A 2-D analytical solution to infinite conductivity fracture injection pressure transient analysis in non-Newtonian/Newtonian composite infinite reservoirs
Bibliographic record
Abstract
Abstract Two fluid regions are usually created during either water or polymer injection into an oil reservoir for enhanced oil recovery. The two fluid regions create a composite reservoir system that requires analytical solution that can be used to evaluate the injection performance. In this study, we present a 2-D solution for non-Newtonian fluid in the inner zone coupled with infinite boundary in the outer zone using power law model. The outer zone fluid can either be Newtonian or non-Newtonian. Moreover, the mathematical model is formulated such that either zone can be with non-Newtonian power law fluid or Newtonian fluid. The infinite conductivity fractured solution obtained was compared with the ones obtained using the radial line source solution that had already been developed in the literatures, and a perfect match was obtained. An application was made to three examples that have been presented in a previous work, and satisfactory results were obtained. The dimensionless pressure drops during the early linear flow regime for all values of flow indices are the same, but with deviation during radial flow regime.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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 | 0.001 | 0.000 |
| Open science | 0.001 | 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".