Numerical Study of Gas Production from a Methane Hydrate Reservoir Using Depressurization with Multi‐wells
Bibliographic record
Abstract
Abstract With the implementation of the production tests in permafrost and offshore regions in Canada, US, Japan, and China, the study of natural gas hydrate has progressed into the stage of technology development for industrial exploitation. The depressurization method is considered as a better strategy to produce gas from hydrate reservoirs based on production tests and laboratory experiments. Multi‐well production is proposed to improve gas production efficiency, to meet the requirement for industrial production. For evaluating the applicability of multi‐well production to hydrate exploitation, a 2D model is established, with numerical simulations of the performance of the multi‐well pattern carried out. To understand the dissociation behavior of gas hydrate, the pressure and temperature distributions in the hydrate reservoir are specified, and the change in permeability of reservoir sediments is investigated. The results obtained indicate that multi‐well production can improve the well connectivity, accelerate hydrate dissociation, enhance gas production rate and reduce water production as compared with single‐well production.
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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 | 0.000 | 0.001 |
| 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) | 0.002 | 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".