A shale gas resource potential assessment of Devonian Horn River strata using a well-performance method
Bibliographic record
Abstract
Middle to Upper Devonian Horn River strata in British Columbia, western Canada, has become a proven province of commercial shale gas resource in the last few years. The shale gas resource potential in the Horn River Basin has been historically assessed based on reservoir volumetric characteristics. However, as fundamental mechanisms controlling shale gas ultimate recovery remain poorly understood, the classic theories and simulation techniques applied to evaluate recoverable gas for conventional reservoir have proven inadequate for shale gas reservoirs. Determining the ultimate recovery from production data at the well level and projecting these data to the basin level to establish the ultimate recoverable resource may provide a more realistic estimation for long-term sustainable development planning. This paper analyzes well performance of 206 wells using Arps and Valko models in the Horn River Basin with adequately protracted production records and projects these performances to the future to assess the ultimate recovery of shale gas resource. This process yields a mean estimate of recoverable methane gas resource of 114 TCF (1 TCF (trillion cubic feet) = 28.3 × 10 9 m 3 ), with a large uncertainty range of 38–217 TCF (90%–10% confidence interval). This study also suggests that the drastic variation in estimated ultimate recovery (EUR) from wells across the basin is attributed primarily to the intrinsic geological character of the shale reservoir, though advances in technology and industry practice may also contribute in some degree to this variation.
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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 | 0.001 |
| 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".