When Does a Longer Shut-In Lead to a Larger Radius of Investigation?
Bibliographic record
Abstract
Abstract While the concept of radius of investigation is better understood for drawdown tests, its applicability to buildup tests is less certain. For example, a rule of thumb is that "one cannot see a particular feature in a buildup unless the radius of investigation during the preceding flow period has seen that feature". In this paper, we clearly illustrate that the radius of investigation of a buildup can be larger than that of its previous flow period. Another common contention is that the radius of investigation of a buildup is limited by noise dominating the late time pressure behavior. Oliver1 and later Thompson and Reynolds2 defined the radius of investigation based on the distance from the well to the region of the reservoir which has the greatest impact on the pressure derivative. We have used this approach to calculate the derivative and show that the ratio of noise to the signal from the reservoir does not necessarily increase. We show that when data is sampled appropriately, the radius of investigation of a buildup can easily go beyond that of the preceding flow period, and clearly demonstrate when this may remain unaffected by noise.
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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 | 0.010 | 0.084 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".