Sizing Conformance Control Treatment Based on Law of Gel Transportation Through Porous Media
Bibliographic record
Abstract
Treatment volume sizing is quite indispensible to conformance control project design. The sizing methods used currently suffer from such disadvantages as oversimplifying the law of gel transportation through porous media or completely neglecting it, and give calculation results far from optimal. A new sizing method is presented to take the transportation law into account. First, theoretical analysis, physical simulation and numerical simulation are employed to conduct qualitative analysis on how gel transports between one injector and one producer. It was found that most of gel injected into formation would migrate through the effective water-swept region toward the producer. This region, low in flow resistance, can be approximately deemed as the overlap of two equirotal circles. The intersection angle of the two circles is called water-swept angle and dominates the area of this region. Water-cut performance of the producer, mobility ratio and relative permeability-saturation relation can be used to compute this angle. Given the optimal treatment distance, the area of the gel distribution region will be determined. Then treatment volume can be determined by multiplying the area by the water-swept thickness. Its consideration of fluid properties, rock properties and well performance allows this new method to gain an advantage over other sizing methods. In a field case, this method yielded much smaller treatment volume and saw good response to treatment. Keywords: water channelling; conformance control; treatment volume; physical simulation; numerical simulation; effective water-swept region
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.003 |
| Science and technology studies | 0.000 | 0.003 |
| Scholarly communication | 0.000 | 0.007 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".