A Novel Approach in Understanding the Role of Water in Oxidation and Upgrading Reactions during In-Situ Combustion Oil Recovery, Part B: Interpretations
Bibliographic record
Abstract
Summary To understand the role of connate water as a source of hydrogen in oxidation and upgrading of bituminous oil at high temperature, heavy water (D2O) and O-18 enriched water (H2O18) were used as connate water in two different in-situ combustion experiments using a conical tube. Aside from a fundamental understanding of the role of such reactions in in-situ combustion, the results could also potentially help in optimizing in-situ hydrogen generation and upgrading of heavy and bituminous oil. The conical tube had previously been used for understanding the impact of air flux in sustaining the combustion front (please see Alamatsaz et al. 2011Alamatsaz et al. 2012,2). Significant upgrading was observed in these tests with a produced API gravity of 35 °API compared to the original bitumen gravity of 9 °API. The produced fluids (gases and water) were analyzed with a mass spectrometer to demonstrate the effectiveness of using D2O and H2O18 as tracers in bitumen upgrading reactions and specifically to determine whether the H2O18 would be more effective than D2O in understanding the role of connate water. It was found that heavy water exchanges too readily with hydrogen atoms in the bitumen when the two are mixed. As a result, it could not be reliably used as an indicator for identifying the role of water. The run with O-18 enriched water, however, provided a better indication of water participation in the oxidation reactions. The results obtained from the mass spectrometry analysis of evolved gases and water samples collected in the second test showed that water does split during the reaction and O atoms of indigenous water molecules do combine with C atoms (from the hydrocarbon) to form CO2. These findings open the path for mechanistic considerations around the processes taking place during in-situ combustion and in-situ upgrading reactions.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".