Ice Formation During Gas Hydrate Decomposition
Bibliographic record
Abstract
Abstract A number of numerical simulation studies of gas hydrate reservoirs have indicated that the pressure reduction method known as depressurization is a promising technique to produce gas from hydrate reservoirs. In some cases, severe ice formation has been observed, leading to plugging and termination of gas production. Some researchers have suggested that if the flowing bottomhole pressure is not lowered beyond the equilibrium pressure corresponding to the freezing point of water, then ice formation may be avoided. This argument is based on the premise that the lowest temperature would occur at the wellbore. If temperature can be controlled to above zero by controlling the bottomhole pressure, then freezing should not occur. The objective of this work is to explore under what conditions ice particles form. Various cooling mechanism (cooling because of decomposition, gas expansion, etc) are studied in detail. For this purpose, a 3D mathematical model for gas production from hydrate reservoirs is introduced which incorporates energy balance, fluid flow and kinetics of the hydrate decomposition along with the ability to predict the formation of ice particles. This model is developed by modifying the GPRS (General Purpose Reservoir Simulator) platform to account for a number of mechanisms including hydrate decomposition and ice formation. GPRS is an object oriented reservoir simulator code developed at Stanford University. We will then apply this simulator to model largescale hydrate decomposition process in porous media, and demonstrate the effect of ice formation on gas production behavior. Through some case studies we investigate the conditions in which ice forms and becomes an issue. The learning for these studied are then used to suggest practical ways of avoiding ice formation. Introduction Hydrate particles are made up of natural gas molecules trapped in water molecule structures, and are considered as a potential resource for clean energy. Enormous quantities of methane gas exist in the form of hydrate in the permafrost and offshore environments. Large resources of hydrate have been explored worldwide including the North West Territories of Canada, Siberia, Alaska and Japan. In the last two decades much interest and research has been devoted towards the mathematical modelling of gas production from hydrate reservoirs. Three general techniques have been suggested to recover gas from hydrate reservoirs which are all based on breaking the stability conditions of hydrate leading to generation of gas; Depressurization, Thermal Stimulation and Inhibitor Injection. While depressurization does not require an external source of energy and is based on propagation of pressure drop from the wellbore to the hydrate decomposition zone, the thermal stimulation technique needs an external source of energy, not unlike those applied in the thermal recovery of heavy oils. Efficiency and economics of these techniques is the subject of numerous investigations. The first attempts to model hydrate formation and decomposition go back to the works done in the first decades of 1900's which aimed at preventing hydrate formation in the gas transportation pipes. Exploration of hydrate reservoirs and their potential as a new resource for energy has resulted in more research activities in the last two decades.
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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 | 0.000 |
| 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) | 0.006 | 0.001 |
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; both teacher heads agree on what is shown here.
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".