Fundamental Behaviors and Borehole Deformation on Wellbore Stability and Sand Production in Conventional and Hydrates-Bearing Gas Reservoirs
Bibliographic record
Abstract
Abstract A general formulation for a coupled Thermal-Hydraulic-Mechanical with hydrate Dissociation (THMD) system is developed and applied to sand prediction for conventional gas and gas hydrate bearing sediments (GHBS). Two-phase fluid and conductive heat flow are coupled to an elastoplastic geomechanics model. Series of solutions for simplified models are presented. Fundamental geomechanics behaviors before and after plastic yielding, sanding, and gas hydrate dissociation are defined, discussed, and simulated differently and sanding onset for both conventional gas formations and GHBS are defined by an effective plastic strain (EPS) criterion. The accuracy and reliability of the proposed conventional model are verified by comparing the model prediction with the results of hollow cylinder tests on two different types of sandstone. The advantages of using the EPS over stress-based criteria as an indicator for onset of borehole collapse and sand production are discussed. Introducing a moving gas hydrate dissociation zone (front), the fundamental geomechanics behaviour and elastoplastic deformation of the skeleton formation are highlighted. The effects on sand prediction due to the characteristics of non-linear plastic yielding criteria and gas flow in porous media are also emphasized.
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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 | 0.000 |
| 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 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".