Production of Gases During Thermal Displacement Tests
Bibliographic record
Abstract
Abstract During laboratory testing of thermal processes (hot water and steam displacement of bitumen) a consistent observation has been the production of very high gas volumes with produced oil and water. These gases are many times more in volume than what is expected from solution GOR and what is observed in the field. This paper presents an ensemble of experimental results of thermal displacement tests in oil sand and bitumen bearing carbonate rocks. The focus of analysis of these tests deals with the generation of non-condensable gases. Various laboratory core floods are run over a temperature range of 160 – 200°C+. Tests are run on native-state oil sand and carbonate samples, containing original saturations of bitumen and connate water. Cores are exposed to either hot water or steam, in linear flooding configurations or soaking conditions. The output from these tests is a measurement of produced gas volumes and compositions as a function of either soaking time or volumes of water/steam injected through the core. Tests were conducted on McMurray oil sand, Grand Rapids oil sand, and carbonate systems. During thermal displacements and at temperatures as low as 160°C, gases are generated. The gases are predominantly CO2 and H2 with traces of CH4 (which is usually seen early in the experiments) and other low carbon hydrocarbons. The last ones are usually at the noise level of the analytical instruments. What is significant is that at the lower temperatures there is no apparent generation of H2S and that supports the fact that the gas generation process is not aquathermolysis driven. The generation of gases is apparent in bitumen rich and bitumen free samples. This supports the assumption that the generation of gases is geochemical in nature, as well as through organic decomposition. The conclusion of the analysis indicates that the generation of such gases is caused by the combined effects of water/oil and water/solids reactions. Gas generation is affected by the system conditions and in general higher gas volumes are produced at lower P/Psat. Gas production is also strongly affected by surface contact between water and solids, which leads to lower apparent gas generation rates in carbonates compared to oil sands, and higher gas production from floods compared to soaking tests. The effect of such reactions in the exploitation of clay bearing sands and carbonate rocks is that the generation of extra gases will affect the thermodynamics (partial pressures), heat transfer (insulation) and relative permeability curves of the intended processes (SAGD, CSS, SAGD-solvent).
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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".