An Improved Kinetics Model for In Situ Combustion of Pre-Steamed Oil Sands
Bibliographic record
Abstract
In situ combustion (ISC) has been recently evaluated as a follow-up process to steam assisted gravity drainage (SAGD) with the expectation to combine the advantages of SAGD and ISC. Before the design of such a hybrid process, it is important to understand the chemical reactions between air (or oxygen) and residual oil within a SAGD chamber in the presence of water and steam in order to simulate the process with a reasonable degree of confidence. In this study, an improved reaction kinetics scheme, in terms of Saturates, Aromatics, Resins, and Asphaltenes (SARA) fractions, is proposed to represent the complex chemical reactions during ramped temperature experiments. From the results of a set of laboratory ramped temperature oxidation (RTO) tests, the oxidation behavior at different temperatures has been carefully analyzed. On the basis of the analysis, a reaction kinetics model consisting of low temperature oxidation, thermal cracking, and high temperature oxidation reactions has been developed. This model has then been incorporated into CMG STARS to simulate RTO experiments. The experimental results of seven RTO tests, including temperature profiles, oxygen consumption, and carbon oxides production, have been successfully matched by tuning kinetic parameters. From the experimental and simulation study, it is found that the coke, which is formed through cracking reactions and traditionally considered to be the main source of fuel in ISC, reacts slowly at high temperatures in the RTO tests. The other source of fuel for combustion in the RTO tests is light hydrocarbons distilled from the original bitumen or cracked from oxidation and cracking reactions. These light hydrocarbons are responsible for the rapid high temperature behavior observed in the RTO tests. This work greatly increases the understanding of fuel sources, and the proposed model is able to predict oxidation/combustion behavior of pre-steamed Athabasca oil sands under a wide range of temperatures.
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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".