#WelcomeRefugees: A Critical Discourse Analysis of the Refugee Resettlement Initiative in Canadian News
Bibliographic record
Abstract
Rate decline analysis is an essential tool in predicting reservoir performance and formation property estimation. The use of historical production data to predict future performance is the focus of the empirical domain of decline analysis while the theoretical domain focuses on the use of such data to estimate formation properties. A number of attempts have been made to establish the theories of rate decline in solutiongas drive reservoirs. Such attempts have established the theoretical decline exponent b as a \nfunction of formation properties. However, none of the attempts have established a direct link between the empirical and theoretical domains of decline analysis. The purpose of this work is to establish the missing link and deploy such link in reservoir property estimation. \nIn this work, a functional relationship (equation) between the empirical (���\t) and the theoretical (�) was derived; based on the definition of a new parameter known as timeweighted average of the theoretical exponent, � \nThis new parameter was found to be related to the empirical exponent, ���\t thus establishing the link. Theoretical justifications for the ranges of values of the theoretical exponent were also offered. Consequent upon the establishment of the relationship, this work developed a new improved technique for estimating reservoir permeability. The technique was applied to a number of cases and was \nfound to yield excellent estimates of permeability even for an heterogeneous reservoir. Sensitivity analyses were performed on the results. The work also investigated non-Darcy flow effects on decline parameters. Lastly, this work provided mathematical justification for the existence of the hyperbolic family of curves in solution-gas drive reservoirs.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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".