Bibliographic record
Abstract
History of Multiple Pressure Coil Tubing Instrumentation The evolution of coil-tubing instrumentation has been primarily driven bythe ongoing development of SAGD projects. In 1995, one of the earlierproponents of the technology, Alberta Energy Company, went looking for acompany that could provide a means to instrument horizontal well pairs used inthe SAGD process. Concurrently, PROMORE Engineering Inc. had embarked on aninitiative to develop high temperature pressure sensors. The two companies setout to design and manufacture coil-tubing instrumentation that would remain drywith special ports accessing the wellbore. Initial prototypes were designed forinjection and production well(s) and incorporated multiple pressure andtemperature sensors, bubble tubes and conventional thermocouples (Figure 1).Based on continued co-operation, the two companies patented the CT-MORE(Coil-Tubing Conveyed) monitoring system in 1998, which provides theinstrumentation cornerstone of most SAGD projects today. Commercial Development Based on the commercialization of SAGD and the ensuing need to reduce costsfrom pilot project phases, PROMORE set out to streamline the manufacturing andinstallation process. With an initial investment exceeding $1.0 million, thecompany was able to reduce the dependence on coil-tubing services inconjunction with reducing the average size of CT-MORE Systems (Figure 2).Several design changes allowed the CT-MORE diameter to be reduced from 1-in. to1 1/4-in. Other designs were developed to improve overall wellbore hydraulicsand 1-in. and 3/4-in. CTMORE's became available. These changes and investmentreduced manufacturing costs resulting in savings to the operating companies.Figure 2 shows the decrease in manufacturing costs which resulted in largesavings to the operating companies. As noted on the plot PROMORE's investmentin SAGD resulted in a service entity with complete control over manufacturing.Note: third part coil tubing services are no longer required formanufacturing. In addition to the manufacturing process, it became evident that newdeployment techniques and procedures would have to be developed, especially inconsideration of the use of smaller diameter CT-MORE strings. Two uniquesystems allowed the CTMORE systems to be deployed economically.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".