Mapping Middle Triassic Doig Sandstone reservoirs in northeast British Columbia using seismic attributes
Bibliographic record
Abstract
The Doig sandstone reservoirs have historically produced oil and gas in northeast British Columbia and northwest Alberta, Canada. These reservoirs occur in the study area as N-S trending linear sandstone geobodies 10-30 m in thickness at many places, and some tens of kilometers long. The challenge is the determination of the reservoir sands 20m in thickness from seismic data that has an average bandwidth of 10-60 Hz. In the area under study, comprising the Fireweed, Buick Creek West and the Stoddard areas in northeast British Columbia, the reactivation of the deeper fault structures also have some tectonic control on the Doig sandstones of interest. Therefore, the challenge is to identify not only the spatial variability of these Doig sands but also crosscutting faults and fractures. We address these challenges by first enhancing the bandwidth of the available seismic data using spectral inversion to estimate thin bed reflectivity, followed by relative acoustic impedance and unconstrained waveform classification to map the reservoir heterogeneity. This is followed by generation of coherence and curvature attributes to detect minor faults and fractures.
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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 | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".