Stability Evaluation of Proppant in Fractures of Gas Storage in Yulin Gas Field
Bibliographic record
Abstract
In nearly a hundred years of construction, underground gas storage has become the main natural gas storage and peak regulation means in the world. For the gas storage, the large production and high flow rate of the gas well in the actual production process will cause the backflow of proppant filled in the supporting fracture, which will bring great harm to the gas field production. In this article, when the proppant fracture reaches a stable state in the process of gas injection and production, the stress of proppant particles is analyzed, the critical velocity of proppant reflux is calculated, and then the critical production model is established; calculate the permeability change during proppant migration, then calculate the fluid velocity and production, and determine the fluid velocity range of injection and production wells in gas storage. The parameter sensitivity of velocity and flow model is analyzed. The results show that with the increase of closure stress, the critical gas flow and critical gas velocity of proppant backflow gradually increase, and the proppant filling layer is more stable. The smaller the thickness and width of the filling layer, the greater the critical gas flow and critical gas velocity of proppant backflow, the more stable the proppant filling layer, and the lesser the chance of backflow. The higher the saturation, the lower the critical gas velocity, and the more prone the proppant to reflux. It has important guiding significance for realizing the optimization of gas well production and maintaining efficient production efficiency.
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 | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".