A new reaction model for aquathermolysis of Athabasca bitumen
Bibliographic record
Abstract
Abstract Aquathermolysis of bitumen occurs when it is thermally cracked in the presence of water. Current in situ technologies for bitumen production, such as Cyclic Steam Stimulation and Steam‐Assisted Gravity Drainage, inject high pressure, high temperature steam in the reservoir to heat the bitumen which in turn lowers its viscosity enabling flow to a production well. Thus, the major physical effect of steam is the heating of bitumen which mobilises it. Beyond physical interactions, chemical effects also result: steam heating produces acid gases, such as carbon oxides, sulphur dioxide and hydrogen sulphide along with small amounts of hydrogen and methane. For steam‐based in situ bitumen recovery processes, nearly all analyses, including simple drainage theories and thermal reservoir simulations, focus solely on the physical processes: heat transfer, fluid flow and thermodynamic equilibrium. However, steam chambers are also underground reactors: bitumen aquathermolysis occurs due to high temperatures and water saturation. Here, we describe a new in situ aquathermolysis reaction scheme for Athabasca bitumen to predict hydrogen, methane, carbon oxides, hydrogen sulphide and other heavy molecular weight hydrocarbons. Reaction parameters were fitted against one experimental data set and validated against other independent experimental data sets, both from the literature. Our results indicate that, to more accurately predict gas compositions and rates, the effects of aquathermolysis should be taken into account in reservoir modelling. © 2012 Canadian Society for Chemical Engineering
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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; 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".