Geological modeling of the oil sands reservoir by integrating the borehole and seismic data in the JACOS Hangingstone SAGD operation area, Athabasca, Canada.
Bibliographic record
Abstract
Three dimensional geological models were constructed in the JACOS Hangingstone SAGD operation area, Alberta, Canada, integrating three dimensional seismic data of 5.4 square kilometers and 76 well data. The objectives of the study were to establish the detailed reservoir distribution and configuration for the reservoir characterization and to optimize the deployment of the SAGD injector/ producer well pairs. Sedimentary environments of the Lower Cretaceous McMurray Formation, which comprises the main layer of oil sands, were considered as fluvial to upper-estuarine channel fill deposits, and oil sands reservoirs were formed as the vertically stacked incised valley fill sands. Sequence analysis using well data was conducted at first, and framework of the stacked incised valley system was established. Further detailed sequence structural model was then constructed using seismic data. Property model which describes the sedimentary facies distribution was constructed through the interpretation of the acoustic impedance inversion and multi-attribute analysis from three dimensional seismic data. Constructed models were used for the actual SAGD horizontal well pairs planning as well as the reserves estimation. Top and bottom depths of the reservoir were estimated in the range of 2.0 meters near the existing wells even in such a channel sands environment which often changes its sedimentary facies abruptly.
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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 | 0.000 |
| 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 | 0.001 | 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".