The Practice and Cognition of Hydraulic Fracturing Technique for Shale Gas Reservoir in Southeast Chongqing
Bibliographic record
Abstract
Shale gas is an important unconventional energy resource. However its only achieved successful commercial exploitation in the United States and Canada. Shale gas well QY1 was carried out in southeast Chongqing.Taking this well as a case, the fracturing design optimization workflow and its practice are described in this paper. The fracturing feasibility of well QY1 was firstly determined by referencing all the physical parameters of target formation. Then the reservoir stress model was revised and reservoir stress profile was established as well. The reservoir simulation software (Eclipse) was applied to build reservoir geological model for predicting the gas production and determine the optimized permeability enhanced area (PEA). The unconventional fracturing model (UFM) was used to optimize the fluid volume and fracturing scale. And the final fracturing plan was made based on the optimized conclusions. This optimization workflow and the good result provide reliable technique support for the development of the shale gas reservoir in this area. Key Words: Shale gas, PEA, Fracture propagation model, UFM, Production predicting model, Optimization
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How this classification was reachedexpand
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 | 0.002 | 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 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".