Mobility of Gas-in-Oil Dispersions in Enhanced Solution Gas Drive (Foamy Oil) Exploitation of Heavy Oil Reservoirs
Bibliographic record
Abstract
Abstract In the cold production of foamy heavy oil under solution gas drive, the oil and the released solution gas are believed to flow in the form of a gas-in-oil dispersion. The mobility of such a dispersion is an important issue in the mathematical modelling of the cold production process. However, very little factual information is available in the literature on the mobility of gas-inheavy oil dispersions. The objective of this work was to fill this gap in our knowledge of foamy oil flow behaviour by measuring the mobility of gas-in-heavy oil dispersions under varying conditions. A new apparatus was developed for measuring gas-in-oil dispersion mobility as a function of the dispersed gas fraction and the pressure gradient. It uses a sand-pack holder with three sections of different diameter to produce three different pressure gradients in the same flow test. An in-line mixer was used to generate live oil for producing the foamy dispersions. Several validation tests were conducted to check the equipment and procedures. Tests were carried out with a viscous mineral oil, as well as with a heavy crude oil. At a low gas fraction, such as would exist immediately below the bubble point pressure in the reservoir, the apparent viscosity of a gas-in-oil dispersion was higher than that of the live oil at the bubble point pressure. At high gas fractions, the apparent viscosity of the dispersion was lower than that of the live oil at the bubble point pressure. The boundary between low gas fraction and high gas fraction was in the 15% - 20% gas fraction range. Therefore, in the interval 0 to 15% - 20% gas fraction, the apparent viscosity increases with increasing gas fraction, and then at higher gas fractions, it decreases with increasing gas fraction. The apparent viscosity was also found to vary significantly with the pressure gradient; in general, increasing with increasing pressure gradient. In terms of the relative permeability, it was found that the oil relative permeability varied significantly with pressure gradient and displayed a value of higher than unity at an optimum combination of the values of the pressure gradient and fractional flow of oil. The gas relative permeability remained low in all tests. A comparison of the mineral oil tests with the crude oil tests showed that the two systems behaved similarly. Introduction "Cold production" is the term given to a successful, but as yet not fully understood, heavy oil production technology. The term "cold" emphasizes the fact that no reservoir heating is involved. It is essentially an improved form of primary production by solution gas drive that may also be termed enhanced solution gas drive. The improvement consists in the increase of recovery factors compared to conventional primary production and is induced by producing the (vertical) wells at very high rates. The most significant difference between the new technology and the conventional one lies in the attitude toward the sand influx into the production well.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".