Construction cost evolution of standing column wells in the area of Montreal, Canada.
Bibliographic record
Abstract
Thanks to its role as a catalyst for geothermal projects using standing column wells (SCW), the geothermal research team at Polytechnique Montréal has been able to monitor and significantly influence drilling costs. Based on monitoring of drilling costs over a period of eight years, this presentation aims to share the strategy adopted and the means taken to reduce SCW costs in the Montreal region, Canada. As SCWs were little known in Montreal about ten years ago, drilling contractors tended to offer high prices for their construction. Discussions with contractors showed that these high costs included a significant safety margin, proportional to the risk perceived by the contractor. To change the perception of drilling contractors, our team then produced and made public plans & specifications, as well as drilling speeds and geological logs for SCWs up to 500 m deep. This strategy allowed for the public sharing of geological conditions on the island of Montreal, which reduced uncertainty for drilling contractors. In less than eight years, drilling costs have fallen from over $1,500 CAD per meter to approximately $160 CAD per meter for SCW of 500 meters. For institutional projects, we have found that the cost of SCWs now represents only 7% of the total cost of a renovation project where oil heating is replaced with a geothermal system using hydroelectricity.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".