Design and deployment of an integrated instrumentation system in a monitoring well at the Aquistore Geological CO2 storage project, Saskatchewan, Canada
Bibliographic record
Abstract
This paper provides an overview of the Aquistore geological CO2 storage project initiated in Western Canada in early June 2011. The Aquistore site is located in south-eastern Saskatchewan, Canada, near the city of Estevan. Initially, 1,000 tonnes/day of CO2 will be injected into a deep, highly saline aquifer at near 3.4 km depth in the Williston Basin. The injection interval is characterised by a thick sandstone aquifer of the Deadweed and Winnipeg Formations, and is overlain by the Icebox Member of the Winnipeg Formation and by the Praire Evaporite. The measurement, monitoring and verification program of Aquistore provides an opportunity to develop and implement effective methods for monitoring CO2 storage sites and ensure conformance of the storage process through continuous monitoring. In particular this paper will focus on the completion of the dedicated observation well, located at 150 m from the main injector, containing a fibre-optic distributed temperature system, fibre-optic distributed acoustic system, multiple pressure and temperature gauges and one fluid recovery system. Many of these tools are able to measure over the full depth of the well (3,400 m). This integrated down-hole monitoring system was casing-conveyed, accomplished by wrapping the tools around the main casing during its installation. The integration of the information from this monitoring program will provide valuable insights for similar projects and the professional community considering the deployment of unique multiple-instrument strings in the field of geological storage of CO2.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".