An Experimental Development to Characterise the Flow Phenomena at the Near-Wellbore Region
Bibliographic record
Abstract
Abstract The understanding of rock characteristic and fluid flow behavior at the near-wellbore region is an important topic. Triaxial experiment setup can help to investigate these properties. In this research, a new triaxial experimental setup has been developed where the higher scale of the parameters such as higher reservoir pressure, and comparatively larger core sample can be used. High permeable synthetic porous samples are prepared to validate the device. The new triaxial experimental setup is validated with water as a base fluid. In the validation test, real samples and synthetic samples are used. First, flow in convergent direction is studied which represents as production at the in-situ condition. Then, the flow in divergent direction is examined that may represent the injection of fluid to enhance the hydrocarbon production. The near-wellbore flow phenomena are studied with real and synthetic samples. The results indicate that using this triaxial setup pressure drop and pressure buildup test can be explained. The new scientific setup is able to reduce the scale-up gap between laboratory data and field data to get actual reservoir flow phenomena.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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".