A novel dandelion-based bionic proppant and its transportation mechanism in different types of fractures
Bibliographic record
Abstract
Low-permeability reservoirs are generally characterized by low porosity and low permeability. Obtaining high production using the traditional method is technologically challenging because it yields a low reservoir recovery factor. In recent years, hydraulic fracturing technology is widely applied for efficiently exploiting and developing low-permeability reservoirs using a low-viscosity fluid as a fracturing fluid. However, the transportation of the proppant is inefficient in the low-viscosity fluid, and the proppant has a low piling-up height in fracture channels. These key challenges restrict the fluid (natural gas or oil) flow in fracture channels and their functional flow areas, reducing the profits of hydrocarbon exploitation. This study aimed to explore and develop a novel dandelion-bionic proppant by modifying the surface of the proppant and the fiber. Its structure was similar to that of dandelion seeds, and it had high transport and stacking efficiency in low-viscosity liquids compared with the traditional proppant. Moreover, the transportation efficiency of this newly developed proppant was investigated experimentally using six different types of fracture models (tortuous fracture model, rough fracture model, narrow fracture model, complex fracture model, large-scale single fracture model, and small-scale single fracture model). Experimental results indicated that, compared with the traditional proppant, the transportation efficiency and the packing area of the dandelion-based bionic proppant significantly improved in tap water or low-viscosity fluid. Compared with the traditional proppant, the dandelion-based bionic proppant had 0.1–4 times longer transportation length, 0.3–5 times higher piling-up height, and 2–10 times larger placement area. The newly developed proppant also had some other extraordinary features. The tortuosity of the fracture did not influence the transportation of the novel proppant. This proppant could easily enter the branch fracture and narrow fracture with a high packing area in rough surface fractures. Based on the aforementioned characteristics, this novel proppant technique could improve the proppant transportation efficiency in the low-viscosity fracturing fluid and increase the ability of the proppant to enter the secondary fracture. This study might provide a new solution for effectively exploiting low-permeability hydrocarbon reservoirs.
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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 | 0.000 |
| 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 | 0.000 |
| 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".