Detecting and Quantifying Leakage Through Defective Borehole Seals: A New Methodology and Laboratory Verification
Bibliographic record
Abstract
Abstract A new method for quantifying leakage through poorly sealed boreholes is presented and verified using a laboratory scale sandbox experiment. The method applies to a leaky borehole between two aquifers separated by an aquitard. A nonreactive tracer is injected into an upper aquifer piezometer, and the lower aquifer is pumped at a fixed rate. First, the presence of the tracer in the recovered water indicates the existence of the hydraulic short-circuit and cross-contamination. The leakage rate associated with the pumping rate can then be determined by measurement of the recovered tracer concentration. By correlating the leakage rate with the pumping rate, the hydraulic properties of the defective seal can be determined and the degree of cross-contamination can be predicted for any pumping rate. The method will be useful for practitioners who need to evaluate the quality of a borehole seal. The method is successfully tested using a laboratory sandbox experiment.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".