Numerical Simulation and Screening of Oil Reservoirs for Gravity Assisted Tertiary Gas-Injection Processes
Bibliographic record
Abstract
Abstract Corefloods and field investigations confirm that a large amount of incremental tertiary oil can be recovered from dipping water drive reservoirs using gravity assisted tertiary gas injection processes. These processes include the Double Displacement Process (DDP) and the Second Contact Water Displacement Process (SCWD). The DDP consists of injecting gas into waterflooded oil zones. The SCWD process consists of submitting these gas-flooded zones to a new water displacement process. Reservoir simulations performed with an adaptive-implicit simulator were applied to investigate the macroscopic mechanisms of the two processes. The effects of several important parameters on the performance of the DDP were studied to optimize the oil production of the process and to develop a set of screening criteria for selecting candidate reservoirs for the process. Moreover, the SCWD process was simulated to investigate its feasibility. Furthermore, the two processes were simulated physically in a micromodel – transparent cell. The results have shown that both processes are efficient methods for recovering the residual oil to water. A good representation of the laboratory results was obtained through the simulations. It was confirmed that oil film flow plays a very important role in achieving high recovery efficiencies in the DDP. In the SCWD process, trapped gas reduces the possibility of the residual oil being trapped in the center of pores in the secondary water invasion. Consequently, residual oil can be recovered quickly by a second water flood. Therefore, the SCWD process is suitable for application in situations where the source of gas is not sufficient, and where the formation has a high irreducible gas saturation.
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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".