A Quantitative and Visual Experimental Study: Effect of Fracture Roughness on Proppant Transport in a Vertical Fracture
Bibliographic record
Abstract
Abstract The roughness of fractures may play an important role in affecting the migration and placement of proppants during hydraulic fracturing operations. Previous studies focused on investigating the proppant transport in smooth vertical fractures, which did not consider the effect of the fracture-surface roughness. We examine the migration of proppants in rough and vertical fractures and then quantitatively reveal the effect of roughness on the instantaneous proppant transport and final proppant placement. Two types of rock samples (marble and granite) are fractured with the Brazilian test and molded to manufacture 20 × 20 × 5 cm transparent replicas. The surface roughness of these rock samples was first characterized by fractal dimensions. Then, the dyed fracturing fluid with a given proppant loading was injected into the rough vertical fracture. In each test, the inlet pressures were continuously monitored in order to obtain the differential pressure across the fracture model while the proppants were being transported in the fracture. The process was videotaped to real-time track the proppant distribution in the rough fracture. The proppant-transport behavior in the rough and vertical fracture was observed to be totally different from that in the smooth fracture. The major experimental findings include the following: 1) The proppant in a rough vertical fracture does not progress as a regular sand bank that commonly occurs in the smooth fracture, but rather an irregular-shape sand clusters with fractal characteristics; 2) In the rough and vertical fracture, the phenomenon of proppant bridging is visually observed, and such phenomenon is more likely to occur in the location with a larger roughness height. This implies rough fracture could promote a wider spreading of the proppant in the fracture compared to smooth fractures, and; 3) The existence of roughness enhances the vertical displacement of fluid containing proppants. These effects are also favorable for obtaining a better filling of the proppants in the fracture. Our experimental study reveals the mechanisms of proppant transport and distribution in real vertical fractures under the influence of roughness effect.
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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".