Extra Heavy Crude Oil Downhole Upgrading Using Hydrogen Donors Under Cyclic Steam Injection Conditions: Physical and Numerical Simulation Studies
Bibliographic record
Abstract
Summary Physical simulation experiments of a downhole upgrading process showed that the use of a hydrogen donor additive (tetralin) in the presence of methane (natural gas) and mineral formation under cyclic steam injection conditions led to an increase of at least three degrees in API gravity of treated extra heavy crude oil, a three-fold viscosity reduction and an approximate 8% decrease in the asphaltene content with respect to the original crude. A continuous bench scale plant was used at different temperatures (280 – 315 ºC) and residence times (24 – 64 h) for carrying out kinetic studies. A reaction model involving four pseudo-components (light, medium, heavy and asphaltene fractions) was used and the kinetic parameters (pre-exponential factors and activation energies) were determined. Using these data, compositional-thermal numerical simulations were carried out and validated using the bench scale data. The results showed a good match between the calculated and experimental ºAPI gravities of the upgraded crude oil (average relative error 4%). Using the previous model, the downhole upgrading process was numerically simulated under cyclic steam injection conditions. The simulation runs showed the production of 12 ºAPI upgraded crude oil, accumulated over a 70-day cycle. However, a reduction in the percentage of conversion of tetralin was observed (0.8%) in comparison with the bench scale experiments (3%), which was attributed to gravitational segregation of the steam coupled with low mixing efficiency of the hydrogen donor with the extra heavy crude oil at reservoir conditions. Introduction Underground upgrading processes have always been of interest to the petroleum industry, mainly because of the intrinsic advantages compared with aboveground counterparts. Lower lifting and transportation costs from the underground to refining centres can be achieved, as well as a potential increase in the volumetric production of wells. In addition, a decrease in the consumption of costly light and medium petroleum oils used as solvents for heavy and extra heavy crude oil production can also be obtained. Finally, the use of porous media (mineral formation) as a natural chemical 'catalytic reactor' will allow the improvement of the properties of the upgraded crude oil, further reducing expenses for downstream refining operations. Several methods of underground crude oil upgrading have been reported. These concepts include downhole steam distillation(1), deasphalting(2–5), underground visbreaking(6–9), hydrogen(10–17) or hydrogen precursor injection(18–22) and in situ combustion(23–25). With the exception of the latter, the numerical simulation of downhole upgrading processes has relatively little research on it. Shu and Hartman(8) and Shu and Venkatesan(26) used compositional simulation and experimentally measured kinetic data to determine the effect of the visbreaking reactions on the percentages of recovery of heavy crude oil produced by cyclic steam injection and steamflood. For the former route, the authors found an increase of 5% in the oil recovery due to viscosity reduction in the heated zones of the reservoir(8). Similarly, Kaskale and Farouq Ali(7) reported the numerical simulation of a steamflood in a five-spot array for the production of upgraded Saskatchewan crude oil.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 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".