Analysis of the Influence of Different Fracture Network Structures on the Production of Shale Gas Reservoirs
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Bibliographic record
Abstract
Volume fracturing is a key technology in developing unconventional gas reservoirs that contain nano/micron pores. Different fracture structures exert significantly different effects on shale gas production, and a fracture structure can be learned only in a later part of detection. On the basis of a multiscale gas seepage model considering diffusion, slippage, and desorption effects, a three-dimensional finite element algorithm is developed. Two finite element models for different fracture structures for a shale gas reservoir in the Sichuan Basin are established and studied under the condition of equal fracture volumes. One is a tree-like fracture, and the other is a lattice-like fracture. Their effects on the production of a fracture network structure are studied. Numerical results show that under the same condition of equal volumes, the production of the tree-like fracture is higher than that of the lattice-like fracture in the early development period because the angle between fracture branches and the flow direction plays an important role in the seepage of shale gas. In the middle and later periods, owing to a low flow rate, the production of the two structures is nearly similar. Finally, the lattice-like fracture model is regarded as an example to analyze the factors of shale properties that influence shale gas production. The analysis shows that gas production increases along with the diffusion coefficient and matrix permeability. The increase in permeability leads to a larger increase in production, but the decrease in permeability leads to a smaller decrease in production, indicating that the contribution of shale gas production is mainly fracture. The findings of this study can help better understand the influence of different shapes of fractures on the production in a shale gas reservoir.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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 it