Multiphase Flow Modeling for Gas Hydrates in Flow Assurance
Bibliographic record
Abstract
Multiphase flow is a central component in all flow assurance strategies in oil and gas production. The risk of plugging of flowlines due to hydrate formation is also one of the most prevailing flow assurance problems in subsea deepwater oil and gas operations. Hence, it is critical to develop a model to account for the inter-coupling of hydrates and multiphase flow. We present a new framework to model the effect of multiphase flow on hydrates and vice-versa. In the current work, we use a two-phase (gas/liquid) hydrodynamic slug flow model and explicitly incorporate hydrates as a third phase. The model is based on fundamental multiphase flow concepts and has the capability of predicting hydrodynamic slug formation and propagation in three-phase flow. The utility of this tool is demonstrated in the modeling of hydrate formation in gas-water and gas-oil-emulsified water systems by comparing the multiphase flow behavior in terms of flow regime, slug length distribution, number of slugs, and slug frequency. For the gas/oil system with emulsified water, we perform a systematic study on the aggregation of hydrate particles and the subsequent viscosification of the slurry, and its impact on the multiphase flow behavior of the system. The results reveal that hydrate formation has a significant effect on the slugging exhibited by the system, suggesting that one may be able to infer hydrate formation from the changes in the flow characteristics. As part of the validation of this model, we have performed an extensive comparison of the two-phase flow regime predictions of our model with available experimental data, as well as with a number of models available in literature. The results show that our model predictions are in good agreement with literature and the prediction accuracy of our model is higher than all the models compared. This establishes our model as a viable multiphase flow modeling tool to predict the flow behavior in oil and gas pipelines. Hence, in this work, we demonstrate the capabilities of the model to perform transient simulations of two-phase and three-phase flow. This is the first step in the development of the model, with the ultimate goal being completely understanding the interdependence of hydrates and multiphase flow, hence enabling flow assurance engineers to develop better hydrate management strategies.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".