Managing the Blackstone Swanhills Sour Gas Reservoir Pool, Western Canada
Bibliographic record
Abstract
Abstract The Blackstone Beaverhill Lake (Swanhills member) "A" Pool is a dry gas reservoir of the sour content up to 22% of H2S+CO2, one of a series of highly dolomitized late Devonian aged reef carbonate structures in the Western Canada. Discovered in 1979, the Blackstone pool is trapped at a depth of 4800 m TVD with a gas column height of 165 m and with an underlying aquifer. The pool size was initially estimated at 1,150 bcf from the early appraisals and the 1985-2000 production data, but revised due to the impact of water influx with two high rate producers watering out at high loading rates. Depleted by only six wells, the pool has produced 770 bcf of gas as of Dec 2009. The final EUR recovery factor could eventually reach 93% under optimized favorable conditions. Although the pool behaves like a single tank with an average permeability of 50 md, the complexity of dolomitized reef facies, barriers and baffles, porosity and permeability features, made it difficult to forecast the production performance and execute infill drilling plans, on the basis of integrated geoscience & reservoir engineering studies. Additional uncertainties, such as high drilling/workover cost and risks, facilities and gas gathering & processing, gas prices, also confront the pool's depletion plan. By providing a detailed field case study of the Blackstone pool, this paper demonstrates that reservoir management is a reciprocating business process between fact findings & business options constrained by cost effective measures and commercial matrixes. Timing often emerges as a critical factor. The ultimate goal is to protect and maximize the value of assets. The Blackstone pool proved to be one of a few successful high RF water-drive carbonate reservoirs. Simple water chemistry tracking turned out to be a very effective surveillance practice that altered the reservoir management plans.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".