Block to Block Interaction Effect in Naturally Fractured Reservoirs
Bibliographic record
Abstract
Abstract Initially, gravity drainage mechanism in naturally fractured reservoirs was modeled and validated by solving the available analytical equations (e.g. Firoozabadi and Hauge method in 1990). Block to block interaction effect has been included in this model. Then the effects of different parameters on recovery process were investigated and compared with the production mechanism of different models, such as, dual porosity, dual permeability. This work determined that the most effective parameters on recovery process are block height and matrix permeability. Also in the case of capillary continuity between the blocks, vertical fracture permeability has no effect on recovery process. The main conclusion drawn from this work is that reinfiltration causes a reduction in the production rate; however, it has no effect on ultimate recovery. Also it was concluded that trickled oil from blocks above always prefers to reinfiltrate into the matrix blocks below rather than flowing through the fractures. The following limitations and assumptions apply: 1-D flow.System pressure is constant.Fluid viscosities are constant.Fluids are incompressible.Model is valid only for two phase oil/gas system in the presence of immobile water.
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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".