CO2 Storage as Hydrate in Depleted Gas Reservoirs
Bibliographic record
Abstract
Abstract With the increasing concern about climate change, the public, industry, and government are showing increased interest towards reducing CO2 emissions. Geological storage of CO2 is perceived to be one of the most promising methods that could provide significant reduction in CO2 emissions over the short and medium term. However, one major concern regarding geological storage of CO2 is the possibility of leakage. Carbon dioxide under the pressure and temperature conditions encountered in most geological settings remains more buoyant than water. Processes that could lead to permanent trapping of CO2 include geochemical reactions with the formation of solid minerals. This trapping mechanism is attractive because it converts the CO2 into a solid compound. However, the time-scale of such reactions is perceived to be centuries to millennia. In contrast, the kinetics of CO2- hydrate formation — leading to trapping of CO2 in the solid form — is quite fast, providing the opportunity for long-term storage of CO2. In this paper, geological settings suitable for formation of CO2 hydrates are investigated. We study storage of CO2 in depleted gas pools of Northern Alberta. Thermodynamic calculations suggest that CO2 hydrate is stable at temperatures that occur in a number of formations in Northern Alberta, in an area where significant CO2 emissions are associated with production of oil sands and bitumen. Simulation results presented in this paper suggest that, upon CO2 injection into such depleted gas reservoirs, pressure would initially rise until conditions are appropriate for hydrate formation, enabling storage of large volumes of CO2 in solid form. Numerical simulation results suggest that, because of tight packing of CO2 molecules in the solid (hydrate), the CO2 storage capacity of these pools is many times greater than their original gas-in-place. This provides a local option for storage of a portion of the CO2 emissions there. In this paper, we study the storage capacity of such depleted gas pools, and examine the effect of various reservoir properties and operating conditions thereon. In particular, we study the effect of the in-situ gas in formation of mixed gas hydrate; the effect of rise in temperature as a result of the exothermic reaction of hydrate formation; the effect of initial reservoir pressure, temperature, and porosity; as well as conditions for avoiding the deleterious formation of hydrates around the wellbore.
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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) | 0.019 | 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".