logs and from a microseismic survey shot over one of three horizontal wells in the area. We also have extracted attributes such as AVAz, VVAz, Curvature and Coherence from the 3D surface seismic data that covers the area. In part one of this effort we used the FMI data to illustrate that the fractures are almost uniformly vertical and aligned. This satisfies key theoretic requirements of AVAz and VVAz.
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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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".