Simplified Reaction Kinetics Model for In-Situ Combustion
Bibliographic record
Abstract
Abstract We integrate the results of six one dimensional combustion tube tests and several reaction kinetics experiments conducted with Thermogravimetric Analyzer and Differential Scanning Calorimetry (TGA/DSC) to investigate fully the burning characteristics of a Canadian bitumen (8.6 °API, 54,000 cP at 25 °C). Our ultimate goal is to estimate the variations in the chemical reactions occurring during in- situ combustion (ISC) within a reservoir which has heterogeneously distributed fluid saturations. Thus, six combustion tube experiments are conducted at varying initial water (Swi=0%, 16%, and 34%) and oil (Soi=34%, 54%, and 84%) saturations. The best performances are achieved for high initial oil and water saturation cases. The dominance of the low temperature oxidation (LTO) reactions is observed in the experiment with the intermediate water saturation (16%). The combustion front for the experiments without water (Swi=0%) could not sustain. The combustion tube results are further investigated with the reaction kinetics experiments. Hence, ISC experiments are simulated by TGA/DSC at constant (5, 10, and 15 °C /min) and varying (observed during combustion tube experiments) heating rates. The combustion tube tests suggest that water is a critical component which maintains the sustainability of the combustion process. The reaction kinetics experiments reveal that at the latent heat, interaction of steam with bitumen enhances the burning characteristics of bitumen. If the combustion front temperature (~ 400 °C) is reached with low heating rates (5 °C /min), the LTO reactions lead the formation of several different types of fuel which cannot generate sufficient heat to maintain the sustainability of combustion. Hence, LTO products adversely affect the performance of ISC for the cases which had insufficient heat generation or no initial water. However, higher heating rates (10-20 °C /min) lead the formation of more effective fuel which can generate more heat upon cracking at higher temperature ranges and maintains the sustainability of the combustion front. Because at lower initial oil and at no water saturation cases lower heating rates are observed during ISC experiments, ISC could not sustain. And, since at higher initial oil saturation with the existence of initial water saturation cases higher heating rates are witnessed during ISC experiments, the combustion process could maintain sustainability. Therefore, we recommend the injection of water to the zones with lower initial water saturations prior to field application of ISC to increase the heating rate of ISC zones.
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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) | 0.000 | 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".