Investigation of Blocking Characteristics by Particles in Heterogeneous Reservoir
Bibliographic record
Abstract
A mathematical model of suspension filtration in porous media has been established based on mass conservation principle and characteristics of particles depositing and blocking. On this basis, percolation rules and blocking characteristics of suspension in heterogeneous reservoir were investigated. It is showed that suspension injection could remarkably reduce the permeable ratio and improve the heterogeneity significantly. Low-speed and low-viscosity injection could achieve shallow profile control, and high-speed and high-viscosity injection could achieve deep profile control. Adjusting the injection rate or viscosity of carrying fluid slug at the right time to make the particle retention concentration profile in thief zones and the water-flood front keep consistent could achieve dynamic profile control. For the reservoirs without a good interlayer, the optimum injection rate and viscosity of carrying fluid were chosen based on the connectivity of layers, and in the reservoirs with good interlayers the injection rate and viscosity should be lowered appropriately under the field permitting conditions. When the suspension concentration was constant, the instantaneous fractional flow of high permeable layer first decreased sharply and then ramped up with the increasing injection volume. Initial percolation coefficient is the basis of a high utilization of suspension and a good result in profile control. Key words: Heterogeneous reservoir; Suspension; Percolation; Profile control; Retention concentration; Blocking characteristics
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".