Applicability of SAGD in Eastern Venezuela reservoirs
Bibliographic record
Abstract
Although Venezuela has one of the largest heavy oil accumulations in the world, the high viscosity of the oil poses a challenge in terms of economic recovery. Steam assisted gravity drainage (SAGD), which was originally used to develop heavy oil and bitumen reservoirs in Canada, has been proposed for the production of oil fields in eastern Venezuela. In order to apply SAGD for Venezuela's heavy oil reservoirs it is necessary to understand the process as it applies to the different pressure, viscosity and temperature (PVT) conditions between the reservoir on both countries. This study investigated the effect of the component grouping for fluid characterization in order to evaluate the potential productivity from this technology and propose the best SAGD performance. The original 14 components identified in the existing PVT analysis were reduced into 2 and 3 pseudo-components. The stability and results using both fluid characterizations were compared to attain reasonable running times in the simulation process. A sensitivity analysis was conducted using thermal simulation. The parameters analyzed were vertical well spacing, injection steam rate, well flowing pressure, and horizontal length. The effect on the oil recovery from the angle of dip in the reservoir and the orientation of the well pair in the reservoir was also analyzed. A steam injection rate of 400 tons per day provided the optimum cumulative steam-oil ratio (SOR) for the cases analyzed. A differential pressure of about 200 psi improved the oil recovered and decreased the SOR. The case with the best oil production performance was obtained for horizontal lengths of 2,000 feet. At this value the oil production reached a maximum and the SOR a minimum. Oil recovery also depended on proper well placement accounting for the dip angle of the portion of the reservoir where the well is located. It was concluded that SAGD technology has considerable potential to increase the oil recovery factors from eastern Venezuela heavy oil reservoirs. 6 refs., 10 tabs., 16 figs.
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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".