Overdamped Slug Tests in Aquifers: The Three Diagnostic Graphs for a User-Independent Interpretation
Bibliographic record
Abstract
Abstract An overdamped slug test may be analyzed using several methods, which are known to yield different results for the hydraulic conductivity. The methods belong to three groups: group 1 neglects the influence of the solid matrix strain, group 2 is for tests in aquitards with delayed strain caused by consolidation, and group 3 tries to take into account the elastic and instant solid matrix strain. This paper deals with slug tests in aquifers and, thus, considers the groups 1 and 3. In practice, users select a single theory, which avoids having divergent values. However, this means that something is wrong with the theories. This paper explains what is wrong, and why. First, an approach is proposed to detect inconsistencies. The test data are presented in two semi-log graphs and a third, derivative graph along with theoretical predictions: these are the three diagnostic graphs. The shapes of the semi-log plots are shown to be altered markedly by a small inaccuracy in assumed piezometric level. The derivative plot does not depend upon this assumed piezometric level, but can verify its correctness. Most often, the assumed piezometric level cannot be defined with enough accuracy to avoid systematic bias in the test data. If this is ignored, the results of the first two plots cannot fit a theory. The derivative plot has been used for thousands of slug tests in confined and unconfined aquifers. It appears that all test data follow only one theory, that of group 1. An examination of equations and assumptions concerning solid matrix deformation shows that the group-3 theory, unfortunately, mistreats the links between fluid mechanics and solid mechanics. Therefore, the proposed three-diagnostic-graphs approach unifies the two theories, helps us to find and to be aware of what is wrong in the group-3 theory, and, most important, it yields a user-independent final result.
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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 | 0.003 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".