Multiple fracturing of horizontal well in shale gas productivity factors numerical simulation researching
Bibliographic record
Abstract
Shale gas is an important kind of unconventional energy, having highly the potential resources and a long developing time etc. Currently, it only has been successful exploited in the United States and Canada. As the poor reservoir property, natural low pressure and difficult development characteristics etc in shale gas, the business development of shale gas relies on horizontal drilling and fracturing technology breakthrough. Horizontal well multiple fracturing technique can form fracture network, increase the seeping area, reduce the flow resistance and improve the productivity of horizontal well, enhance the shale gas production effective, obtain industrial development successful. In this paper, we use the coalbed methane(CBM), double medium module in Eclipse numerical simulation software to establish mathematical model, to investigate the relationship between fracture system and productivity in shale gas reservoir. The permeability on fracture system, fracture conductivity, fracture spacing, fracture half length and the number of fracture have the impact on the capacityof horizontal well after fracturing. It can effectively optimize and guide multiple fracturing in shale gas horizontal well construction and forecast capacity.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".