New Completion Techniques Improve Production Rates in a Maturing Gas Reservoir
Bibliographic record
Abstract
To ensure continued economic success of drilling new wells in maturing gas or oil fields, it is often necessary to find methods to reduce well costs or to improve stimulation efficiency. Imperial Oil Resources applied the emerging technologies of grass-roots coiled tubing drilling and coiled tubing fracturing in the Tilley Milk River Gas Unit. This paper will describe the impact of these new technologies on well economics and production.In 2000, grass-roots coiled tubing drilling was used on 9 wells in the Tilley field. Drilling costs were 15% below estimates. Coiled tubing fracturing was also applied to the wells drilled in 2000. First year average gas productivity was 50% higher than expectations, leading to investment reappraisals indicating that well reserves were 30% above previous estimates. In 2001 an additional 25 wells were fracture stimulated with coiled tubing also showing increased production rates.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".