Numerical Investigation of Depressurization through Horizontal Wells in Methane-Hydrate-Bearing Sediments Considering Sand Production
Bibliographic record
Abstract
Sand production has been identified as a key reason limiting sustained and commercial gas production in methane-hydrate-bearing sediments. Production tests in Canada and Japan were terminated partially because of excessive sand production in pilot wells. It is meaningful to carry out numerical investigations and sensitivity analyses to improve the understanding of sand production mechanisms during the exploitation of methane hydrates. This study introduces a numerical model to describe the coupled thermal–hydraulic–mechanical–chemical responses and sand production patterns during horizontal well depressurization in methane-hydrate-bearing sediments. The model is benchmarked with a variety of methane hydrate reservoir simulators. Results show that the spatial and temporal evolution patterns of multi-physical fields are different and the hydromechanical evolutions are the fastest. Gas production and sand production rates are oscillatory in the early stages and long-term rates become stable. Gas production is sensitive to rock physical and operational parameters and insensitive to rock mechanical properties such as cohesion. In contrast, sand production is sensitive to cohesion and insensitive to rock physical and operational parameters. Although cohesion does not directly affect gas productivity, gas productivity can be impaired if excessive sand production impedes production operations. This study provides insights into the sand production mechanism and quantifies how relevant parameters affect sand production during the depressurization in methane-hydrate-bearing sediments.
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 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 | 0.001 | 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 | 0.001 |
| 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".